Coveo Solutions Inc. (CVO) Earnings Call Transcript & Summary

Good morning, and welcome to Coveo's very first Capital Markets Day. My name is Paul Moon, I'm the Head of Investor Relations. And I would also like to welcome those that are joining us online via the webcast. It's a pleasure for you to attend, and thank you so much for spending your time with us. I would also like to note that this event is being recorded, and a replay is accessible on our Investor Relations website after the conclusion of today's event. Moving to the agenda, just quickly here. As you can see, we've got quite a comprehensive program. We're going to kick things off with Louis, our CEO and Chairman, and we're going to move on a technology demonstration by our Founder, President and Chief Technology Officer, Laurent Simoneau. We will also go to go-to-market with Louis and also marketing, our Chief Marketing Officer, is in the room, Sheila Morin; and will also discuss a little bit ESG. We have a 15-minute break in the middle. So I'm sure you'll welcome that. And I'm really excited about the customer panel. We've got a couple of fantastic partners with us today. And thank you so much for joining us on this event And of course, this would not be a Capital Markets Day without a financial review, and we have Jean Lavigueur, our CFO, to present this material. Lastly, we also have a Q&A session, and I would ask those that have questions to kindly wait until the Q&A session. And we will have a couple of mic runners, I'll be one of those and kindly raise your hand for your questions, and we'd be happy to address them. Those on the webcast, there is a dialogue box if you want to submit a question, by all means, please do so. We will take priority for those that are in the room to answer questions. But if there's something we cannot address, we'll certainly deal with that off-line. A little on this slide is, of course, our legal disclaimer. The material being presented should be considered along with our AIF or MDA and most recently filed financial statements available on our website and also on sedar.com. We will be making reference to non-IFRS measures and ratios. And of course, the reconciliation of those ratios to IFRS is available in the appendix. We also have a definition of these measures in the appendix. Also, we'll be making reference to KPIs that are relevant to us in our industry and a definition of those is also available in the appendix. And lastly, all figures presented will be in U.S. [ funds ]. With that, I take great pleasure introducing our Chairman and CEO, Louis Tetu. Louis?

Thank you. Paul, and Welcome, everyone. I'll start my timer because I can talk forever about this company. This company is a passion. So thank you all again for being here. So first of all, thank you to all of you for amazing turnout and for your interest in the company. You've obviously heard a lot about the company through the earnings calls for many of you during the IPO road show and through the various presentations. We're going to try today to -- not to repeat everything you know, but to take you a little further. I think you'll -- hopefully, you'll find Laurent's presentation very enlightening. And really on the backdrop, this is about communicating to you our excitement and what we see. At the end of the day, we can't control the markets right now. Coveo has performed well since the IPO. The markets like the tide. We can control the boat, and we want to talk to you about the speed of that boat, the quality of that boat and the size of that boat. And right now, what we're seeing and communicate to you why, what are the fundamentals that make Coveo such a high potential company, at least in our view, so that's not a forward-looking statement. That's in our view. Coveo is an AI platform. Fundamentally, we were born in AI a dozen years ago. with the desire to use AI essentially to create more relevant experiences, essentially use artificial intelligence to essentially recommend. And so they say, we started as a search vendor. When you're in the search business, it's really about delivering the right set of results, and that's fundamentally a recommendations process, and we're going to talk about that. And really, our focus is on enterprises and our focus is on helping enterprises deliver great experiences. And the word profitably was added in the past year, where it's not only about using algorithms to deliver highly personalized experiences that people love. Think about your Netflix experience. This is often an analogy I use. But how do you do that to maximize business outcomes? And we're going to talk quite a bit about that, and that speaks volume about our direction from an R&D and investment perspective as a firm. For those of you who are newer to the story, fundamentally, Coveo is built around the fundamental belief that digital experiences that digital leaders have raised the bar. Think about you as a consumer. We're all a browser window away from taking our experience to Amazon and to Wayfair in the furniture industry and to Spotify or to Booking.com or to even walmart.com or Target. But there are very, very few companies that do that very well. These companies have hired herds of data scientists. Wayfair has 2,200 developers and data scientists, not the usual profile of a standard furniture company. And so what happens is these companies have raised the bar. Essentially, where we expect highly personalized experiences that essentially are designed just for us. We expect experiences to be really, really people-centric, not product-centric. So in the former world, let's say, you were doing e-commerce, you would serve a catalog, you would push products into the market. Now it's about understanding who's at the other end and then designing the experience towards that person. And this is really the genius of Laurent and his team. Literally more than a decade ago, turning search on its head and saying search is not about keyword or being able to retrieve content, it's about first and foremost, just like Netflix. First question and only question Netflix asks is who's watching? Because that's the one thing I need to know in order to assemble an experience that you will love and that will drive more consumption. And fundamentally, experiences today that are -- and we're going to talk about the imperative of AI, our experiences that need to be super coherent and even prescriptive that need to anticipate your needs, not only cater to your needs. And this is really, again, what Coveo does. And this problem is really, really important. Have a look at the McKinsey -- this is a McKinsey report from November 2021. So it's not that old. Personalization is no longer a nice to have but a must have for brands. So more than 70% of consumers expect one-on-one personalization, increases revenue by 10% and lowers CAG by 50%. And so that's very, very substantial. And so what happens is that if you fail to provide it in the world -- think about 3 audiences, think about consumers or buyers; think about customers, actual customers looking for service or information; think about employees even in the workplace. If you're dealing with prospects and you fail to deliver that, you're affecting revenue. If you're dealing with customers, your -- you failed to serve them in a way that you're going to increase your cost to serve. We're going to get into why. You're going to impact loyalty and so on. And if you're dealing with employees, it's a loss of productivity. If you can't give employees the information they need in the course of work, you essentially are missing out on a big opportunity. And so this is really what's going on. And what's going on within enterprises, and I can certainly share that I personally sit on some public company boards, and I sit on the board of Circle K and Questar essentially in Canada, and I've sat on other boards as well. Customer experience is a boardroom discussion. It absolutely is. And it has become more and more over the past decade because -- and it's -- so it's at the epicenter of the digital transformation conversation. And the minute you start talking about that, you start -- you talk naturally about personalization. It naturally leads itself to personalization. And you can't talk about personalization without talking about costs, revenue and margins because you can't just personalize at all costs. And so fundamentally, this is the epicenter of the digital transformation conversation and only AI and data can solve the challenge. What's happening in large enterprises is large enterprises deal with -- and this is our focus. Large enterprises deal with very large volume and variety of content and products. So we have customers in the commerce space that have 1 million SKUs. So when you have 1 million SKUs, it's tough for a merchandising team to do that manually. So you can't just say, oh, it's raining today, let's put umbrellas on sale. It's a little more complicated than that. That problem is compounded by the fact that they deal with very large and diversified audiences. Again, we have customers that have 1 million consumers a day. Bunnings in Australia, which is the equivalent of Home Depot, they have -- during the pandemic, they had as much as 1 million consumers a day. So it's Black Friday every day for them. And then -- so how do you do that while making sure that you're making profits. How do -- and only algorithms can solve that problem because it's very hard to deliver the expectations -- to the expectations of an audience that's asking for a very relevant experience. When you're dealing with millions of SKUs, millions of documents, many sources, many sources of content, lots of diversity, how do you make money at it? And that's what firms like Amazon and so on have become experts at. So it's a fight against algorithms, and you're either going to adopt these algorithms or you're going to fight against them. And if you're in the latter category, give me your stock ticker, I'll short you because you're not going to win. You're not going to win in that game. And so what we've done, and if anything, Coveo was early in its market, we've been -- we started out as a -- this has been 15 years of more of cumulative know-how here where we started as a search firm and Laurent's firm was an offshoot of the company named Copernic Technologies. And as I said, Laurent really turned search on its head, and I said it before by saying search is about understanding the person at the other end so that we got into the world of contextual relevance. That was in 2010, and that's the same year where we became Gartner top right in the Magic Quadrant for Enterprise Search, which is a very important report in enterprise software in the world of enterprise search. Google at the time was selling a box named the Google Search Appliance and wasn't even in the cloud. And we were already known back in 2010 for being the #1 very complex, advanced enterprise search firm. But that's only the beginning. Then Laurent decided to hire a bunch of data scientists take the company to the cloud and then build the machine learning and deep learning and AI, semantics infrastructure to deal with some of the world's most complex problems. The early adopters of this technology over these years, up until 2017 and 2018 were the tech companies. We have Bernard from Salesforce today. Salesforce is an amazing partner of ours. They're also a massive customer of Coveo. These are the companies, Salesforce.com, Intel, Dell, HP, F5 Communications, Zoom Communications, Adobe, et cetera. These are the companies that understood the power of machine learning and the importance of delivering personal digital experiences. And so for the better of those years, we worked across the tech sector. We started diversifying around circa 2017-2018 and taking that technology into manufacturing, into CPG, into financial services, into health care. So we work with companies like Cigna, Humana. We work with Schwab. We work with Vanguard. We work with Citigroup. We work with Chamberlain Garage Doors, LiftMaster. These are the companies today that use us all over the world. And because they too understand the need to use data to perform that personalization. So essentially, in the world of enterprise transformation, digital is old news. People talk about digital transformation. I would argue that you need to remove the word digital. Digital is old news. That's -- you needed to be digital 10 years ago. That's old news. We're beyond that. It's really about intelligence. There's a new category of software now. And I like the way Satya Nadella puts it at Microsoft, where he said, in the past, there were 2 layers of software systems of record where you store data and you manage data and all the infrastructure around it and databases and networks and et cetera. And then systems of engagement where people engage. Now there's a third layer, which are systems of intelligence. So if you look at the topology of a company, essentially, it looks pretty much like this. Your journey starts on websites. And you're going to hit the website, right? That's think of yourself against as a consumer. And so you start on your mobile device or on your website. Typically, the application that runs that website for most large companies is probably something like Adobe Experience Manager, which is -- runs the web content management infrastructure and all of that. Then maybe you want to buy something or transact, you're going to be taken to a transactional site. And that transact, you get into commerce, whether it's a marketplace or a B2C commerce engine or a B2B commerce engine, a retailer. Essentially, you're going to have an infrastructure, and that could be a Shopify. But unlikely, enterprises don't deal with Shopify. Shopify and Shopify Plus and et cetera, but the average Shopify customer process is about $100,000 of gross merchandise value a year. The average SAP hybris customer processes about $300 million a year of gross merchandise value. Some of them are north of $10 billion. And so you're dealing with commerce sites that are powered by technologies such as Oracle, ATG, IBM, SAP, et cetera. So you're going to be taken to that site and then you buy something and maybe you're going to come back for the warranty or you have an issue, you're going to go to a community, you're going to try to self-serve. And ultimately, you're going to hit a contact center. That's the world of customer service. And then behind the scenes, you have agents in the contact center in the workplace and then that can link back into areas such as research and develop -- product development, manufacturing or G&A or et cetera. That's the cycle. Fundamentally, what Coveo wants to do is -- and what Coveo does is we're the engine behind the scenes. And by the way, that's just an anecdote, but the Coveo logo was built on that. The Coveo logo is a signal on one side and an amplifier on the other side, 360 degrees. That's the way it was designed. And the reason is that we inject ourselves into these experiences and we collect signals that we can carry through the experience. In the world of AI The way I explain AI to my wife, who's a dentist and really is not really good with technology, is before AI, humans programmed data models and rules. You program rules on data models. After AI, AI finds the rules. That's the fundamental difference, and that's the transformational aspect. AI finds the rules because AI creates a flywheel effect. In a way, what I'm going to watch this weekend, if I do, if I watch something on Netflix this weekend in a butterfly effect, it will affect your next recommendation in the way Netflix will assemble your next experience. That's the power of AI. AI has the ability to process massive quantities of data and essentially figure out the rules. So AI in our world, learns from every interaction to make the next interaction better. And that's really the way that works. So it changes the world from that perspective. We built a platform for that. We built a platform that reaches content at scale, that collects in almost real time, the signals from every interaction and is able to serve dynamically the next interaction in real time. And we created solutions on top of that platform use cases. So one of them is in commerce. And the beauty and really -- and especially in this day and age, people talk to us about the economy and et cetera, Coveo is all about ROI. So despite the economy, we continue to believe that if -- I continue to believe that if I hand you -- no matter how the economy goes, if I hand you a bag of dimes, you're going to give me a nickel, I think so. Although right now, I'm not even sure, when I look at the markets, but in general, and that's what Coveo is. Coveo, we can come in, in commerce and essentially say, "Hey, we can leave your infrastructure as is, you're using SAP, you're using Salesforce Commerce, you're using Oracle, ATG, your using whatever, it doesn't matter, don't change that, don't rip and replace, you can do add the cards, you can show products, you can connect them to supply chain, you can process a payment and all of that. We're going to put our technology on top of that. Within 4 to 12 weeks, we're going to increase your revenue." That's what we're talking about. We're going to increase -- because by adjusting the relevance dynamically, detecting customer intense signals, making better recommendations, we're going to actually increase your conversion and we're going to increase your card sizes, and we can even start looking at constraints as we'll talk about in a few minutes around inventory availabilities around showing you the full catalog, detecting what's potentially higher revenue, higher margin, et cetera, and ultimately increased loyalty. If you're doing $1 billion of commerce, that matters. And we're going to show you some of those numbers and some of those examples today. In the area of customer service, especially in a tough economy, the first thing companies want to hang on to as their customers because that's the cheapest source of revenue. They want to take care of our customers, but they can't increase the cost. So how can you -- if you're not growing, how do you make customers happier and get more revenue from them without increasing the cost or potentially lowering the cost. If you're growing like Salesforce, for instance, has been growing all along, how do you grow the company without growing support costs linearly? And that's through self-service and pushing the right knowledge to the right customer or the right agent at the right time so that everybody self-serves and everything is more -- much more efficient and you don't need to hire as many agents and really bringing intelligence from across an organization to each customer in their context. And then from a platform perspective, we have a search and recommendation platform that essentially can increase, so on websites, you need -- there is also the requirement to make websites much more engaging. -- and much more personal. So there is no such a thing. It is no longer acceptable for a large organization to deliver vanilla to everyone to deliver the exact same experience to everyone. So when you go to a URL, the content should adjust dynamically as soon as you start clicking. Now 99% of companies don't do that, hence, the opportunity in fact. But the expectation is clearly there. And in the workplace, same idea. If you can enable more employee self-service, if you can make intranet, I don't know how many of you love SharePoint. I haven't met many people in my career who love SharePoint because the idea that you're going to feed a single platform, put all your knowledge into it and that you're going to go get everything you need from there is absolutely flawed. Content is everywhere. You need to be able to find the right content from across an organization and bringing in the course of work within 10 millisecond to help people become more proficient at what they do, and get the information they need. And that's exactly what we do. Although right now, as we'll talk -- I'll talk about later when I talk about go-to-market, it's very obvious to us that service and commerce is where there is a high ROI, but right now, we don't believe that companies will invest as much into -- and so for us, it's really right now about commerce and service, it's really about the idea that -- because those are high ROI solutions, this is how we land new accounts. So let's talk about commerce for a moment. And Laurent will go into more details. So I'll talk to you about commerce, I'll talk to you about service and I'll talk to you about the platform, the application. Commerce right now, we announced today in our last quarter was -- we had our best quarter ever. We're excited with our service business. We're excited with. We love all of our children the same, platform, service and commerce. But there's no question that the opportunity in commerce is mind-boggling right now. And I'd like to give you an example of how intelligent personalization can transform commerce, and I'll give you an example of how today companies work like this. So they look at things like traditional search engines look at click-through rates, and they monitor that and they serve you more of what's popular. So if you're a Canadian tire and you run a search engine, I'm going to understand what people click on and -- number one. So let's say, Product A 10%, Product B 9%. And then I'm going to look at ad to cart, what people buy? So people click on, A, a little more, but they don't add the cart this much and they click on B a little less, but they add the cart more. And so that's where right now the world is. And most companies stop right there. And search engines learn that and serve more of what's popular, what people click on and what people add to cart. You see -- we've all been on commerce sites where it says most popular products, for instance. But when you start doing that, what happens is that suddenly, the engine starts learning what's most popular. And typically, in retail, as an example, was most popular. There's a notion of popularity. But what is really popular is something that people love, and that's 30% discounted. Now that's really, really popular. So what the search engine starts doing is promoting stuff that's heavily discounted, and that's popular, it forgets to display the tail end of the catalog, the entire catalog to the consumer -- so those products stay in the warehouse because they never get sold. The margins go down, and the first thing you know is the stuff that's in the warehouse needs to get sold. So you're going to discount it 2 month from now. And that, my friends, is part of the reasons why in digital commerce, the margins went down dramatically over the past few years. When you start looking at more sophisticated algorithms, you start looking at things like that, margin, excess inventory. If you have 5,500 of product A in the warehouse, you got to sell them. And so that ought to be factored in, in what you're going to show customers as they come. And so how about return rates? How about shipping expenses, in stock, at store, brand support, et cetera. So what we're building, and we're continuing to do R&D there, we're building a -- that's the main difference between a search engine and intelligent AI platform. What we're building, in fact, is the algorithms that actually can deal with these multiple dimensions and make the best decisions to maximize both the balance between delivering great experiences, but driving, in fact, better revenue and better margins for the company. So we're doing a lot of R&D in that area. Our commerce solution essentially allows a company to deliver -- and again, Laurent will show you some visual examples of that and so on. But allows companies to deliver highly personal customer experiences. I thought they were clapping for us. And really -- but also where we're moving, and this is an ongoing thing, this is really the main R&D direction for us is automating revenue maximization. And this is a 5-year journey for us. We want to be and continue to be the best at that. So we're really taking it way beyond and then enable a different type of merchandising where merchants no longer make manual decisions about putting umbrellas on sale before it rains or barbecues because it's sunny, but where merchants will really have the tools to test and run machine learning. So essentially, our retailers, they not only want to be like Amazon, they need to be like Amazon. You don't have a choice because consumers, again, are a browser window away from going to Amazon. So this is where the bar is. And so you're dealing with complex demand, you're dealing with complex business, each product with different attributes. And then the merchants have insights, and they have a thousand of ideas that they want to test. And so we want to give them the infrastructure, the AI infrastructure actually, that allows them to both delight the customers, but really maximize revenue and profit at the same time. And nobody, nobody in the commerce world is talking about that. Nobody in the commerce world is talking about that. If you go to Salesforce.com commerce, if you go to SAP, if you go to Adobe, Magento, if you go to -- well, Oracle just shut down, it's -- or is winding down its commerce business and so on or IBM, they're not talking about the algorithms that actually do that. So these are the fundamental algorithms that are not about delivering commerce but are about making sure that companies actually sell and make money. And so we think that's really, really important. Laurent will show you that -- and this is just an example that in the world of commerce, different people looking at the same thing in the world of Coveo will actually get different recommendations as you see below, and I won't steal Laurent thunder, he'll talk about that. But essentially, there is a huge difference between the scenario on the right and the scenario on the left. And this, my friend is really, really fundamental to driving business and so on. So highly, highly important. And at the same time, how we can use deep learning to actually adapt in real time. It's called the Cold Start Problem. In the world of commerce, oftentimes, we don't know who's at the other end. We don't even have a cookie. And just by watching behavior through deep learning, we can actually adjust a different type of experience, and again, Laurent will show you that, but we'll also show you the financials on how that moves the needles. And that's an example. Clarus Shoes is an example. They own 14 brands of shoes. Allen Edmonds and Famous Footwear, Enrico, Sam Edelman and et cetera. And you see the types of increases in conversion and lift in conversion rate that we're doing with machine learning. That company does more than $3 billion worth of sales of shoes. And so that really matters economically. In the area of service, we're -- it's really about increasing customer satisfaction by driving a better experience. So that's important because it impacts revenue, it impacts loyalty, it impacts retention, but really, at the same time, improving the agent efficiency and reducing cost. So how can you get both is really the idea. In historically, if you wanted to improve customer service, you needed to spend more money. What Coveo is doing is we're going to companies and we're saying, "Hey, through better algorithms by using AI, you can do both. You can drive more self-service intelligence." And when you drive self-service customers prefer that. I don't know how many of you say, "Hey, I really -- when you wake up in the morning, I really want to go talk to a contact center agent today. I'd really love that, right?" Nobody likes that. So the idea here is you can do both and we are at a point where we're now starting to triangulate what's the impact on OpEx and obviously, cost reduction of self-service, call deflection and et cetera. And then ultimately, how do you turn service from a cost center to a profit center. And we're doing a lot of work around the analytics and dashboards and and BI to understand the financial impact of that. We already know that it's huge, and you're going to hear from Bernard at Salesforce later on today. So the AI service solution of Coveo is the same platform, but in this case, applied to service. In this case, what we do is we use that same technology to provide intelligent knowledge in the course of a self-service interaction or even in product and then we recommend it for agents. So when agents need to interact, we connect them as well. And then we connect the full experience. So what we mean by that is we're able to integrate Coveo in there -- in the software. So at Salesforce, Coveo is in the product so that you don't even need to leave the product to get contextually relevant recommendations of knowledge and the help files, et cetera. We're behind chatbots, then we push knowledge real-time, as you try to submit a case, if you haven't been able to self-serve, and we still try to deflect and avoid that you're going to talk to an agent. If you do talk to an agent, we're going to be the inside panel of the agent that understands the customer context and the upstream journey to tell that agent what kind of knowledge is required, so that the knowledge can solve the issue quickly, and all the way to age and full search of knowledge, et cetera. So we provide the entire end-to-end knowledge experience. Again, that increases customer satisfaction and reduces cost. So it's really, really important. And we have huge customers doing that. Xero is one of them. Xero is the largest SMB accounting software firm in the world. They're based in New Zealand. They have 3 million businesses using their software. They're bigger than Intuit in the space. And we moved their self-service from less than 70% to 95%. Every time we do that, they don't need to hire an agent, essentially. That's what, that really means in this particular case. And then the platform itself is really the ultimate glue of that story. So we will see in the go-to-market section that we land with commerce and service, but then we are in a position to go to the CIO and say, "Hey, Coveo can be your unified intelligence layer across the entire enterprise. And we do that for many customers, and Salesforce is one of them. Again, you're going to hear from Bernard, who's Vice President of Salesforce. But these are all the use cases that Coveo helps power at Salesforce today, and we keep continuing to expand. So it's the AppExchange, which is the largest business apps marketplace in the world. It's their websites, it's Trailhead, which is all the personalized learning, it's the customer self-service and so on. So Coveo is an extremely -- we've demonstrated here, we're an extremely flexible platform. So we have the ability to take that -- those stories, and we do the same for HP, for Dell, for a number of them and go to the CIO and say, "Hey, sign an enterprise license agreement with us, and we can essentially roll out Coveo as your single source of customer interaction signals and your single central AI engine to run a fully connected customer experience across the board." We think that's a huge market. Our view hasn't changed since the IPO and the details on how we compute that are in our filings. But essentially, I would argue that from a value creation standpoint, only in commerce, if you take the installed base of SAP in the commerce world, by the end of this year, the SAP commerce group of customers will be processing about $1 trillion of gross merchandise value of sales, of revenue. Technically, theoretically, if you put AI on top of that, that's another $100 billion that you're going to increase that revenue, notwithstanding the fact that you're probably going to double the margin from that revenue. So this is a very, very significant value creation, and this is a very significant market. For us, and I'll conclude on 2 things. For us, it's really about -- we look at Coveo as a start-up literally, despite the size we are today. We're still a small company. But we're really building an infrastructure. My day-to-day job and the management team is really focused on these 6 pillars. So first of all, how -- and I'll talk about it in go-to-market, where we focus the company to get better economics for the shareholders is our #1 focus. How we gain efficiency? You see us gaining more operating leverage faster and becoming really, really much more efficient, quicker. This is really a key initiative for us, and it's not about cutting costs, that's not the idea we're growing. And -- but it's about making sure that we continue to tune the organization, and again, I'll talk about that one as well. We were tuning our go-to-market model, and Sheila and I will talk about that later on. We're designing completely -- constantly reengineering the customer journey so that it becomes -- we reduce the friction to engage with customers. We create a simpler customer journey that is delightful and so on, and that's how we've built our brand and our reputation. We're bringing the customers into innovation. We have now customer advisory boards and our product managers are very active with our customers and so on to understand how we can move the needle and how we can partner with them in results. And finally, we're really focused on our people. Coveo is a culture of relevance and excellence. And there's a lot of -- I personally spend a lot of time on making sure that the right people are getting on the bus and -- for scale and that we preserve a very high performance and leading culture. And that's really -- those are the 6 things that certainly I worry about when I wake up in the morning. From a growth perspective, it's -- we have many opportunities. Most software companies sell 1 application. I built with [indiscernible] our COO, business before named Taleo, and it was a very good business in the HR world and so on, but we had 1 app. It was a talent management SaaS application that we sold in the world across the world. But we didn't have much opportunities other than to upsell. When our customers hired more employees, we charge them a little more. In the case of Coveo, we have a platform that has -- on which solutions run. And we can cross-sell new use cases. If I land with commerce, then I can go back to you and talk to you about service. And then there's a compound effect of using more use cases from us because we collect the data along the way, and we can connect ultimately commerce, to service, to web and et cetera. And so there are many opportunities for us to grow and to grow also our pricing, we think there's a lot of headroom in terms of getting a bigger share of wallet, essentially from our customers. Number two, we're continuing to acquire new customers. We're expanding into new use cases -- we're working with systems integrators and expanding Accenture, Deloitte, E&Y, Perficient, [indiscernible] a number of them. So we're expanding the distribution infrastructure continuously. And #3, we have the ability to develop new markets. We think Asia-Pac has some -- offers some opportunities for us. We're growing in Europe, thanks to the acquisition of Qubit, but also quite a bit of organically. And we have an ability to do that. And then we're going to pursue M&A when -- in a responsible fashion -- when the valuations, I would say on the private side come down and make sense for our shareholders. So that's -- those are really the levers that we can pull to grow the business. And above all that, I'll say, making responsible choices. So with that, that's a bit of an intro. I hope you appreciate it. And we're obviously extremely excited with the growth prospect of the company. And now you'll see it in action, which is really at the end of the day, what matters is what a customer sees and how we create value and how we triangulate that to the economic value of what we do, which drives a lot of what we can charge for our software. Thank you very much.

All right. Thank you, Louis. Good morning, everyone, and good morning to our remote audience. So my name is Laurent Simoneau, Founder, President and CTO of the company. I'd like to say I'm the old guy here. So in the next 30 minutes-or-so, we're going to give you an update of where we are, what we're investing in, what is important for us and what is strategically important for our customers, which is quite tight. So I'd like to start with an update on this slide. Some of you have seen this slide before. So that's new version of the slide, reflecting our priorities and reflecting where we're investing. So we are an engine in the middle. We have a platform that is driven by AI that does classic enterprise search on the left side, so we are indexing all sorts of content in the enterprise securely so it can be searchable in fractions of second, okay? So that's a classic Coveo. On the right side, that's the behavioral data that we capture from all of those experiences on the top that we power with search with recommendation in a personalized fashion. We capture all of these behavioral data, collect searches, page views [ add to carts ] and so on. So we capture all of that and transform that into machine learning powered relevance, AI-powered relevance. And we do that across multiple lines of business. Louis mentioned, really commerce and service being our 2 main lines of businesses. This is interesting because those are 2 different challenges. In service, most of the time, if you're going to ask for help, you're going to be logged in. You're going to provide your user identity and so on, right? In commerce, especially in the B2C e-commerce, 75% of the sessions are anonymous. So how do you personalize anonymous sessions? That's an amazing challenge that we are addressing right now. So how are we going to do that? We are, first of all, measuring everything that we do through AB testing, so we can increase revenue per visit in the context of commerce, profitability is the future, conversion and so on. How are we going to do that? We are capturing a lot of information on our platform. We are indexing content with security and permissions and so on. But then we are starting -- so we already have a user profile, for those who are familiar with the CDP market, so we connect to existing data in CDPs and our customers are also sharing with us a lot of this data about their operation. So we capture all of that to build our machine learning models. Now we are experimenting with sub-customers about things like cost to serve, long-term value of customers, propensity to buy and so on. And same thing on the product catalog, especially in commerce, we already have store availability, when there's a brick-and-mortar store associated to the e-commerce. We care about entitlements in the context of B2B commerce, got different price lists for different customers, right? But now we are experimenting with some customers about with product margins, they're sharing with us their product margins, which is critically important if the ultimate goal is to look at overall profits, right? Cost of shipping and probability of returns, so all of those things are related to product margins. So that's a big deal. We are experimenting with that as we speak. So all of those experiences at the top that are powered by Coveo, we position ourselves as the intelligence behind while our customers can build user experiences with our own tools, most of the time, they will use our APIs behind the scene to power those experiences. So that's why I would like to say where the intelligence behind. We like to do this at a high scale. We look at big problems where there's a lot of volume, a lot of different users, complex product catalogs, complex customer service environments, we thrive there. The more complex environment is, the most value we're going to create. We focus on the data, the behavioral data so we can build specialized AI. So I mentioned the difference between service and commerce. So from the same platform, we build different models that will specialize for the audiences and the problem at hand. And we do all of that with the utmost respect for privacy and security. That's the deal that we have with our customers. They trust us with their customer data. So we take that very seriously. So let's look at what we do in commerce are areas of investment, what we care about, what is important. So first of all, the first point is relevance in value. How are we going to create or help create great experiences for the shopper and bring value for the merchant? And that's where we also have additional capabilities around merchandising that we will show you. Strategic integrations. So there are big platforms out there that are capturing a lot of commerce volume, we think we can help make those environments and those platforms better and enterprise capabilities is about our ability to deal with big, complex environments. At a very high level, this is what we care about. Understand the shopper intent to provide the best results, right? You're looking for fish in a grocery store, we're not going to give you fish cookies, like it is right now with some big grocers, right? So that's the relevance part. But then if you're only showing what people want, that is at the highest discount, then the margins may be a problem down the road. So we need also to couple that with the business outcomes that are defined by the merchandisers and align both at the same time for us, that's in a way the holy grail. And no one is doing that, I would say, in the proper way for all sorts of reasons, technology is hard to build. The data may not be available at the same time. So we're really focusing on that right now with our strategic customers are getting to a point where this will be aligned perfectly. So let me give you a few highlights on what we have built that will help us get there. So to understand the intent of a user or a shopper, you need to understand, you need to have a little bit of personalization running in the background or a lot of personalization actually. Problem is, you're anonymous, you -- we have nothing on you basically to personalize your experience, right? So how do we do that? Under the hood, we capture all of this behavioral data from other shoppers, we mix that with the product catalog, we create what we call product vectors. So we understand what's the natural path from 1 product to another in the product catalog, not defined by the merchandiser, defined by other user sessions. And that's what we base to power one-to-one personalization for shoppers. So it works in real-time, it works for search, it works for product listing, it works for a recommendation. So let me give you an example here. I am on a shopping website. I'm looking for -- I'm browsing and I'm looking for T-shirt, baseball hat and a few additional things. And then I search for man hoodie, right? This is what I'm going to get. All right, it kind of makes sense with my history. Merchandisers have not created those links. It's been done automatically. Let's look at the different sessions. I'm looking for gloves and [indiscernible] like I live in Quebec City, Canada. So in November, that's what I need to look for. I'm looking for men hoodies. Look at the different results. This is all done automatically. This is done automatically because folks in the past that were looking for this on the top presumably bought what was there in the bottom. It needs to be embedded in the experience, it needs to be transparent and it needs to be fluid. So we're expending that with some of our strategic customers right now, and we're seeing already a very good impact from revenue per visit. When we're doing A/B testing between experiences that are classic, powered by Coveo, and experiences where we're enabling this one-to-one personalization. So we're quite excited by this. Some elements also that are helping from a conversion perspective and revenue per visit perspective. So we -- for a long time, we've had store availability, which is quite important, especially post COVID. So people may buy online, but pick up in store. People may want to see is this available in the store and all of that. So it increases conversion. We've proved that. So variance, so color size and so on at the first level, this is super important. If you're like me and you're trying to buy the shirt, it's only available in medium-size, it's not exactly a great experience, right? And what we brought from the Qubit acquisition is also the ability to the badging. So the merchandisers will create badging rules and insert that into the experience. I'll show you a little bit more what's the view on the merchant. So how do we now provide great consoles and tools for the merchandiser to configure the whole experience, right? So this is the evolution of the Qubit product that we acquired last year. We call that the Coveo merchandising hub. From that console, you have the ability to personalize content, create badges, configure product recommendations on. But importantly, you can build campaigns. You're building campaigns, from those campaigns, you can do analytics, and you can get product insights on what works and what doesn't in real-time. So you have -- for instance, here, you have a few campaigns and you see that there is an incremental revenue generated versus the baseline. If I click on the campaign here, you can look at the campaign metrics, you can look at conversion rate, revenue per visitor. You can look at additional data here because often in online stores that data may not be reliable, right? So all of this helps the merchant understand what's going on and make decisions on what's working and what's not. Now this is new. And this is what we're testing with customers right now. So that's the merchandising for product listing manager. Think of a category page, so men's sweater or things of that nature, merchants will want to have some control on what they're showing. So they are trusting AI and machine learning, but sometimes you're releasing a new item or so on, how are you going to surface that, right? So one way to do that, and that's what we've built in the past months, we call that a product listings manager, you will see here all sorts of listening pages of category page. You're going to select the men's sweatshirt, and you already see revenues and conversion and bounce rate and you all see metrics tied on that, right? So I want to boost Nike products. I'm a merchant here. I want to boost Nike products. We've got a promotion, I want to boost that, right? So how are you going to do that? Click here, select brand. Say, brand is Nike. I want to push that. And boom, as a merchant already you see the results changing. Then as a merchant, you may want a drag and drop, you may want to say for this listening page, I want to see these results at the top. I want to pin those results. So you're going to drag and drop at the top here, the results, right? And then you can save this and test if it works and do A/B testing and test if it works. And then you can measure when this customer start sharing us with the margins, than in the campaign instead of just tracking revenues, we are going to track profits from those campaigns. And then, of course, we have all of those dashboards at the top that will track the overall system, how it works. So by mixing relevance and one-to-one personalization is a big component of the relevance and the merchandising hub, we think we're covering really the challenge. We're addressing really challenge of stores, online stores out there, right, bringing increasing revenue and increasing profits. With this, we think we have the right components. All right, so let's switch to service. We still and must care about relevance and value and service. The value is different. It's not about revenue, it's about case deflection, it's about time to resolution and metrics of that nature. And we do that with a lot of investment relevance. We care about omnichannel support. As Louis said, it's not exactly the best outcome to talk to a customer service agent all the time, right? So people want to get service across multiple channels. And we're investing quite a lot of resources, making sure that our integration in strategic partners like Salesforce are the best that it can be. So let's talk about the omnichannel and the journey. So when you're a customer, you have multiple ways to get service when you have a problem. And on the right, this is the most expensive one for the company to provide service. On the left, that's the most -- that's the cheapest one. So we -- our goal is to cover the entire journey through various methods, through various technologies, through various integrations and make sure that all of this journey is connected. So let's look at some examples here. Self-service success. That's -- in a way, that's classic search. You go on a website of Intel, you ask a question or you ask a complex query. We're going to service you the best answer that we found with a degree of precision. We don't show things that we're not sure about. Think of a little bit of what Google does, okay? We call that smart snippets. So we surface the answer from the question. Then we have classic search results. And then at the bottom, we also have people ask this, people ask that. And when you look at the analytics, that's quite popular. That's all based on the same technology from a question-answering standpoint. If you're not finding what you want and you want to log a case. So we call that as the deflection. So you get into a form like this one. This is from Okta, another of our great customers, and you're entering your content here, right? Oh, I need to change the MFA, I want to reset template, and you will see that on the right, Coveo is surfacing results automatically that may help you not log the case. And with our deep learning capabilities, we're servicing also tags that may help you route the case when you submit it. So you log a case. Now the agent within its console, so that Salesforce, Coveo is embedded in the Salesforce on the right side, the agent will have results coming from the entire enterprise being proposed, being recommended on the right based on the case that was just logged in. So the agent also has the ability to search. We're going to provide answers when we can, and then the results will also adjust. And then there's a session summary, what we call the user action, where the agent knows what the user has done previously. And finally, this is new. We're investing quite a lot in Slack. We're all familiar with Slack, I assume. So Slack is a different channel. It can be used for customers, but it can also use for swarming. Multiple agents will provide a question to Slack channel and -- provide an answer, sorry. So same technology here will show answers when needed, okay? And finally, if you really want to go as early as possible, you do what we call issue avoidance. So this is Xero. Louis mentioned Xero. We are embedded in the Xero app for millions of users each and every day. So when you enter a Xero app here, this is what you see, right? Dashboard is about your company. You're looking into your contacts and you have a question. So the question mark here in the top right, this is powered by Coveo. Look at the recommendation. Of course, there's a search box, but look at the recommendations tied to what you're doing and where you are in the application. If you go into invoices, recommendations are obviously different, okay? So that's a way to do issue avoidance you're in Xero, you don't need to log a case. We want you to find your problem before even asking question or before searching. But of course, you can search and it will be contextual, right? So we're working at getting even earlier in that journey, we call that issue anticipation. And down the road, we are also experimenting with field service enablement. So finally, from a platform investment perspective, we care about scalability, we care about reliability, securing and compliance and global presence. All of our customers are running on same cloud. We release more or less 1,500 times a month in a seamless fashion. We monthly, more or less, 4 billion index updates, 25 billion events and billions of searches. So this is what we do each and every month. We have a U.S. presence. We have a HIPAA cloud for the health care sector. We have a European cloud for data residency. We have a cloud also in Australia. And now we are opening Canadian Cloud in January. So all of this allows us to innovate faster to also have, I would say, pretty solid cost of operations from a cloud perspective. So with that, thank you for your time, and back to you, Louis.

All right. So let's talk about go-to-market. And -- so Sheila and I, I'll introduce Sheila in a minute, but we'll talk to you a little bit about how we continue to go-to-market and how we're expanding the go-to-market. So first of all, for us, it's all about optimizing the P&L for the company. We want to grow. We want to grow efficiently. And very simple, down-to-earth principles. We want to -- Coveo is a company that has a multitude of applications, and there are a lot of places where we can go. And for us, it's a matter of focus and really picking the 3 things that we should do and then drop in all the rest. And it really boils down to where can we get more revenue per customer over time. So given that we're a platform and that we can land and expand, which I'll talk about in a minute, how do we acquire customers that have the ability, have the profile to expand with us. Today, our largest customer is a $4 million year subscription. We want to see that number go to $10 million, and we want to have many more than one. And so in market selection, that matters. Number 2 is a more -- continuing to increase the efficiency of our customer acquisition model relative to the revenue that we bring in is obviously a key consideration. The cost of sales in the SaaS industry doesn't go down linearly again -- versus the revenue. It doesn't cost you 10x to sell a customer that is 10x larger that will give you $1 million over a customer that will give you $100,000. So we're not unlike any of your businesses, any other business. So this is really, really important is understanding exactly where we can find that optimal mix. Going, needless to say, where we excel, where we dominate is really the term, where -- when we engage in sales, we convert, we win essentially. And it has to be a binary sustainable differentiation in the market selection, so to increase our conversion rate, make our success -- our salespeople wildly successful and increase the revenue. And then finally, you look at the back end of it, customers that follow a certain pattern that really are a good fit for the platform that our product development guys, our R&D people love, our service people love and customers that are great to work with, like Bernard. And really so from a retention and that translates into continuing to increase the net expansion rate, obviously, and making sure that we're successful. So it's really about 6 key initiatives -- 5 key initiatives, sorry, that -- and it's really around continuing to push value, play where you bring a lot of value, just drop the rest and so on. If you're a software company today and you don't deal with Coveo, you're losing money every month. That's literally where we are in the customer service area. And we're soon going to be there, I'm confident, in commerce intelligence. If you're a retailer, and you don't deal with Coveo, I would love to -- when I'm online at Canadian Tire, I would love to put Coveo on top of that and get only 10% of the margin we can generate for them. We see that all day every day. And this is where we want to play. So fundamentally, the message of Coveo, first of all, if you go on our website, there's a platform message. So if you look on the left-hand side here, it's really about an AI platform that makes every experience delightful and profitable. But it's really also on the right-hand side about ROI, everything we do stems from ROI. We have a business value assessment team within Coveo, those are expert analysts, financial analysts. And when we work with a customer, we do not engage unless we understand the financial return, the projected financial return of what we do. We believe actually that in this economy, there is 1 buyer, the CFO, no matter who we sell to, there's always especially in this economy, a CFO at the end, who will say, "Wait a minute, how is that? They're very meticulous right now about how they spend. Wait a minute, is that bringing us revenue or is that cutting costs?" And we're designed for that. So you can see here, it's about boosting CSAT, it's about websites, it's about productivity measures, it's about obviously revenue margins, et cetera, you can visit our website. It's about profitizing every digital interaction. This is really the key message here at the center of the slide, and this is really the go-to-market message and the positioning of Coveo. To our knowledge, we're the only company in the space. Everyone in the space talks about bits and bytes and technology and all of that, we're about dollars, and we care about that. And so our lines of business are really aligned with that. So we run the company with 3 lines of business, and the company is divided in the form of a pod structure. So we have teams, cross-functional teams in each area. So commerce and service. So both in B2B, we're very strong in business-to-business. We're very strong in retail now also, and we've talked about self-service and contact centers. And then the platform play. And the way that we run the business is we invest new logo acquisition to land is done in commerce and service because this is where we can demonstrate very quickly hard ROI. We can show immediate ROI. We can walk to a large organization and say, "If you deal with us within 90 days, you're going to earn x millions of dollars, period." And then we expand. We have a platform team that once we do that successfully, and we gain a lot of trust with the customers and the metrics and et cetera, we can go to the CIO and expand and then cross-sell solutions and et cetera. So this is today how we run the railroad, and we think it's extremely well adapted to the current economy. And so to do that, we have packaged integrations to the most popular enterprise apps. In the service area, Salesforce dominates. There's no point dealing with anybody else. Salesforce owns 70% of that market within the enterprise on a global basis with a product offering named Service Cloud and the product offering named Experience Cloud, in particular. On the website area, it's really an Adobe world. Most large organizations deal with Adobe, and then we do a lot of work also with Salesforce on the platform. And in the commerce space, the dominant player is SAP. And we also work with Salesforce. Salesforce is definitely growing in the space, a little smaller in business-to-business. They acquired a company named CloudCraze a few years ago, and we work very well with CloudCraze. We make it much better, and they acquired a company named Demandware also in B2C retail. A little more high-end markets, but growing into larger enterprises. So it's a very great mix. SAP and Salesforce in the space don't compete that often sort of different market positioning. So we're very well covered from that perspective, and we invest aggressively in R&D to make sure that we are the absolute best solution for these customers, and we're far, far, far ahead from any competition in those ecosystem. We're also aligned with systems integrators. So those are the family doctors of these companies. So if you're Thomson Reuter, I'm just going to name companies that are customers, Pfizer, J&J, Philips, et cetera. You work with Accenture, you work with Deloitte Digital, you work with NTT data, you work with all those large systems integrators. And so they all have practice. If you type Accenture's Coveo on the web, you'll find the Accenture machine learning practice in the space design around Coveo. And so we spent a lot of time, and we have entire teams at Coveo focused on recruiting, enabling, supporting these systems integrators as well. And they're aligned by line of business as well. Smith is a smaller system integrator, but 100% focused on enterprise commerce. They're very, very specialized in the space. They're one of the best in the market. And so the -- hence why we deal with them et cetera. So these are the partners. So essentially, the go-to-market strategy is designed around supporting the entire cycle. So we have groups that, as I just described, support systems integrators doing a lot of educating -- education training enablement. The more we enable some of their developers at Accenture, their salespeople, their project leaders and their partners, the more we get referrals and we certify them. We -- obviously, you can hop on the web. If you're a developer, you can hop on the web, Coveo is an API-first headless low-code platform. So that's a bit technical for some of you. But essentially, it means that it's very easy for a developer to fire up Coveo. And it is definitely our strategy to make it easier, easier and easier to engage for a developer. Those developers are either found within big companies or within the systems integrators we deal with. So if you're a developer at Accenture in India, wherever in the world, you just log on the Coveo website and you can touch the platform right away and start building essentially. So we're creating that -- we've created that developer experience and allow the self-service trials. The goal here is not to go down market for us. The need for Coveo is with enterprises, but there are thousands of developers at Procter & Gamble, and those are the people we talk to. Our sales team is focused on selling to business units. So we have commerce black belts, service black belts, platform black belts, search, recommendation engine black belts calling on to heads of digital, heads of marketing, if it's websites, heads of customer service and CIOs. And then ultimately, our platform team -- once we're in a company our platform team is a very senior group that is tasked with establishing strategic relationships with CIOs. So essentially, the play here is we go to CIOs with a very senior team, and we talk to them about the Coveo platform and how to create a center of excellence within their company and leveraging the fact that we're already in their company and very successful with a number of use cases and so talk the CIO into signing large-scale enterprise agreements, and we think there's a lot of upside for the company in doing that. And so we're definitely investing in that area. So with that, I'd like to introduce Sheila, our CMO. I'll just say that Sheila came to us almost 2 years ago now. And when Sheila came to us, she said, "Louis, I don't know technology. I know yogurt, shampoo and [indiscernible] and the reason is Sheila ran marketing at L'Oreal in Canada. She ran marketing at Danone and she was the CMO at Cirque du Soleil but Sheila has joined us and has really transformed our global marketing and our global brand and it's with a lot of pride that I introduce you. Thank you.

Hello, everyone. A pleasure to be here with you to talk about marketing. So today, I'll talk about how we increase pipeline and not only in terms of quantity of pipeline, but in terms of quality of pipeline, so we can be more efficient. Now what we pass to the sales team because that's what we do in B2B, we create pipeline so that we can pass the baton to the sales team and they go and sell it. So how do we create more volume of pipeline and more quality of pipeline? So here are some metrics for calendar year 2022, so year-to-date calendar versus last year of how we improve marketing qualified leads in terms of volume, quality. So in terms of volume, we have definitely a lot more prospects interested in Coveo, plus 65% more leads. In terms of quality, one thing that we've done, it is not in here is that we created a lead scoring system. So when a lead comes in, we look at the quality of the [ lead ]. Is that an enterprise. We love enterprise. We mention it. We want enterprise. Is that an enterprise, what industry, what tech stack? So then we can know what the priority is for the sales team because we know that those customers we want to win them, and we know we can bring a lot of value to them. Then we are also obsessed by hot marketing qualified leads. What is that? Hot MQL is actually people asking for a meeting with us. So we created enough content, enough visibility so that they are interested at asking a meeting with us to book a meeting, get a demo, contact us. And I'll talk about this later, but those are gold leads. We want more of those. And we were able to increase it by 83% calendar year. Also Salesforce and SAP leads. We mentioned that before. We like those leads. We know we can be really successful with this integration, plus 140% of leads coming from Salesforce and SAP, and this will continue to grow in the future. And then expanding with our installed base, tons of opportunity within our own customers. So we want to attract people in other departments to come and be and look at Coveo, plus 107% here. So we're doing great things. What are we doing that is creating this and what are we doing that will continue to bring growth to Coveo from a marketing standpoint? Four main things, and I'll go into each of them. The first one is continuously optimize digital marketing and maximize the return of in-person events. Let me explain this a little bit. From 2005 to 2020, Coveo pipeline was mainly coming from in-person events, trade shows. And then COVID happened and the team asked to shift urgently to digital marketing because there was no such things such as trade shows and in-person events. So where do we find pipeline online. So from 2020 to 2021, the marketing team built a foundation of a strong digital marketing machine. And I'm pretty proud of where we are today in 2022 with our digital marketing. It's performing well, very well. And on top of that, we can bring -- we're bringing in-person events. So we have the 2 best worlds coming together, digital marketing plus in-person events. This year, in Q2, 35% of our leads were coming from in-person events. And in Q4, it's going to be even higher. So in-person events work, and now we're adding this to what we were doing in the last 2 years. On digital marketing front, you know that there's a lot of touch points. And it's never finished, the optimization we can do with digital marketing. There's always things we can try, tests, testing new messaging, testing new channels, testing new approach, new visual, what is -- what people are going to click on. So we have a full team doing this. We're working with the expert at Google, at LinkedIn to improve our marketing digital machine, and we're at a very good place, but tons of great opportunity in front of us. Then hot marketing qualified lead, like I mentioned before. Why are we so obsessed about this? My team would tell you that they look at their hot MQL every morning when they wake up in the morning because they have 10 more chance to get into a meeting than a normal leads. It's people asking for a meeting, they want to meet with us and Louis mentioned it, where we had the table, when we are in the meetings, we win. So we love them, and we were able to grow really fast on the marketing qualified leads, plus 83%. It's 19% of our leads today. Last year, actually 21% this year, and we want to be at 30% next year. And we're doing tons of things that you can see here to increase people being interested in our brand. And it comes from awareness, just knowing we exist and then understanding what we do, understanding the value we can bring to them. And then giving them an easy way to meet with us by adding tons of click-through rates that call to action, I mean, on our [indiscernible] to increase our click-through rate, so that they meet with us. So many things that you can see here with kind of book a meeting, with meet with us, a 15-minute meeting with us. And then we know that if they meet, we can win them. Next one is maximize partnerships. With SAP and Salesforce majorly, but we have others, and we showed you all the partners we're working with. But those 2 were Summit partner with Salesforce and we're spotlight partners with SAP. And this comes with a lot of great advantages to those partnerships. The first part is that we target their installed base. We actually target their customers, and we tell them how our integration can actually superpower what they're doing today. How we can bring their experience to the next level right into SAP, right into Salesforce. They don't have to change their tech stack. We're just coming in, fitting right in and boosting all their KPIs. Then we maximize our partnership through co-marketing and join go-to-market. When we are Summit partners, when we are Spotlight partners, it's come with a team of people at SAP and at Salesforce helping us to create leads, helping us to generate more customers. I have a team of 4 people at Salesforce working with us on a weekly basis to actually accelerate some leads and create some events and create some content. We're participating in all of those events like [ SAP CX ], Dreamforce, Salesforce [indiscernible] were there. We're talking to their customers and Salesforce and SAP is helping us just telling the added value that Coveo can bring. And last, but not least, is deal acceleration. When one of our deal lead is stuck it's not converting into a meeting or it's just not -- we're not able to win it, then sometimes they jump in and they help us. SAP, SalesForce of what we mentioned like OSF and Smith and all other partners we can call them, have discussion and they can help us accelerate some deals. So partnership is key in everything we're doing in marketing. And the fourth thing we're doing to accelerate pipeline and improve the quality of pipeline is account-based marketing. And I always use this fishing metaphor. And this is the only thing that I know about fishing. Everything is on this slide. I know nothing else about fishing. So don't ask me a question about fishing. But net fishing is what is the closest thing to traditional B2B marketing. You create a big campaign, it's like a big net that you send in the market, and we try to attract as many fish as possible. And then during the sales process, you disqualify the smaller fish, you disqualify the fish that you don't like that much. And then you qualify the one that you really like and then you transform them into our customers. Spear fishing is closer to ABM. So ABM, it's about the sales team and marketing team working closely together to identify customers, we want to win. The customer that we know we can be really successful with. We identify them and then we go at them. We can go at them from a one-to-one perspective. So choosing 1 customer. This one, we know they're in market. We know they're looking for something for us -- like us. And then we go with the VIP plan just for them. That's the 1 too few ABM when we create a small cluster of customer with the same pain point, the same industry, the same tech stack and then we can adapt content and we go at them as a cluster of customers. And then there's the one too many, a bigger group of customers that are look-alike and we go at them with the sales team altogether to go and win those customers proactively. So it's a bit different than what we do today, but there's a lot of potential. So we started this last year doing a lot of ABM. We started slowly. In Q3, we accelerated this. We actually hired 2 ABM expert at Coveo. And we want to be the best in class in ABM in the SaaS business. And Q4, we have many projects, 20 projects of ABM, touching many accounts in all our line of business in all the 3 ABM approaches. So this should have amazing results. So we will continue to optimize our digital marketing. We will go big and bold in events and in-person events. We will be -- continue to be obsessed with getting hot MQLs, maximize all our partnerships, work with them so we can -- it could be a win-win situation for them and for their customers and then master account-based marketing is -- and there's much more to that, of course, what we do to you. But those are the 4 things that really move the needle. So that was for marketing. Now let's move into the other part of my job, which I'm really proud of, and it's our ESG and 1% pledge. So I'll take a little bit of time with you to talk to you about what happened since we went IPO last year and when we pledge 1%, 1% of our time, 1% of our product, 1% our equity and 1% of our profit down the road. So first, we actually have to decide what we wanted to do with the time and that money and that products that we are offering to foundation. And we quickly got to this mission. We were all aligned about the fact that we wanted to democratize knowledge and education, that knowledge is the ultimate equalizer, that education is the key to empower people to do more on their own. And we decided to invest our 1% of time, equity and product into helping foundations, nonprofit organizations that are actually making accessible -- giving it access to young people, mainly 6 to 18 years old are our focused in vulnerable community to education and knowledge. So what does it mean concretely? For our 1% equity, we already give 2 cycles of the nation. So we had the 6 months where -- after IPO where we were not allowed to do anything, but we started in Q2. So we gave the first donation in July. And then Q3, we gave a donation in October for a total of $184,000 in Canada and around $75,000 in U.S. that will be given for Q4. So the timing is a bit different for the U.S. donation. We're working with Benevity as a platform for our equity donation. So we actually upon IPO, we transfer them 1% of our share and they liquidate it every quarter for us, the portion for the next 10 years, and we tell them where to give the money, which shows many foundations. You see them on the slide, the 4 more important ones are Actua. Actua is an amazing Canadian foundation supporting STEM education in vulnerable communities. There's Girlstart, which is really close to Actua education as well, focusing on girls in U.S. [indiscernible] it's a Quebec Foundation that are actually using sports to get the kids. So coaching coach to be more than a sports coach, to be a live coach, to help kids have an inspiring model in front of them. It's amazing what they do, and I'm super proud of the associated with them. And then Love. Love is about emotional intelligence, about how to build your confidence as a kid when you may not have the great role models in front of you and many other on this. So again, that donation that will happen every quarter for the next 10 years, and we'll build stronger and stronger partnership with [ Dell's ] Foundation and add more in the future as well. For the 1% product, we gave our first product donation with Alloprof. This should be live at the end of November. It's another amazing platform. They actually help students and parents for homework. So imagine if you're a parent and you cannot help your kids to do their homework. At least you have a resource with tons of amazing content and great tools to help kids do what they have to do to succeed at school. So this is great. We're really happy to see our Coveo technology behind this great platform. So it should actually be live end of November, and we'll announce the results and to go-live through a press release. And next product donation should go with our key partner that I mentioned before, Actua, Love, [indiscernible] Girlstart and [indiscernible]. We want to work with them to offer them our technology. The next one is 1% of time. So we are giving 2 days at Coveo to all our employees for volunteering and then we inspire them with different option of volunteering, so tons of things are happening there, more to come because we're building volunteering opportunities with our key partners that you see on the slide. And you see examples here of things that we've done in October-November in different type of foundations. But then ESG is more than the 1% pledge. We also have an environmental play. We have our people well-being, so making sure that we are a good employer at Coveo that it's great to work at Coveo, and then embracing inclusion and diversity. On the environmental front, I won't go into all the details of this, but the thing that could interest you is the fact that we're going to officially launch our carbon footprint evaluation. So we're working to find the best supplier right now to do that in the first part of next year and then, of course, taking this and build our plan to decrease it and improve it in the future. Then well-being. A lot of things have been done here to make sure our employee feels good at work or at home, working from home, a lot of things about mental health that we've put in place to support our employees and physical help as well with sports and gyms that we sponsor and also activities that are happening at the office. Inclusions and diversity, 2 projects that I'm really happy with is the launch of our professional women network at Coveo, so many initiatives to really regroup women at Coveo, making sure they have a network that they can rely on. And we have one thing that I really like is the inspiring women series when we invite women from other companies to talk to our women and say how it is in other company? How can you succeed in your role in this man world? How do you succeed? And how do you get a place at the table, a spot at the table? And the other thing that I'm really interested in is the pilot project we're doing with [indiscernible] internship. So we're going to have 2 interns on the autism spectrum will actually come and work at Coveo. It's a test we're doing. We're pretty convinced that this is going to work really well. We're one of the best environment to work for those type of people. And we think we can actually learn could be a really win-win situation for us. So we have our 2 first intern coming in Q1 next year, and we want to scale this project in the future. And there's also [indiscernible]. We're giving to [indiscernible] every year for the last 10 years. We just launched a campaign on November 10. It's going to finish on November 29. And we -- our objective is to raise $400,000 to give to [indiscernible]. And last, but not least, we work with the Pledge 1% organization that actually work with all companies that are doing the Pledge 1% and they invited us to join them at the NASDAQ bell ringing event on November 29, as -- and they mentioned actually that they invited us because we're a next generation of corporate leaders in the social impact space, and we're really proud of it. They actually invited us also to present what we're doing at Coveo to inspire other companies to do the same. That's it for me. Thank you very much. And I think it's time for the break, right?

All right. It's the moment you've been waiting for. It's a bit of a 15-minute break. We'll start again at 10:55. And again, we're going to kick off the second half with our excellent customer panel. So be sure to be there on time for that. Thank you so much. [Break]

Okay. I think we can close the doors and we're ready to go. All right. So with us, we have Bernard Slowey, VP, Digital Customer Success at Salesforce. Bernard, good morning. Thanks for being with us. And Darren Taylor, who's SVP, Marketing and Digital for FleetPride. So welcome, gentlemen, and thank you so much for, first of all, being 2 amazing partners of us and customers and for your presence today sharing your story. So I'll start with you, Darren. Maybe you can talk a little bit about yourself and about your background and describe FleetPride.

Sure. Well, thanks again for having me. My name is Darren Taylor. I've been doing digital transformation for -- since the late '90s, mainly in distribution at companies like Grainger, if you're familiar with them, or Sonepar, very large company across the globe, and more recently at FleetPride. FleetPride is the largest independent heavy-duty distributor and service provider. So we keep trucks on the road, right, by being more reliable, and we keep them operating faster and more reliably.

Excellent. And we'll hear more about your digital transformation. So on Bernard, I think pretty much everybody knows Salesforce, I think so, but if you can talk specifically about your background and your role at Salesforce.

Sure. Sure. Thank you, and for having me here today. I'm really happy to be here. Hi, everybody. I'm about 18 months at Salesforce. I lead our digital customer success organization. I'll talk about what that is kind of through some of the questions. Before that, I spent a year at GitHub. I led digital customer success at GitHub, and before that, 15 years at Microsoft. I was the worldwide leader for Windows support at Microsoft. So always in support, in success, managed a lot of agents, managed a lot of self-help experiences. And today, at Salesforce, I manage all of our digital experiences. So our portals, our video channel strategy help. All of that kind of sits under me and my team.

Great. So thank you for that. And Darren, I'll start with you, and same question to Bernard afterwards. Talk to us about why customers engage with FleetPride and the kind of experience that you want to create for them, how important that is. Just give us some context here.

Okay. So the simplest way to think about it is we sell truck parts and repair them. Okay. In the simplest terms, like heavy-duty huge trucks, right, all across the U.S. And so when a truck's down, right, they need -- they don't know what they're going to need, but they need it right now in like Virginia or in New York or wherever, right? And so why they come to FleetPride is that they need expertise of what is this thing and where is it, and then reliability and then solutions to manage their business and manage their fleets and people. And so that's what we focus and hone in on. And from a digital transformation standpoint that's literally where we focus, right? So if you think about it and how it relates to Coveo, it's pretty obvious, right, is "what is this," and, "I need it right now." So we sell hundreds and hundreds of thousands of parts, right? And they're in stock across branches and distribution centers and sometimes even on customers' premises, right? So we have products all over the place.

Give us a sense of the scale, just so everyone in the room understands the scale at which you operate at FleetPride.

Okay. So we have about 4,000 employees, right? We have hundreds of branches and service centers across the country in the U.S., and we sell about 800,000 products online, soon to be much more than that. And we'll talk a little bit more about that in the search experience.

Yes, that's great. So it's high volume, essentially, all day every day. Bernard, give us a sense of magnitude at Salesforce and some of the key reasons customers -- you want customers to choose Salesforce and how do you want to serve them. So give us a sense of scale.

Yes. So just to give you an idea of scale. So if we talk about our help portal, which is where customers go -- I'll show an image of it later -- we're probably going to get about 60 million unique visitors at that portal by the end of this year, and we were probably at about 50 million a couple of years ago. So we're seeing huge growth on our portal. Customers come to our portal. And we think about it in 3 reasons. We have 3 journeys that customers come to us. It's education. "I want to learn more about your product." Issue resolution. "I have a problem and I need you to fix it." And then the first journey is onboarding. "I'm new to the product that I want to come and learn." And you mentioned something earlier on. As our products grow, we can't think about all of them scenarios being handled by humans, right? And most of the time, people don't want to engage with humans. You mentioned earlier on. Nobody wakes up in the morning and says, "I want to contact support," right? They want to go to your portal. They want to self-serve, whether that's a video, whether that's a knowledge article, a community post, and Coveo powers that for us. We have a search first experience on our help portal that's powered by Coveo. Our agent console experience is powered by Coveo, all in the name of giving the customer the right content at the right time to solve their issue. That's kind of how we think about it.

How you think about it. So going back to FleetPride, when you think about the e-commerce experience, what were some of your goals, if you look at the before and after, now that we're deploying Coveo and AI and et cetera? And then give us a sense of that journey, and maybe some of the future journey.

Sure. Well, first and foremost, was as the leader in the space, we need to become the digital leader. And when we sell availability and reliability, we need to be the best at search and become the #1 search destination. And we've done that, right? Even our competitors are using our website to look up stuff for other people. And so that's number 1. Number 2 is adoption with customers in the field, and 3 is to understand the customers' experience or really the customers' B2B, the customers' process and then provide solutions, digital solutions, to them. Digital solutions could be like rogue spending or centralized management and stuff like that.

And just building on that, we're all familiar with the immense supply chain pressures that a company like yourself has. So how does automated AI, automated recommendations in search help alleviate some of these challenges as an example?

That's a very good question. I actually get that question a lot. It helps directly. I mean it literally of "what is this?" And then, "what are my options? If you're out of stock here, what other products would work with this? And where are they?" And you need product data, you need a great search engine and AI in order to do that.

If you think about it, managing 800 SKUs and hundreds of thousands of drivers and trucks in multiple branches and so on, how do you do that manually? I know this is a loaded question, and this is -- but how do you do that manually.

You don't, right? So just to give an order of magnitude, this year, we will have added 10x the number of SKUs onto our website, okay? And so it's approaching 7 digits. And there are very -- some of them are highly specialized parts, like a clutch for a 10-year-old truck, right, and this specific engine. They're very specific. But there's patterns to it as you're pointing out, right? And the second thing is that all of us expect, because we use technology and websites and all this stuff in our daily lives, that even though it's B2B, they expect it to be really simple, like B2C, right? Hence -- but you got to follow the rules of the company that they work for, right? But it has to be simple. And so you all understand that, and that's really -- one of the reasons why we partnered, is to understand the business outcomes, both from the customer and from us, and understand that it needs to be simple, and we're going to use the search engine to do digital marketing, too, but it's also a business tool for our customers, right? We become part of their process. And you have to be reliable and fast, et cetera, and relevant to do that, or they'll kick you out in 2 seconds.

So can you comment on some of the metrics that you're monitoring that we've been able to achieve so far, and talk about the importance of that competitively? Because your customers have alternatives for these parts and so on, so how are we moving the needle from the metrics? What are you tracking?

One of the things as it relates to Coveo, your team and my team worked on this together, is search rank, right, which is when you type in something, what do people usually click on, on average? Is it like the 10th thing on the page or the fifth thing, right? And the lower the number, the better. And we've improved that dramatically in the last 12 months.

Right. And when they -- for those of you in the audience, when you increase or when you reduce that number, when you become really, really good at showing the right product on the first result, obviously that translates into much more customer satisfaction, much more conversion, much more sales.

That's right. So our conversion rates more than doubled, which translates to dollars, of course. And so is our -- we do specific customer satisfaction every quarter on our e-commerce solutions, and we have raised dramatically [ into that ].

Yes. So conversion rates doubled. We'll remember that. That's really good. Bernard, you make a difference at Salesforce between customer support and customer success. So just to frame the conversation, could you start by explaining this?

We used to actually treat them -- they were separate organizations in our company, and most companies have support organizations and they kind of have success managers to help drive adoption. We've actually brought them organizations together now. We think about it all as one thing. Customer success, whether a customer has a problem, whether they're trying to learn to do something, whether they want to adopt. It's all about driving success of the customer. That's what we're here for.

Right. And when you think about the evolution of that customer journey, and we now have -- well, maybe you could describe the number of AI-powered experiences that we've been working on together at Salesforce with Coveo, starting in the product and then the community and et cetera. Yes, so I'll let you...

Yes. I'll start with our portal because we've actually been on a journey ourselves. About 18 months ago, we relaunched our portal using Experience Cloud. We were on a kind of custom IT stack, and with that, we enabled Coveo to be that kind of search first experience. And we saw incredible results with our new portal in Coveo. So we measure something that we call self-help success, which is customer came to the portal, they consumed a piece of content. It could be a video, it could be an article, and they don't go on and create a case. And right now, our self-help success is up 97% for a portal. So if you think about the amount of customers I said earlier on that are coming to that portal, 60 million unique visitors, not even returning. It's a huge number for us, and we were at the low 80s. So you think about the growth that we've had there. But we haven't stopped there with Coveo. When the customer wants to submit a case, we've simplified the process for them to submit a case. We have a lot of products. It's a complex ecosystem. Sometimes it's confusing for customers, like what do I need to give them? What do they have? And so we used to have a horrible case submission form, and you probably all experienced this with certain companies, where it was scroll down, scroll down, select all these options, give us all this information. And we simplified it now to like a Google-type experience where they just need to tell us their problem, and we're using Coveo in the back end and AI classification model with Coveo that's able to recognize matching intents and say, "Okay, the customer has given us this description. Here's what the problem is. Here's some content that's relevant for that." And then we route off that to the right support engineer on the back end. So that's been something new we've been working on with Coveo. The other piece is we recently launched Einstein chatbot within our case submission form and sometimes, I think where chatbots fail terribly is if it doesn't have the right dialogue for that intent, and you've probably all experienced this on different websites you've gone to. It just kind of fails. And so what we have is Coveo. If we don't recognize a dialogue, it falls back to Coveo. So Coveo is the search engine within the Einstein bot. So we can still give them articles, et cetera, within the bot, if the bot is not able to solve. And that's kind of just 3 of the customer-facing experiences that I would think of right now.

So when you think about -- you mentioned we like numbers, right? And it's really important to understand the economics of this. When you think about 60 million visitors, unique visitors, right, is that what you said, a year? And the ability, in fact, to help them help themselves and help them self-serve and et cetera, what would be the alternative? And again, a bit of a loaded question, but how would you do that without technology?

I honestly don't know if we could have enough bums in seats to do it without technology. We have a huge support engineer footprint. We've got credible support engineers. But we still manage a lot of volumes through them today, even though 97% of customers are being self-served. So I don't know how we'd do it without technology. I don't know if it will be possible without what we have with you guys on our portal.

Do you -- is it fair to say that as Salesforce grew, and we all know that Salesforce is such a high-growth organization and an incredible growth story, that the -- that support infrastructure of those agents, there's quite a bit of complexity in hiring them, training them, getting them proficient enough so that they can truly help customers who often are pretty competent and then scale that. As Salesforce grew, this group didn't grow quite as fast.

Yes. Yes. It's -- obviously, things are changing a little bit in the macro environment right now, but it has been hard for us to hire support engineers that have the quality we need for Salesforce. As you mentioned, our products are quite technical. A lot of customers who we deal with would be admins, et cetera, very technical as well. So it takes us time to ramp. We need find the right profile to ramp that person to be at the level we need them to be to be a support engineer. So that's difficult for us. It's difficult to find the right people. But what I will say is, you showed it earlier on, is that in-console experience with Coveo, that helps our support engineers reach the levels they need to reach, right? Because it's giving them content just like we want to a customer that's helping them do their jobs with the customer.

Yes. And so it's fair to say that you don't want a Black Belt support engineer that's so heavily trained and knowledgeable, et cetera, to help a customer change their password.

Exactly. Exactly.

Or do simple things that could be done self-service and so on. And then in turn, junior support people, through with technology, can actually gain more proficiency essentially to solve issues.

Exactly. And if you talk to a support engineer, nothing frustrates them more than dealing with the simple scenarios over and over. Like they're smart people. They want to handle the complex scenarios. They want to try and troubleshoot [ its swarm ], spend time with other support engineers to get to it. So you need to get that other volume out of the system. And that's what self-service is all about, is you need to get it out of the system so they can handle the more complex scenarios.

And maybe one last question for you is when you think about Salesforce at a high level as a company, there's a product that you sell, the power of the Salesforce platform, but there is competition also out there. What -- on a relative scale, how important to you, for the growth of your company, is the experience? Is it about the product? Or is it about the experience?

I think for every company right now, if you're not thinking about the experience front and center, the customer and the sentiment experience with our customer, you're going to fail. And we care incredibly about the experience of our customers. Even that example of case submission, like that doesn't seem like a big thing, right? But we reduced the clicks the customer has to go through by 85% to submit a case. And that's what we mean about caring about the experiences. We're getting into the minute detail of, "How many times do they need to click on something in order to do something?" And so Salesforce, we're razor-focused on making sure the customer is at the center, and we're always thinking about that experience. And all the data is out there. Gartner, Forrester. Customers will leave you now based on that experience. They will leave you now based on that experience.

That's what they're buying. And Darren, perhaps you can build on that. If I operate a fleet of trucks or I'm an independent truck driver and I'm trying to keep my truck on the road, and so when I have multiple alternatives on a relative scale, we're not just buying a part from you. How important is that experience for them to keep -- to retain customers? And potentially, does that give you price power, in fact, too?

It's absolutely critical, and it's reliability, right? You have to do it over and over and over and over again, right, to your point. It's not just a one time. right? You're providing not only a transactional effectiveness or reliability for this one part. You're also doing that thousands of times, because some of them are very large fleets. They have trucks all over the place, right? And they're managing a ton. And as soon as a truck's down, they're in a predicament and losing money, right? Thousands of dollars a day. What do they do? And so that type of problem solving and doing -- it's all about the customer experience and doing that reliably.

And so in closing, to both of you, I'm going to ask the same question. What's next for us? What, working together, how can we push that technology further? And what can we expect?

Well, one of those is continuing to push on the relevancy and AI. I mean, that's really what it's all about, right? As we have 10x the amount of SKUs and rolling this out to massive fleets and small mom-and-pops at the same time, the amount of users we have is growing exponentially because it's a slower industry to adopt. So we are in a mass, mass change. And as the leader in that space, we have to push the envelope from the customer inward and do that together, right? So focusing on relevance logic, and not only do I need this part, to your point is, I need these -- I need to complete the job. These 4 things also have to go through that. It's not just buy a sweater and some shoes, you actually need this stuff to prepare the truck, right? It's highly, highly, important. And so an AI engine that keeps tuning it, and then we believe that, [ next ], into all our digital marketing efforts and integrating into our customer systems.

And Bernard, same question. What's the future? What will this look like 3 years from now?

Yes. You mentioned some a little bit earlier. We're starting to do a lot more in-app experiences, so we don't want the person to have to start on a portal and search and come to us. So partnering again with Coveo, and when they're in the product and they're trying to do something in the product, we have data of what they're trying to do. So using Coveo's model to understand, "This is what they're trying to do. This is the type of content that can solve for that," and giving them that content experience within the app. So they never have to leave Salesforce. They stay in Salesforce, get what they need and then they're able to go and achieve their business outcome. That's really important to us. The other thing I'd say where we're partnering with you guys as well is we're trying to expand language capabilities. So as we're starting to launch our bot, it's English only right now. We want to go to a lot more markets, and so we're working with you on the models to make sure that it works well. And some of these like Japanese is a very complex language, et cetera. So starting to work through different languages with Coveo as we want to go beyond English.

Go global.

Yes.

All right. Well, thanks to both of you for being here with us and sharing your stories and the success that we have together, and certainly, we hope to continue. Thank you.

Awesome. Thanks for being a great partner.

Good morning. Pleasure to be with you and to talk about our financials. My name is Jean Lavigueur. I'm Chief Financial Officer of Coveo. So let's start by reviewing our key metrics and KPIs. So we reported for the September quarter revenues of $27.9 million. Those are U.S. dollars. Total revenue. That was up 43% year over year. Of that revenue, 91% was comprised of SaaS subscription revenue. So -- and that was up 47% year-over-year on a -- looking at organic revenue only though, that 47% was 30%. So we've been public for a year now. Reporting for the last 4 quarters, we're able to meet, reaffirm or even raise guidance both on the top line and on the bottom line. So when you look at our revenues, 91% from SaaS subscription revenue. The difference is from professional services revenue, which is about 8% of revenue. There's only 1% left from old legacy customers that were on-prem, that now, for the most part, with the exception of that 1%, has all moved to the cloud. So that transition from on-prem to cloud at Coveo is done. When you look at other KPIs, cRPO, up at 51%. As you know, cRPO is a good metric when you look at billings. So we look at cRPO. So I think always very comforting to see that as -- of course, revenue looks more backwards. Certainly, cRPO gives you a snapshot of billings and bookings that we've done as of September 30. So reporting at 51%. Net expansion rate at 111%. Over 600 customers and over 700 employees. So let's focus now. Let's double-click on SaaS subscription revenue. So incredibly proud here to show the predictability of that SaaS subscription revenue, right? So if you look at our MD&A, last 8 quarters, you will see revenue going up each and every quarter. So how are we able to deliver, be so consistent with that SaaS subscription revenue while we've had COVID, recession, et cetera? So first of all, it starts with signing customers -- signing long-term agreements with customers. So most of our customers signed for 3 years. Furthermore, when we sign with them, it's always invoiced annually in advanced. And for those customers that, actually, they always commit with regard to either number of users or number of queries. So when you think of our use cases, everything that's customer-facing, we sell based on the number of queries; everything that's employee-facing is based on number of users. And those are committed for the entire term of the typical 3-year agreement. So it makes for a very predictable revenue stream. Of course, customers from time to time will exceed those number of queries. What happens then is that we work with them typically to increase their commitment for the remainder of the term of the contract. As a reminder, last October 2021, we acquired Qubit. Hence, why we had the delta where revenue grew 47% and 30% organically. So this will be the -- the September quarter will be the last quarter where we had the full contribution of Qubit. Of course, next quarter will be solely -- organically will be a very small portion of Qubit revenue. Turning over to another key metric is cRPO, current remaining performance obligations. So as I said, so when you look at SaaS subscription revenue, these are all revenue that's recognized ratably. cRPO really takes a snapshot, as of September 30, of the remaining performance obligations over the coming 12 months, standing at $88.7 million, up 51%. So if you think about really our business model, if you look at our balance sheet, you'll see deferred revenue. Deferred revenue sits at $53 million. So as I said, customers signed 3 years, but we invoice annually in advance. That's what's on the balance sheet, right? That's what's contracted and invoiced. That's $53 million. Then the next layer is cRPO. Everything that's contracted, but as we get to the second and third anniversary of the contract, then cRPO includes those renewal years, not invoiced yet, but included in cRPO. That's the next level. That's $88.7 million. Third layer is ARR. So ARR looks at the entire -- it looks at revenue, regardless if it will be -- it assumes that it will get renewed over the coming year. So last quarter, we reported $25.5 million of SaaS subscription revenue. So ARR crossed over $100 million, of course. And then, of course, you have total RPO. So RPO over all the years, everything that's been contracted, and that's $160 million. So it's not only a very predictable revenue model, but it also provides high visibility as well in the future. Moving over to net expansion rate, right? So net expansion rate, 2 components here. The first component are, of course, GRR, gross retention rate. Those are the renewals. And of course, to get from GRR to net expansion rate, NER, then you add on top upsells and cross-sells. So if we focus, to start with, on GRR. So when you consider that only, by the way, only 1/3 of ARR comes up for renewal every year, right? We're really proud of, again, being in the, call it, mid-90% GRR rate. So again, very high rate, very strategic application for our customers that come 3 years. Of course, very high renewal rate with our customers. Of course, when you look at our customer success, our tech support, we don't claim to be as good as Bernard's organization, but we certainly believe that we have also a world-class organization with regards to those 2 areas. Secondly is net expansion rate. So when you add upsells and cross-sells, that's how you get to the 111%, 112% that we've experienced over the past 6 quarters. So how do we get to that? So first of all, about 40% of those are upsells, right? So when you look at upsells versus cross-sells, it's 40-60 mix, right? So upsells, 40%. So how does that work? As I mentioned, typically queries for customer-facing types of use cases, and agents for employee-facing. They're committed for the entire term, right? So customers may start with a division, with a geo, and then will expand during the term, and we'll contract for the remainder of the contract, right? So that is how we get to upsells. What's really exciting, though, is cross-sells. Laurent showed you the breadth of the platform, right? So as much as we want to land with -- we talked about commerce, we talked about service, it's really expanding, and we've dedicated teams now to ensure that customers, once they've adopted that initial use case, that then they cross-sell, right? So let me give you a couple of examples. One of the top 3 TV manufacturers in the world started with us, but started with commerce. We want to make sure that on the B2B front, they were able to ensure that they had an amazing digital journey for their customers. But it was already planned that once they went live, once they were live, they were happy with us, then and only then, they'd give us the customer service. Because, of course, all those customers buying those TVs, whenever they wanted to upgrade the firmware, the software, where would they go? Same experience. And of course, they wanted that one platform to capture all of those user interactions so that you can go back and sell back to those customers, maybe accessories for that TV, right? Because you know them across the journey. Let me give you another example of a cross-sell, which we reported a couple earnings call ago. One of the largest software companies in the world, we were in one of their divisions in customer service only, right? Once we were successful with them, they were -- of course, they were our champions internally. From a global perspective, the global team looked at all the success that they had in that division and went global with it. So now all divisions within that company that has 400,000 customers, large enterprise customers, all of them will be using Coveo across our customer service and as well as in products. So we cross-sell -- so we upsold with regards to number of agents, of course, queries in the customer service center, but also in the product for all of those 400,000 customers. So again, amazing cross-sells. And certainly now, Louis has promoted one of our sales executives to focus on this day in, day out. We'll talk a little bit more about that white space actually later. ARR. So when you look at the mix, we talked about how commerce is super exciting. You see those 4 rows up there. When you look at the growth rate, super excited, of course, this is the product, the line of business, the product line that we've launched only 4 years ago, and certainly very excited with the growth on that line of business. Service, though, we've launched it over 10 years ago. It's a very -- it's a mature one. So it's still growing very fast. You've seen all the maturity that Laurent showed. So very excited, of course, with service. Websites is also a good line of business where typical average revenue per customer here is lower than the other ones, however, it's easy to buy, easy to deploy. We got some good volume from that line of business. And certainly, we can expand from that or cross-sell, of course. And finally, workplace. Workplace typically, in those types of environments with a softer ROI, not growing as fast, but it's still a nice cross-sell. Once we've landed with one of those kind of hard ROI type of use cases in commerce and service that we talked about, certainly, workplace can be a nice cross-sell. When you look at geos, we did report that we did have a headwind with regards to currency with our top line by about 3%. It impacted us negatively on the top line. So the reason for that is that 80% of our revenues is denominated in U.S. dollars. So that 20% remaining across Canada, Europe and rest of the world, that's the 20% that's causing that 3% variation and the headwind with regards to the top line. However, when you come down -- when it comes to expenses, because we're over-indexed in Canada with regards to R&D, most of Laurent's teams in Canada, that becomes a tailwind for us and is helping us with regards to the adjusted operating loss, and we'll talk about it in a second. Okay. So let's talk a little bit about growth, but especially talk about efficiency here. So as I said, really proud of the -- of our ability to meet, exceed our own guidance consensus with regards to the top line. What about the bottom line though? So we went from, a year ago, 26% negative adjusted operating loss to 17%, so a year later, right? So an improvement of 9%. So clearly, we've been able to keep the acceleration -- to keep the growth rate on the top line while being -- showing efficiency with our operating leverage across the business. So we'll double-click on each of those items as to how we've been able to do that, but certainly, I think we've adapted to the market. We have a very strong balance sheet. We've got over USD 200 million with no debt on the balance sheet. We have plenty of cash. We need $30 million to get to cash flow breakeven in 2 years. So with that, so -- but still, regardless, I think the market demands that we adapt and that we're showing more balanced growth. Clearly, as you can tell, we've adapted our approach, hence, delivering minus 17%. Keep in mind, though, that for the September quarter, having a lot of R&D folks in Canada, there's a lot of vacation that did create -- that did help us for about 2%, and as well, FX helped us for about 2% as well there. So when we look at cohorts, right? So when we look at customer cohorts, we've looked at the data for the last 7 years. This is data that we've taken from the prospectus that we've shown you a year ago. We've looked at the data, and it's pretty -- it hasn't changed much, really. So really proud to say that when you look at a dollar that we -- where we land, 5 years later, we'll actually double. Now we've talked about the net expansion rate of 110% right? Actually, the first couple of years, it's actually faster than that. Why is that? Well, most customers signed for 3 years as I reported. So there's very little churn, and hence, why you see that dollar becoming $1.02 and then $1.04 in years after the first and second year. Then, of course, comes renewal. That's when we see some churn. However, we're still able to cross-sell and upsell, as I described earlier, to get all the way to 2x after 5 years with those cohorts. So we talked a little bit about cross-sells and upsells. So I wanted to give you a little bit of an understanding of what is the opportunity here, right? And as I mentioned, Louis appointed an executive to focus specifically on that, right? So when you look at our customers, about 40% of our customers, 250 of them, are giving us -- right now, they're paying between $100,000 and $1 million a year, right? But for the vast majority, almost half of those customers are only either in 1 line of business, call it service, or even within just 1 use case within line of business. That line of business, say they're only with their customer committee online. That's where they've started with us, right? So can we convert a portion of those 250 customers already paying us between $100,000 plus a year into -- look at those, we've got over 10 customers that are paying us over $1 million a year. They have adopted us within all 3 or sometimes all 4 lines of businesses, right? So if we can -- so if we convert only 25% of those 250 customers, put them on the right-hand side and get them over $1 million with those cross-sells and upsells, that's a $40 million to $50 million opportunity that is right in front of us if we do a good job of, again, creating those centers of excellence. That is how they've done this, how we've done this, right? So making sure that those customers -- actually, whenever there's an opportunity to personalize, for search, for recommendations, merchandising. Whenever there's an opportunity, there's the center of excellence where our technology gets adopted across the enterprise, again, to capture those signals across the customer journey, right? That's what feeds the machine learning models. That's how we get smarter. That's how we can help even more our customers. So let's double click a little bit on the bottom line now. And it's how we will accelerate our path to profitability. So it starts with gross margin, right? So when you look at the gross margin, it's in red at the bottom. Product gross profit margin is -- has consistently increased from 80% 6 quarters ago to 83%. Laurent showed you all the innovation on the platform. But also in parallel to that, there's a lot of optimization on the computing infrastructure while ensuring that we're still 4 9s, 5 9s, and that there's no security issues, right? So it's a daunting issue, yet the engineering team, lots of stability in the team, lots of expertise across the computing infrastructure that we leverage so very far. So as a reminder, when you think of cost of revenue, the computing infrastructure is really the most important cost in there. But there's also the cloud ops team, there's customer success, there's tech support, which are important components. But certainly, compute infrastructure costs are certainly the highest cost in there. Of course, when you look at the total product -- the total gross margin, it is -- it does get diluted by professional services, as I -- as a reminder, it's about 8% of our revenue. It's about 15% to 20% margin. It does get to be a bit lumpy on the professional services front. It's still a small organization. When we acquired Qubit, the profitability was not to the levels that we typically experienced in the past. So right now, you've seen a little bit of lumpiness. But overall, very happy with the progression of that team of integrating the Qubit team into Coveo. So now the next item is the operating expenses, right? So here, again, what you'll see is that over the last 4 quarters, where we used to spend 100% of all of our operating expenses as a percentage of revenue a year ago, now we're down 9%. 900 basis points of efficiency that we've saved over the last 4 quarters. How were we able to do that came from sales and marketing. Sales and marketing, 8% -- so of that 9%, it came 8% from sales and marketing as they were more efficient. Sheila showed you, right, how she's been able to go from in-person events to 100%, of course, digital. And now she's able to optimize between those 2. With regards to the sales team, we used to be organized by territory. When we moved to COVID, we reorganized and specialized. That increased productivity. So with all those measures, of course, we've had -- that's how we've been able to go from 53% of sales and marketing expenses as a percentage of revenue down to 45%. So amazing. When you look at R&D, it's remained constant. We believe that we're still in the very early innings of AI-driven powered applications. So from our perspective, we're not asking Laurent right now and R&D to make some important savings here. We want him to keep innovating at a fast clip. And certainly, from a G&A perspective, we did have to absorb a number of costs of being a public company, but now it's all about leveraging systems, teams as we grow, of course. We often get asked about unit economics. So let me start with talking a little bit about what the definitions of each of those 2 that we're going to talk about. So we're going to talk about CAC/ACV and we'll talk about LTV/CAC, okay? So CAC, of course, is customer acquisition costs. So when we're going to talk about customer acquisition costs, for us, it's going to be the entire sales and marketing organization, fully loaded, right? For the given period, we're going to work with them where we will be measuring the ACV, the annualized contract value. So it's going to be how many -- how much did we invest in sales and marketing versus how many bookings in annual contract value did we generate during the given period? So we'll look at that. And the next one, we'll talk about LTV/CAC, of course, a key metric. So here, again, to calculate LTV, customer lifetime value, we will look here at the average ACV when we land an account. Our average revenue per customer is $160,000 per year per customer, typically 3 years. But when we land, of course, it's lower and then of course it grows to the NER. So what we do is that we just take that ACV and we divide it by our GRR, which we saw in the mid-90s, right? So that's how we calculate customer lifetime value, and then we'll calculate what's the metric of how much we invest in sales and marketing per customer and see versus the actual customer lifetime value. So on the left-hand side here, CAC/ACV, as you've seen, we've been able to improve by 10% CAC/ACV, as we've discussed. For us, it's all about -- we've talked about the sales and marketing efficiency, right, where we reduced as a percentage of revenue sales and marketing. It directly translated, of course, into improving our CAC/ACV. So our bookings did -- kept growing at a very nice clip, but of course, sales and marketing expenses, which did increase, we increased sales and marketing over 20%. But of course, bookings grew at a much faster rate than sales and marketing expenses, and that's how we are able to improve this key metric. With regards to LTV/CAC, it's even better, 40% increase over that period. How were we able to do that? Well, first of all, the average land -- when we land a customer, the average ACV has grown tremendously over those 6 quarters. That's number one. We also talked about GRR. Our gross retention rate also improved. And then, of course, when you talk about CAC, we've also been able to reduce our CAC, so we're spending less per customer, hence, why we've -- because we've been able to improve on all those metrics, that's how this all translated such an improvement over such a short period of time, 1.5 years, basically. So if I kind of bring it all together, it really comes to accelerating our path to profitability. So we've talked about how we're improving our product gross profit margin from 80% to 83%. We talked about how we've been more disciplined from a sales and marketing perspective, right, going, over those 4 quarters, from 49% to 45%. We've been more efficient. We've talked about, certainly, from an R&D perspective as well, being more focused, being more prioritized. Louis talked about the focus on certain key initiatives and in commerce, in service. And of course, leveraging from a G&A perspective, now that it's been a year since we've been public, all those initial expenses, those initial investments are paying off. So what does that translate into the adjusted operating loss as a percentage of revenue? You've seen here, for last quarter, at 17%, which was an amazing beat. So -- and we're extending it for next quarter as well. So for the December quarter, midpoint of the guidance is at 20%. So for us, for the fiscal year, that was an $8.5 million, almost 900 basis points improvement with regards to adjusted operating loss. So again, we're adapting to the times. And while certainly from a top line perspective, being able to deliver on strong growth, certainly being more efficient with it, and of course, extending that for the remainder of 2023. So with that, I'd like to just conclude that for us, we believe that we're in the early innings of AI and ML. It will be a revolution. Hopefully, you've understood the innovation that we're pushing in the market right now. And all those customers certainly from all those global tech leaders all the way to very traditional industries are adopting it. We have one platform, one single multi-tenant platform for all those customers, enabling, of course, fast upsells and cross-sells, have a large TAM that Louis talked about. So initially, we started with intranets way, way back when Laurent founded the company. Doubled that with service, now doubled it again with commerce. We have a loyal customer base. We talked about the GRR and then the NER, 111%. And of course, we talked about all those areas that we have for us to grow across -- we talked about the white space within our customer base, but as well outside, with winning new customers, with our partners, and, of course, on our own. And finally, an experienced management team to keep delivering and executing on this plan. So with that, I'd like to invite Nick for the Q&A session, and as well the rest of the team.

Okay. So yes, we'll start here. Ittai?

Ittai Kidron from Oppenheimer. And thanks for the day today. It was very informative and very impressive, I might say. And Louis, I will say, for how impressed I am with the vision and the product, I'm kind of scratching my head with what's little left on top of it and saying, how come you make so little economics from your customers? For all the value that you bring to the table, my question is, why isn't the ticket bigger? Maybe I should ask Darren. Would you pay double the price for the value that they [ come around ]? Asking seriously, because ROI is very clear. Time to value is very clear. So why can't customers pay more for this? That's question one. Question two, now that you have a bunch of broader portfolio and commerce has clearly been a very big game changer for you, what are the opportunities not to cross-sell, but to rather bundle and get far greater adoption faster and bigger, right? And heel-to-toe type of progress, more like jumping up a hill kind of a movement.

Yes. Well, I mean, 2 questions that are right at the core of our strategy. The answer to your first question is we're getting there. We work with large global organizations, and getting the data to close the loop and connect what we do, you start with a relevance platform. That's a little bit -- if you say in a bar on a Friday night that you're in the relevance platform business, you're not -- that's not a very good conversation. So you have to make it really, really tangible with data and then close the loop. So basically deploy, measure, connect that to the financial outcomes and then close that loop. You heard me early in the first presentation this morning. We're obviously amazed by some of the metrics that we see and some of the financial ramifications. I mean some of our commerce customers are $1 billion -- multiple billion-dollar sales companies. And when you move these metrics by several percentage points and so on, on the revenue side, the conversion, and it's [ not ] to your point, you say, "Hey, the value of that software is significantly higher than what we get for." I think it's -- it leads to reengineering the business model and we're thinking about that around engaging -- taking on more risk and engaging on a performance basis with some of our customers. More like if I hand you $10 of cash flow, maybe I can charge you $1 for it and then guarantee the results and so on. And we're certainly -- we certainly have a team that's focused on that right now. It's easier said than done. You need to establish a processes and so on to measure that and so on. But we're definitely -- I can confirm that we're definitely working along those lines right now and that we know -- and it's not about abusing our customers or whatever. It is about getting into a real partnership. Today, we've been more -- because of the evolution of the company, we've been more a software supplier, so to speak, as opposed to a business partner in many instances. And so to change that relationship to a more strategic relationship kind of goes hand-in-hand with the evolution of the brand. Coveo was a no-name company just a few years ago and then suddenly, we do some amazing things with some of the greatest brands in the world. And so that recognition allows us to get into the C-suite much more often and partner at that level and then talk to the CFO and then talk financial metrics and so on. So that's the long answer to your first question, but definitely, you're on the right track here. Number 2 is sort of along the same lines as our platforms group now is able to really, to your point, bundle or position the Coveo platform. Because Coveo is really a platform. It's always been a platform, but when you start a software company, if you want to sell a platform, people won't quite see it unless you make it very tangible with specific use cases, which is exactly what we've done in our history. So we said, wow, we designed Coveo as an AI platform. We made it a customer service intelligence solution, and then a commerce intelligence solution, and a workplace intelligence solution, but underneath it is really a platform to unify digital journeys and digital journey intelligence. Coveo is an enterprise-wide intelligence platform, and we're making some good headways in conveying that message to the CIOs and so on and getting some traction there as well. And of course, that will lead to some much more bigger engagements with customers once they understand the true power of the platform as opposed to being pigeonholed in a tactical use case in a silo within a large company. That's still interesting. But that's, as Jean said, $160,000 a year, and the platform is $5 million to $10 million a year. That's really the difference, and we're working definitely along those lines.

But I mean to Jean's slide in particular, the cross-sell opportunity and even within particular lines of business where we have 1 use case and there might be 2, 3, 4 others that we can go within that particular LOB, we're in the very early innings of that opportunity, and that's exactly why we have the platform team now that can go and hopefully attack that. Yes, Richard?

Okay. It's Richard Tse with National Bank Financial. Louis, you talked about the Canadian Tire example. And I think we can all sort of appreciate that, who -- we actually use that website. What's holding them back from moving ahead? Is it sort of a technical thing, like they try to understand the market? And I guess the related question is that...

Well, to be clear about it, we didn't run a sale campaign yet with Canadian Tire, specifically.

Right. I'm just sort of talking more broadly.

Yes, more broadly, but we're just giving multiple examples because we're all consumers, and we all go to these sites and so on. And just to illustrate that these are big companies and that when we look at companies like that, what I mentioned totally out of the blue -- not out of the blue, but given our knowledge and so on, but without any specific analysis as it relates to Canadian Tire in particular but for a company of that size, that is between $5 billion and $10 billion of revenue, when we look at the digital experience and so on, we believe that the value of a technology like ours is in the hundreds of millions of dollars. And that's the scale that we operate at. And when we look at their experience today relative to what a technology like ours could provide, I'm just giving that as an example. I could name 99 other large retailers and providers of digital experiences. This is a new -- the application of AI and digital experiences, broadly, is very new. I've mentioned earlier this morning that, if anything, we were early in our market. The machine learning is not new, but it was limited to the companies who could afford hiring herds of data scientists and so on. I mentioned the Wayfair example. And it's public, Steve Conine, the CEO of Wayfair, went public a few years ago and said, we're processing 40 billion customer signals a month to essentially figure out the set of carpets that you will likely enjoy next better than anything that you could search. Now in order to do that, they hired 2,200 developers and data scientists. 99% of companies cannot do that. So we're in the early innings of that, but nevertheless, the imperative as we heard from Darren and -- the imperative of doing this is absolutely there because, again, goodwill is very, very volatile and only a browser window away. So -- and the ability of algorithms to maximize business outcomes is incredible in terms of value creation. So why isn't everyone jumping on this today? I think there is still a bit of education in all of that, but there is an imperative that is driven by competitive pressures, which is if you start losing -- and any business that's online, selling online, they see what converts. They don't see what goes away. See, and so that's where -- and so there's more and more education, but we see -- we would have gone 5 years ago, even, to retailers and to distributors, talking to them about an AI platform and the importance of personalization and the use of algorithms to optimize revenue and conversion and profits, and everyone would look at us and say, "Hey, what are you talking about?" And well, today, it's becoming much more mainstream. And so it's a question of timing, and we believe that we're right at the inflection point of that market. Thanos.

Thanos from BMO. Can you speak to the competitive dynamic? And so typically, in the sales process, is very often the decision the customer is making whether to go with a turnkey platform like yourself versus hiring the hundreds of engineers? Or is it more about other solutions that claim to be out of the box like yours, but really aren't. What do you run into most commonly, competitively?

It's a bit of a spectrum. I would say that in large companies, it's increasingly easy to make the argument that going down the path of getting elastic search and hiring herds of data scientists is probably not a good scenario that will -- it's certainly a very risky and a very expensive scenario to build it yourself, unless your name is Target, Walmart or something like that. And even there. So that's number 1. Number 2 is sometimes, and oftentimes, I would say, in the sales cycle, we run what we call these -- we call them art of the possible sessions with prospects, because sometimes we need to educate prospects on what is even possible out of the box. A lot of them come to us and say, "Well, my problem is search. I just need to fix search." And they don't understand what that means. I kind of explained this morning the search paradox in retail, for instance. If you put a search engine on a retail site, you're going to drive margins to 0. And I explained why this morning. Because the search engine is going to start learning what converts and what converts is popular products 0n sale. That's what converts. And so we start -- we run a lot of sessions that are in the sales process. They're not long sessions. They can take 60 minutes or whatever to sort of educate customers in the commerce space, in the customer space about what is possible, and more often than not, in the vast majority of cases, they're pretty amazed and it kind of resets their perception of what can be done and how easy it is. Because deploying Coveo is a matter of weeks. And that's what's amazing about this, is the ratio between effort versus benefit is extremely low in terms of -- or high, depending on what you look at, benefit versus effort, right? So Coveo is probably one of the technologies that brings you the most ROI relative to a very small effort, in fact, relative to the effort you're going to put in. And so there's a lot of that. So we get competitive pressure when the perception is that all you need is a search engine and we get compared to other search products and et cetera. But again, Coveo was born in AI. We've been a dozen years building an AI platform. We have hundreds of millions of cumulative R&D. We've never done a one-off for customer. As Jean mentioned, it's one single multi-tenant platform. So -- and what that means, by the way, when you invest in SaaS computing, whether it's with Coveo or anybody else, that model is extremely critical. SaaS is just a delivery model. SaaS about putting an app on the Internet and delivering it through the Internet and charging a subscription for it. That's SaaS, software-as-a-service. We are a cloud-native multi-tenant platform. What that means is there's one version of that platform. It's updated 15 to 20 -- Laurent said 1,500 times a quarter, you said? So several times a month -- sorry, several times a day to all of our customers simultaneously across the world. And it means basically that, that platform can be super robust, super secure, because we only manage one. It means that from an innovation rate perspective, all of our R&D is focused on enhancing that platform all day, everyday as opposed to many software companies that will take a piece of software, and the R&D team is busy dealing with customer 1, 2, 3, 4, 10, 20, 40, and ultimately, it doesn't scale. So our R&D team is larger than the vast majority of our competitors all together, and they're working that. So the innovation rate, and for those of you who've been following us for a while now, you see the speed of innovation that we're doing. And this is because of that architecture. So long story to say that we're accelerating the innovation and increasingly raising the distance between the competing search products certainly. The big platform vendors like Salesforce, like SAP, like Adobe and et cetera, they realize that the gap is only increasing. They don't have the teams internally to do what we do. So we're in a pretty good -- it's hard to be -- it's hard to build a Coveo, basically. The barriers to entry are very, very high because of the cumulative innovation that is built in the product.

I have a question for Laurent, which is if we were to look at a graph in terms of improvement in key metrics versus time. I mean imagine a situation where you turn on Coveo, you get a very rapid increase in improvements. But then how does it work? After a couple of months, do you kind of hit sort of diminishing returns, and then the impetus to try to bring in additional data sources with the customer? Or does it always keep getting better and better? How does that trajectory look?

Yes, that's a great question. So typically, in commerce, it's easier to measure your impact because the customer already has a lot of the instrumentation in place to measure the impact. So very quickly, we will have, as you mentioned, we will have typically big impact in terms of revenue per visit conversions, things of that nature. But then we will start working at ingesting more data in the models. So for instance, at one customer, we have a catalog coverage, meaning what -- how many products are part of those product vectors that I mentioned before? It was in the range of 30-something percent. So with a few optimization, we moved that to 85%. It has an impact on revenue per visit. We are adding new models, optimizing new models all the time, and it has 2, 3 points of revenue per visit. So that's a good example. And with the ability to do A/B testing all the time, almost in real time, it allows those customers to do tests very quickly and to change or adapt their strategy given the circumstances. So it's not done after the initial deployment.

And Thanos, I'd just add that -- look at Caleres. One of the things they've been able to do with some of our merchandising tools, they can test certain scenarios, and they found a couple that have bumped their revenue per visit by, I think, 4% in 2 separate occasions. So I mean that's big time. So it's one of those things where I think, as Laurent said, yes, you get us up and running, especially in commerce, but then there are ways to continue to improve and to continue optimize and find ways to generate more value.

And if I may, the next big frontier will be when we start sharing margins. And all of this data that I shared early in my presentation, when we start seeing that on a regular basis from customers, then we'll see another leap in terms of return.

If I may add, Thanos. The literal answer to your question is obviously, you get a quicker improvement at the beginning and then -- I wouldn't say you plateau. You can continue to optimize models and bring more models and et cetera, but you become the engine. And so the stickiness of this, we can expect GRR to remain very high, if only continue to increase, because then the option upon renewal becomes, hey, do you want to disconnect basically the brain of your commerce? And this is not something that's easy to do, if you understand what I'm saying. It's a little bit like the mainframe in an insurance company that runs -- has been running the policy and the actuarial system for 40 years. You don't disconnect that easily. It's in COBOL. That's another problem. But you see what I mean is -- so we expect these types of applications to continue to be extremely, extremely sticky, obviously, and to the extent that we tie value to the value we create, and then -- we think we can maintain that revenue stream over time and continue to grow it slightly.

It's Paul Treiber from RBC. Just the demo on merchandising hub was really interesting because I think it shows that the retailers don't like to give up some rules and would like to try to manage some of the results. The question is around advertising, though. Advertising, seems like it is an increasing trend within retail, particularly within their own websites. Conceptually, how do you see -- or do you have a plan to address that? And conceptually, how do you see integrating advertising into search results?

Yes. Retail advertising for large brands is a big opportunity. And in fact, let me give you a stat. Actually, Amazon's strategy right now is to run their retail operation breakeven and they make money from retail advertising. Tens of billions of dollars from retail advertising. And the strategy is very simple. They want to kill their retail competitors, and they make -- they fuel that with retail advertising. The key challenge in retail advertising is to insert that in the customer experience in order -- in a way that is not detrimental to the customer experience. Because fundamentally, you go to a site like Famous Footwear, $1 billion of shoes again. You're looking for, I don't know, Nike shoes or whatever. You don't necessarily want to see a lot of it. So how do you integrate -- and you can use AI essentially to sort of understand a degree of relevance, basically, of retail advertising and push that, but make sure that it's well understood in the mix of search results, recommended products, promoted products and then advertisement. And so we think we have the platform for that. We're not an advertising platform. There are some of those out there. But this can become an opportunity for us. Today, we're not in that space yet, but certainly, we have the platform to integrate retail advertising in the context. Because what companies don't want to compromise is the experience.

Thanks. This is David Weiss from Scotiabank. I just have a question in terms of, you talked a little bit about the qualified leads of the MQLs, and you provided some interesting stats there along with efficiencies that you gained in the sales organization. So just in terms of the potential customer win rates, how can we think about that a little bit like in terms of the type of customer, in terms of size or perhaps by vertical? A little bit -- you said you win, but I'd like to get a little bit more detail, if I could.

Lou, you want to take that?

Yes. We don't disclose the percentage of the win rate and et cetera. We can say that once we engage our sales organization, the win rate is substantially high. And we want it to be continuously higher, because at the end of the day, this is the yield of your sales expense. I don't know how else to answer the question but say we're...

We want to win -- we want to beat benchmark of the industry at every single level, and we do.

Yes. I would just add, David, that I think comparatively, as Sheila and Louis said, our win rates are very high. So once something gets into our pipeline, our close rates are -- I mean, I've worked with a number of companies in the past. Ours are really good. From an industry vertical standpoint, I mean, look, you know the 5 verticals that we focus on. Certainly tech is our bread and butter, and we've been incredibly successful there. And I think also on the service side in general, our market position in service is very strong and in particular, in the Salesforce ecosystem, we're very solid. So look, from a customer size standpoint, I think it was another piece of your question. I mean, we do very well in enterprise. That's where we focus., targeting 6-figure land type of transactions. And again, I think we do very, very well in those situations. Where we might be a little bit overkill is when you're looking at, like we talked about, a Shopify account or something like that, where there's a very small number of SKUs and it might be a 4-figure type of transaction. That's not where we do well. Where we do well is high complexity and large number of SKUs, global use cases, things like that.

Okay. Great. That's great. And then one more sort of question switching to just the margin side. So in terms of customer support reorganization, could you provide some points on how you differentiate yourself in that aspect of the business? Just wondering if you actually leverage Coveo's AI yourself in-house, and if that's also perhaps a valuable source of not only customer feedback and satisfaction but perhaps margin improvement as well.

Yes. We call ourselves customer zero. So Coveo runs on Coveo, it's fair to say. So we have our platform available in our customer communities, in our partner communities, into our contact centers and throughout our support organization and elsewhere in the company. So yes, we do get a lot of feedback. We basically use the infrastructure that most of our customers use. Absolutely. In fact, temporarily, we just disconnected Coveo on one platform recently as a temporary transition, and the employees are complaining. So yes, we use it extensively.

Our leader in this space presented at the Technology Services Industry Association, TSIA. We've been -- and we benchmark office, and we've been winning awards from that association multiple years, again, leveraging Coveo. So certainly, we do drink our own champagne, and it's paying off.

Kent Crosland at Mackenzie Investments. Jean, this question is for you. In your presentation, you mentioned that the vast majority of your customers are on 3-year contracts, so they don't churn off in the first 3 years. For the customers that do churn off or leave the platform after 3 years, what are the biggest reasons that they'd leave?

The main reason is, really typically, would be M&A. So we -- and the company that acquires our client, though we do see some of our customers acquiring other of our customers, as we're very concentrated in certain industries. But certainly when they do, sometimes, a company that does acquire our client does not run, for example, on Salesforce or SAP. So of course, there's 2 edges to it, right? Those partnerships are an amazing accelerator for our go-to-market motion. However, when, of course, the acquirer does not run on that same platform, they want to replatform, and it's a different platform that is not a close partner of ours, then it does become a challenge for us to still secure our position. So that's really been our most important reason for churn, though, as I said, churn is very small. We talked about mid-single digits. But in those situations, M&A has been the big driver -- the biggest driver.

Yes. I'd just add, we often see situations in which the platform vendors will overpromise their native capabilities. And we actually see, in some of those M&A situations, customers coming back to us 2, 3 years down the road saying, "Oh, wow. I was promised that this native solution was going to do this," and it doesn't, and we actually get the chance to reengage with them. So we certainly see situations where customers go away and then they come back at some point down the road.

David Kwan at TD. Louis, I think, to start, you talked about offering maybe more value-based pricing options. So I was very curious if you could elaborate on that more. Is that maybe targeting some of these developers and enterprise customers that maybe don't have a lot of budgets to work with? Or is there something else?

No. It wouldn't be working with the developers, creating -- working with the developers to create centers of excellence within customers, we think is a best practice. What we're interested in is combining the power of our platform and machine learning with expertise to team up with, in this case, senior executives of companies in achieving results. So essentially, we're in a position where -- and we're certainly building all the BI. We have a pretty extensive data analytics and BI team at Coveo, and we're building a BI right now that really is focused on the digital metrics, but then -- and the digital performance metrics of commerce and service, et cetera, but also triangulating that to financial returns. And so we're interested in teaming up. There is a certain number of customers that we're in discussion with that want to team up with us not as a software supplier, but as a business partner to help them -- to commit with them to certain improvements in terms of revenue increases, margin increases, et cetera, and engage into different types of contractual terms, to do that essentially more on a performance basis. And they see the advantage of doing that, while it may cause them more money down the road, they see the advantage of doing that and having the full force of the firm and us bringing a lot of expertise combined with technology to really commit to those results. And so essentially, what we say internally at Coveo is when we give $15 of cash flow to a customer or we unleash $15 of cash flow to a customer, can we charge $1? And -- conceptually. And increasingly, there are companies willing to do that. There are also a number of analogs in the industry of some of our SI partners like Accenture. Even McKinsey right now has a massive digital business that is -- and their revenue is entirely performance-based, actually. So they go to companies and they say essentially, "We're to team up, and let's look at your margins, let's look at your revenue, and we're going to put the full force of our firm and our data analytics capabilities and our expertise to commit to results, and we're only going to charge you when we achieve those results." And we are gaining a level of confidence that allows us to make that -- those predictions and those proposals with a fair -- a low level of risk. So obviously, it could change for those deals, the profile of the revenue recognition. But if we think about shareholder value, there's definitely an advantage in doing that from a -- because if you're a software supplier -- and I'll just finish on that, if you're perceived as a software supplier, and we are, to a degree, you work with a customer on a use case, you're procuring a software, a statement of work to deploy, which has a beginning and an end. And I would argue that today, customers look at us and they say, "How much does it take to deploy Coveo?" And they see that the project has a beginning date and an end date, and it's almost like afterwards. I get in customer support and et cetera. I would argue that the end of the deployment should be the beginning. Because it's the beginning of the -- because if I throw data scientists in there and et cetera, I can take their metrics up the roof. But customers don't see that because they tend to have it -- well, no offense, they tend to have a tactical view of us as a supplier as opposed to someone who can double their margins. So -- and this is certainly something that we're absolutely exploring and making hires today as we speak. And some of our customers tend to be a little more strategic and want us to do that for them. Because at the end of the day, this is what matters to them, is growth and operating income. I mean that's what they want to help us. And we're in a position to move the needle quite a lot for that.

That's great. I appreciate it, Louis. Maybe a couple of questions for Sheila. Obviously, in person you talked about going more to that now with the pandemic easing here. Obviously, they're a lot more costly though, but they're more effective in generating MQLs, right? So can you maybe talk about the differences in the ROI, I guess, between your in-person events and digital marketing and what you can do to help narrow that gap?

That's a very good question. Actually, we don't separate. They both work together. That's the most important thing about events, is that events is not just about the event, not just about the booth that you have there. It's the pre event. It's how you use this as a reason to use your digital marketing and contact your prospect and have a discussion with them pre-event. And then during the event, how do you also interact with them, with having meetings and organizing top-to-top meeting, just using the event as a reason. And then after, how do you contact the prospect that you met and the one that didn't have the chance to be there so that you can provide the content that other people had during this event? So we don't look at the event itself as an ROI. It's the full ecosystem around the event that is important, using digital to maximize it and to scale it. So others, just the event itself has a really good ROI because in-person contact, as you all know, is much better. But then it also propels and accelerate our digital marketing to events. So it's a bundle together that we don't separate, but I can tell you that since events are back, ROI is going like this.

Great. Thanks. Other questions? Okay. I don't see anyone else raising their hands. So with that, we'll go ahead and wrap up. Thanks, everyone, for joining both in person and virtually, and we look forward to pushing ahead here and executing. And hopefully, we'll see everybody next year for Capital Markets Day number two.

Thank you very much.