Dun & Bradstreet Holdings, Inc. (DNB) Earnings Call Transcript & Summary

Hello, everyone, and welcome to today's CRM Magazine web event brought to you by Dun & Bradstreet. I'm Bob Fernekees, and I'm the publisher of CRM Magazine, and I'll be the moderator for today's broadcast. Our presentation today is titled Intent Data for Sales and Marketing, Accelerating the Buyer's Journey with Personalized Experiences. Before we start, I just want to explain how you can participate in this live broadcast. At the end of the event, we'll have a question-and-answer session. [Operator Instructions] We'll try to get to as many questions as possible. But if for some reason, we can't get to yours, don't worry, we'll follow up with an e-mail response within a few days. Plus, if you'd like a copy of the presentation, you can download a PDF from the Handouts tab on the console once the event is archived. And just for participating in today's event, you could win a $100 Amazon gift card. Now to introduce our speakers for today, we've got Nipul Chokshi, VP of Marketing at Dun & Bradstreet. Welcome to the broadcast, Nipul. And Nhungly Dang, the Senior Director of Account Development at Dun & Bradstreet. Welcome, Nhungly. So now I'm going to pass the event over to Nipul. Again, he's the VP of Marketing at Dun & Bradstreet. Welcome to the broadcast, Nipul.

Thanks, Bob. Hello, everyone. Great to be here. Really excited, and thank you for joining us. Wanted to just kind of walk through a few things today. Ultimately, what we wanted to do is just provide each of you with some examples of how you can leverage intent data as part of your marketing and sales strategies, examples derived from real-world use, use from our customers here at DNB, how we ourselves use it at DNB for our own sales and marketing efforts and so on and so forth. But before I do that, I wanted to just go into a little bit of context. So ultimately, as revenue leaders going into of 2020 earlier this year, there were a variety of different transformation initiatives that we were likely engaged in, whether it was deploying an ABM program, whether it was developing customer-led journeys, whether it was implementing agile marketing and so on and so forth. Needless to say, over time this year, there have been various disruptions that have just accelerated the urgency and need for those transformations. Ultimately, our buying landscape has changed. I don't think anybody would dispute that. One stark stat here from Gartner, most companies are not necessarily amenable to face-to-face meetings. There was another quote where Satya Nadella, the CEO of Microsoft, he was on a quarterly earnings call and he said, "We've been through what amounts to 2 years' worth of digital transformation in 2 months." And so needless to say, a lot in our world has changed. But it's more about -- it's more of a change where we knew we were headed to this change. It's more about the accelerated pace of that change. And so to that end, when it comes to engaging with our buyers more and more, we -- they kind of trend towards buyers preferring to self-serve their way through a buying journey. Buyers not necessarily wanting to identify themselves to brands before they engage. Totally understandable. I, as a buyer, do that myself as well. But as a brand, it presents -- as a brand marketer, it presents challenges in terms of how do we actually engage these folks, right? And so the idea here is how do we kind of understand what that buyer journey looks like now that buyers are doing more of their research online that -- more buyers are opting not necessarily to identify themselves to us as brands. And so what I want to do is just kind of talk you through a couple of ideas and strategies that we can use, specifically around some of the signals that are available, whether it's intent signals on our website, whether it's intent and interest signals off-site and to be able to harness those signals to drive better engagement with buyers. And so I'll start with kind of a framework. And this is a great framework that we've used with a lot of our customers, where you kind of say, "Okay. Let's draw out the buyer journey." And for keeping things simple, we kind of say, "Okay. Let's divide up the buyer journey on the X axis into 4 stages, right?" There's kind of the stage of buyers who are not necessarily even in market today, but they may or may not be a good fit for your products. There's the stage of buyers that are in market but haven't necessarily engaged with your brand. Then there's a stage where buyers are coming to your website and anonymously browsing your website, giving you some indication of interest, but they haven't necessarily raised their hands or opted into any communications. And then finally, there's this stage of they've identified themselves to you, they've opted in and they may be in active discussions with you as well. And the idea here is you kind of look at and identified buyers at each stage of the journey. And for each stage, you want to say, okay, which of these buyers are actually high fit, meaning how likely are they to actually become a customer of ours versus low fit. And the reason I start with this framework is it gives a good way as a marketer to kind of think about how do I actually start engaging with buyers. And the idea here is, depending on whether it's a high-value customer or a high-fit customer or not, depending on what stage of the buyer journey they're in, obviously, I'm not only going to have different messages and different offers, but there's different levels of investment that I'm going to place in my tactics, whether it's making sure that my sales reps are doing outreach against these buyers, whether it's making sure that I'm spending more on display ad campaigns and paid social campaigns, whether it's investing in paid search and so on and so forth, right? So this is kind of a good framework in which to be able to identify where buyers are. Now ultimately, when it comes to saying, okay, which stage of the buyer journey our customer's in? There's this new kind of set of signals loosely termed intent signals that enable you to really identify what stage of the buyer journey they're actually in so that you can actually engage them with the more relevant topics. And the way most of our customers think about intent is they really kind of say, okay, there's 2 buckets of intent loosely speaking. There's one bucket, which kind of at the base of it is intent that you get from third-party websites. And this is data that you can buy from various vendors, including DNB, where it gives you an indication of the type of interest as well as the level of intensity with which they're interested in very specific keywords or topics or topic areas and whatnot. And almost always invariably, the solutions here will provide you with a sense of the company as well as potentially the contact that's actually expressing the intent. And then the second bucket is, in my mind, more powerful is because this is intent on our own properties, right? So these are folks that are browsing our websites, whether they're doing it anonymously or maybe they're cookied after having attended a webinar or downloaded a white paper or filled out a form or something, right? So the idea here is there's varying levels of intent that you have access to as marketing and sales folks that you now have the ability to kind of harness to be able to say, okay, what stage of the buyer journey is my prospect in and to be able to respond appropriately from a tactic standpoint as well as message and offer standpoint. The other thing to keep in mind is there's different ways to think about intent. Ultimately, what we've observed is customers who kind of leverage and arrive at intent signals from a variety of different perspectives are ultimately more successful, right? So there's kind of intent where you have a sense of what are the keywords or topics that people are interested in. You also have research-based intent, which is based on the type of content that folks are actually expressing interest in as well as personalized intent, which is basically where -- for example, you've got keywords that you're using to be able to attract or search terms that are the most relevant for you and to be able to track interest based on that. And so ultimately, the idea here is you want to have a holistic view of the types of interest that particular prospects are expressing and then to be able to act on that. And so with that as context, what I want to do is just kind of walk you through a few examples. So I'll walk you through 3 examples on the marketing side on how marketing leaders can leverage these signals to just do smarter and more targeted and more focused marketing. And then I'll throw it over to Nhungly, my partner in crime, who will speak to the sales-oriented use cases. And so the first example here is all about advertising, a great tactic that we've all leveraged, particularly as part of our top-of-funnel tactics, tactics where we're looking to drive engagement. And so I wanted to just kind of walk you through one of our customers, how they're leveraging intent signals to just be a little more targeted and a little more focused so that they can actually drive higher ROI on their digital ad programs. And so what they've done is they've kind of said, okay -- they ran -- they run paid media programs. This is a company that sells a variety of different types of IT solutions, ranging from cybersecurity and online protection-type solutions as well as analytics and Internet of Things management platforms and whatnot. And so what they'll do is instead of just showing for anybody at the top-of-funnel, a generic brand ad, what they'll do is they'll look to see what's the -- what are the types of topics or keywords that the brand is actually expressing interest in. If they're interested in data privacy and malware protection and whatnot, they'll show them kind of this top ad where they highlight their value proposition around cybersecurity. If, however, the brand is more interested in topics like beacon technology and Internet of Things and whatnot, mobile devices, they'll highlight the relevant value prop there. So this is a great example of how intent signals are a great indicator of the interest or the use cases that your buyers may be interested in. And that's a great signal for you to be able to use in order to personalize your digital ad programs. And we'll come back to this whole notion of the interest and how that relates to the types of use cases that you can talk to because Nhungly will talk about what that means from a sales standpoint as well. Another piece here, that same company now, what they'll also do is they'll also differentiate the amount of investment that they place with regards to their digital ads based on the level of fit. So if someone is expressing interest in data privacy and malware solutions, they won't bid equally for anybody who expresses intent in that. What they'll do is they'll say, okay. I'm going to look for folks that are most likely to convert that really, really kind of hit the target in terms of them matching my ICP, my ideal customer profile. And I'll bid more on those folks that have expressed intent and less on the folks who aren't necessarily as likely to convert, aren't necessarily -- don't necessarily resemble an ideal customer for me. And so the idea here is by setting -- not only can you kind of match the ad copy to the interest that is expressed by your buyers, you have the ability to then differentiate your bidding as well based on who's actually expressing that interest and how likely they are to become your customer. Okay. And so this is just kind of an example here. The example that I was talking about, the -- some of the impact, you can see some of the metrics that they were able to observe as a result. By being more targeted, they not only were able to improve on the viewability of the ads. So more of their target accounts actually saw the ads. They were actually able to reduce their cost per engaged account. And again, the reason for this is, number one, they were a lot more targeted based on the interest that the buyer had expressed. They actually showed them a corresponding value prop rather than the generic brand ad. And second, they differentiated their bidding based on how valuable or how likely that customer was to actually convert. So that's one example all around driving paid media and digital programs and how intense signals can help you to do that. Another example is kind of applying that same mechanism for your website experiences. So we have a variety of customers where what they'll do is they'll de-anonymize visitors to their website. And based on third party -- so if this is a visitor to their website who hasn't necessarily visited them recently in the past, they'll use third-party intent signals to be able to say, okay, what are the topics of interest? And as a result, they will customize the bits and pieces of the landing pages that the visitor goes to on their website in order to make sure that they're further engaged. Then you can see some of the impact that our customers have been able to see as a result. The third example is all around buying committees. So a lot of us in B2B, we sell high annual contract value deals, high ACV deals, where we're selling not just to one person in an account, but we are selling to multiple folks in an account. And so before we actually kind of indicate the sales, that this is a sales-ready prospect, I think it's important to be able to assess the buying center and the buying location and whether there's an actual buying committee that's been formed. And it just sends a stronger signal of priority for whoever is doing the follow-up on the sales side, right? And so one of our customers, for example, they sell to -- they sell cloud-based solutions, developer solutions to companies that develop cloud-based services, SaaS software. And so for example, if they sold to Amazon and they wanted to be able to personalize based on the -- and identify whether someone is a good target for them using the type of interest that they're actually exhibiting, what they want to do is they want to look at not just the domain. You also want to be able to identify the specific entity within Amazon. You want to be sure that it's Amazon Web Services and someone from Amazon Web Services that you're actually engaging with rather than just anybody from Amazon who could also be from a retail branch, and so it's not as relevant for you. And then another example here is we have companies where they're able to identify buyer committees just based on the type of interactions and the intent that they're expressing with their campaigns, right? And so what they're doing is they're saying, okay, I want to look for all people, for example, who are on my website, who have expressed the interest in my -- just -- I'll just make this up, on my mobility and cloud-based solutions, right. And the idea here is I want to score those accounts higher if I've got an engagement from someone with a data title in their title as well as a finance-associated title. And so the idea here is based on -- you can identify buyer committees based on the intent that's expressed by different buyers across the account. So being able to look at and ensure that different titles that are part of the buying committee typically for you are actually expressing intent. So that's another great signal. And so there you have it. Those are like 3 quick examples where intent signals can enable you to just get smarter and get more for your digital dollars with top-of-funnel digital ad campaigns, with -- improving on the conversions on your website and signals that can help you to identify when buying committees have formed, especially useful for those enterprise selling-type scenarios. And so with that, I'm going to turn it over to Nhungly, who will walk through some examples of how sales teams and sales development teams can leverage intent to drive more effective outreach.

Thanks, Nipul. Hi, everybody. It's great to be here. Before I jump into the sales use cases, I wanted to share a bit more context about the SDR team. So beginning of this year, we started out with 5 SDRs, and we're now at 25. And then as we move into next year, the plan is to further expand that team and possibly double the number of people on the team, right? So that's -- so it's very important for us to have a systematic process. The SDRs follow as they build pipeline from their own efforts but also while they're supporting marketing activities for webinars, events, inbound leads from the website. So to get into a bit more context of scaling here. For us to scale the team effectively, we've had to adopt a data-driven approach to help the SDRs stay organized, productive and relevant with their prospects. So in the next few slides here, I'll be sharing 3 sales use cases and how we've deployed data and insights to increase the team's focus and productivity. So the first use case here is really around prioritizing sales outreach, right? So we worked closely with our marketing team as well as our marketing analytics team to create a propensity model, and this is against the SDR's assigned accounts. So accounts were prioritized based on account fit, so accounts that are high value for Dun & Bradstreet based on a number of different attributes. We also looked at low risk, right, so meaning companies that are financially stable, industries and locations that are not impacted by the pandemic. And so with this type of insights, we're able to identify accounts with opportunities for up-sell, cross-sell and also new customer acquisitions. So this is a combination of white space and also greenfield. We then pushed a variety of data about each of these accounts back into Salesforce, right? So this helps the SDRs and the sales team be more effective with their outbound efforts. So here is an example of a cross-sell use case. It shows the lattice rating for each account and the potential for selling additional products. So what SDRs and reps are doing is prioritizing, prospecting outbound efforts to As first, then Bs and then so on. In addition to prioritizing what accounts to focus on, they are also leveraging talking points, right? So what we're doing here is reducing SDRs' time spent on research and then manually piecing that data together on their own. So the data that we're pulling is from a number of different sources, right? So we're using company transaction data, so that identifies cross-sell/up-sell potential and sales plays for the team. Understanding the company's tech stack is also really important. So it allows the SDRs to change the talk track if a company is using a competitive solution or if they have a compatible technology installed. So we're -- another data point here that's shown is layering in intent -- buyer intent signals, right? So this, again, allows the SDRs to further prioritize their outreach so they can capture market opportunities before their competitors. And then now that the SDRs have a focus on accounts and sales plays, how do they actually put this all into motion for prospecting to generate interest and secure meetings? So this is where contextualized prospecting comes into play. So most -- sorry about that. So most SDRs and sales teams are using some sort of sales engagement platform like Outreach or something similar. At Dun & Bradstreet, we currently use Outreach. And this is where we've set up a contextualized prospecting process. So the question that we get a lot of the times is, should you personalize or be targeted? In our case, the answer is actually both. In order to scale, we actually have to be very targeted. And then once prospects engage, that's when the SDRs will start to personalize, right? So -- but there's going to be instances where the SDRs will start with very personalized messages against a small set of accounts, right? These are going to be strategic accounts that they're really trying to penetrate with their reps. So to go into a bit more detail on how we stay targeted. So it comes down to being persona-based versus being product-centric, right? So you can see an example of some of our sequences here. But we've created persona-based sequences that makes prospecting more manageable for the SDRs, right? They're juggling a bunch of different things. So having a very systematic and organized way on how they drop people into the various sequences is just going to help them move through their day more productively. So SDRs are -- the way they prospect is going to be through Sales Navigator and using Dun & Bradstreet Hoovers. So when they identify the right contacts, they then drop them into the persona-based sequence. We also try to automate a lot of this manual work for the team. So Dun -- D&B Hoovers is integrated into our Salesforce. The SDRs are also using a tool called Seamless.AI to quickly import their contact list from Sales Navigator back into Salesforce, right? And so again, just thinking through logistically of how to make each process more effective. So within the sequences, we include a number of different types of steps, right? So there's going to be calls, e-mails and LinkedIn activities they'll need to complete. So for LinkedIn activities, we're also using persona-based messaging there in order for us to scale on that channel. And then if the account is surging intent, then SDRs will prioritize prospecting efforts there first. The intent data is also going to allow us to identify areas of interest, use cases and then also what stage of the buyer's journey are our prospects in, right? Are they in a research mode? Or have they progressed to a buying state? This will also dictate the frequency of the SDRs' outreach as well, right? So once they do their outbound and prospects start to engage with the SDRs -- and the engagement could be a number of different things. It could be clicked in an e-mail. It could be connections on LinkedIn. But this is when SDRs will start to personalize their message, right? So they'll go back into Salesforce, look up any historical information that they could start to use, right? They'll dig into the prospect's LinkedIn profile a bit more. What have they recently posted? Have they deployed or released any new products? Just really understanding this person's responsibilities, right? And then we're also prioritizing based on seniority level on how they do their outreach, but then how much they'll start to personalize as well, right? And then the very last use case here is around how sales reps can actually leverage a data-driven approach to identify churn risk and retain customers, right? So we know that acquiring new customers will be more costly than retaining existing customers. So if you bring on the right customers, you want to make sure you deploy strategies that reduce churn but also give your reps an opportunity to sell more into those accounts. So this is a really good use case in leveraging intent data, where it's going to be extremely helpful for the reps. So for example, upcoming renewals. You can track a number of different topics, right? And some of those topics can be your competitors' name, right? And you'll be able to identify customers that are researching your competitors, right? And so here is an example of companies that are showing research intent versus buying intent, right? So the way that works is there's topics and article types that indicate customers are in the research stage. And then there's a different set of content and topics that then show that this customer has progressed into a buying stage, right? So again, having this insight really allows the reps to be proactive and also just get ahead of the churn risk, right? Additional use cases that intent could be used for is during active sales cycle. Again, similar process as reducing churn, right? You'll get insights into which accounts are extensively researching competitive solutions, right? This again allows or enables the rep to effectively navigate conversations, right, with the various stakeholders as they have continued conversations through the sales cycle. Another way would be for new customer acquisition. So we have -- we're able to identify companies that are currently using a competitive solution. And then because we're tracking our competitors, you can then start to see when these companies are in market, looking or researching or shopping for alternative solutions, right? So it's really always about how do we stay really targeted and focused in our outreach, right, to maximize pipeline development. So I've covered only like a handful of use cases here, but there's a variety of ways that you can incorporate data to improve efficiencies and targeting for your SDRs and your sales team. One thing I also wanted to mention, in case anyone is interested, a few of my SDRs and the -- and I wrote a blog series in Q3 of last year about the team's workflow and process. So similar to what I shared today, but we kind of go into a little bit more detail. So there's currently 6 blogs that we wrote. If any of one is interested in reading any of those blogs, feel free to ping me, and I can send those links over to you. And I think we're going to wrap up here. Nipul, you want to summarize everything?

Yes. Awesome. Thanks. Thanks, Nhungly. Some great, great insights there. So hopefully, that was -- we tried to keep this as short and succinct as possible, tried to just give some quick tips in terms of how intent data -- whether it's first-party intent data on your website or third-party intent data that you're able to get to drive better marketing and better sales. For those who are interested, we're happy to kind of help drive your understanding of how intent can help you. And so you can see a few links here that you should be able to peruse. But with that, Bob, do we want to start with the intent -- with the Q&A?

Yes. Absolutely, Nipul. [Operator Instructions] I'm going to jump to Nhungly here, but feel free to jump in, Nipul, if you'd like. The question is, intent alerts can get complicated really fast. How do you make them manageable for your team?

Yes. No, that's definitely a great question and things that we also were challenged with as we're kind of creating these -- a systematic way for the SDRs to kind of move through their day. So just -- again, I think it always goes back to being persona-based focused, right? And so these intent topics that we're tracking are going to be very specific to the different personas that we target, right? And so if you make it persona-based and it's about the use cases that we can solve for them, then it's easy for the SDRs to prospect into those very specific personas and then just drop them into their specific -- the persona-based sequences, right? So if you're being product-centric, then a number of different personas can get in there, right? But if you're persona-based, then we don't really talk about the product. We just really talk about how we actually solve their challenge based on things that, that persona is going to be interested in.

Okay. Great. Nipul, how can people use intent data to personalize the customer journey?

Yes. Great, great question. So a few ways, right? So when I showed the example earlier around the advertising, you can leverage intent data to identify what are the topics of interest, right, what are things interested in? And the example that I had, it was a tech company that sold cybersecurity software as well as software to manage Internet of Things, devices and whatnot, mobile devices and whatnot. And so what they're doing is, for example, looking to see, okay, if someone is expressing intent and interest in topics like malware and online protection and threat protection and whatnot, then the ad that they will show them is very much around their cybersecurity value proposition; in contrast with someone who expresses interest in mobile devices, Internet of Things and whatnot, they'll show them kind of an ad with the associated value prop. So that's a really good example of how you can use intent data to personalize the buying journey just by kind of matching the ad copy to the interest that folks have exhibited. Another way here that you can use intent data is if there's -- you can look to see how much interest folks are exhibiting on your website, for example, based on the number of website visits that a particular account has had or a particular user has had with specific campaigns or specific solutions pages on their website and whatnot. Obviously, that will change the value proposition that you talk about. But it also can improve on how much you shift your investment from a digital ad standpoint if you are retargeting those folks. So if it turns out to be a company that really, really resembles your ideal customer and has a lot more interest in specific topic areas, it's a good bet that you've got -- that these folks are further down the buying journey. And so maybe you should think about investing more in terms of your retargeting dollars, maybe even making sure that you're alerting sales to that fact so that they can raise their priority on that particular account when it comes to doing their outreach.

Okay. Great. Nhungly, I think this question actually refers to the first question that you had. If somebody expresses intent in multiple use cases that your company serve, how do you frame the outreach, balance the pitch? How do you do that?

Yes. No, that definitely is kind of in line with how we manage the persona-based sequences, right, so kind of piggybacking off of my answer for that. So if -- let's just say, if it's a digital marketer, right, and we're tracking a number of different topics, right, that they may be interested in, whether it be advertising -- improving advertising tactics to down to even ABM, right? And so if certain topics are surging higher than others, then that's -- the -- then -- and we do some decision-making here, right? If they're surging more -- surging higher on ABM, then that's definitely the use case or the persona sequence that we'll start to drop them into, right? And then also, through our propensity model, it could also help guide us to understand like what is going to be most important for this company and what are the things that we should bring up with them, right? Nipul, I think you might have some additional insights into how we could also improve that framework as well.

Yes. No. I think you summarized it really well just in terms of how you can leverage kind of the personas and talk more to the problems that you're solving that, again, kind of this approach of looking at the type of interest that your buyers are expressing as a way to really kind of target and personalize your outreach.

Okay. Great. Nipul, what are the main use cases that somebody that's just getting started with intent, what would you say is the best way to have somebody focus if they're just getting into -- from square one? Can you give us just a little...