Deluxe Corporation (DLX) Earnings Call Transcript & Summary

All right. Well, I think we're at 11, so we'll get started. Welcome to our fireside chat today covering financial institution marketing and data for volatile times. As we get started, we'll have just a few housekeeping notes. First, this discussion will be 30 minutes. We're going to try to use this time the best we can. This webinar will be recorded, and we'll send it out within a week. So if you have to hop or something, you can see the rest of it. And we'll reserve some time at the end for your questions. So throughout the discussion, if you have a question or a comment, you can use that Q&A box on the side to share any questions. We'll make sure to reserve 5 minutes. Okay. With that, we'll get started. Thank you for joining us. I'm Madeline Ross, and I'm VP of Marketing at Enigma. At Enigma, we provide data about the identity and financial health of every U.S. business. We reunite data from hundreds of different sources so that we can provide a clear picture of the business and its operations. And we partner with financial institutions and organizations like Deluxe to help them find and engage at small businesses as well as mitigate risk. Today, I'm joined here by Elissa Rodd, who leads the Product Strategy and Innovation Group for Deluxe's Data-Driven Marketing. Elissa is an analytic specialist who focuses on the development and implementation of targeted marketing campaigns. She's also the gatekeeper for all of the Data-Driven Marketing group's data assets, sourcing, evaluating and assessing all of the firm's third-party data.

Elissa, could you tell us a little bit more to start about Deluxe and the Data-Driven Marketing group there?

Sure. First of all, thanks for having me. But yes, I am part of Deluxe's Data-Driven Marketing organization, also known as DDM. And we are a full-service data analytics and marketing services firm, focused predominantly on the financial services industry, although we support all industries and verticals as well. While I'm here to talk more of the data side of the house, our teams do everything from campaign strategy to creative design and development, campaign production and deployment and all the way to performance tracking and optimization. Our mission is really to create elevated marketing programs for our customers that provide them exceptional returns on their investment.

Fantastic. Well, so excited to have you here today because I think so many people have questions about how to best use their data in marketing, how to really get those results that you and your team focus on all the time. And so I'd love to start with just kind of thinking about what data-driven means today. So in marketing, we talk a lot about the importance of relying on data for making good decisions, but at the same time, the landscape is constantly changing in terms of what data is available and in terms of what we can measure. So just starting with that at Deluxe, what does it mean to be data-driven in your marketing work for clients?

Yes. So that's -- it's a great question, and it's one I love. I mean, because I do think the industry uses it very loosely as a buzzword. I mean, our group is named data-driven as well. But I truly believe we are data-driven. To us, it really means that every decision that you make, every single marketing decision is rooted in and based in data and analytics. And when I say everything, I mean everything. For us, it means the creatives you're designing, right, the imagery, the photos you're using, the copy, the call to action. If you're doing telemarketing, right, what you're writing in the script when you're talking to people, the data that you're using, how you're targeting, how you're building models and then how you interpret the results that you get at the end of the campaign and bring that full circle. Coming from the data space, I like to joke that even our data is data-driven. But it's true. I mean, what we're doing every day is every data that we bring in, there's tons of data out there. I'm not bringing in every data set to work with. We're testing it. We're vetting it. We're watching it perform in the marketplace. And then we're deciding what works and what doesn't based on actual data points that we can call out to you. We can say, we did this decision because of this data point.

I love that. And I would love to drill just a little bit deeper there. Kind of you mentioned you're working with all of these different types of data. What kinds of data do you work with most when you're marketing to SMBs and to small businesses in particular?

Yes. That's a good question. So I think just to take a step back, the marketplace for business data is really fascinating because it's really spread out. I work with both business data and consumer data. And I find business data is a lot more challenging to work with for a few reasons, but mainly that one, right? There's just -- there's no one big data partner that you think of. There's so much data everywhere. But I think the data that we work with a lot is twofold. One, it's really strong foundational data. And second, it's really unique specialty data. So when I say foundational data, I mean the types of data that really get a marketing program off the ground, right? You need business name, and you need contact information. You need e-mails and phone numbers and addresses to target to, right? That's what really launches an offline or online program. But what I think makes marketing programs really pop is when you bring in really unique specialty data. And I think that's where Enigma plays really well and why we've loved our partnership with you because you need that base, but you really need to be able to make smart decisions. And so we're bringing in a ton of different data from different partnerships. And I'd like to highlight Enigma because we've started working with you guys for about a year now. And by being really strategic with your data, we have found that our response rates and our return on investment have increased by 1.5x, right? We're not using your data in every campaign we run, but in the ones that we do and we're strategic, we're seeing really huge lift. And I think that's so important because specialty data adds another layer to your marketing. One, it can sometimes add things like coverage, right? Enigma's found us businesses that we've never seen before, and that's huge in marketing. Coverage is key. Saturation is a big part of marketing response. So when we're talking to businesses who haven't been targeted 20 times already, right, they're getting our mail piece for the first time or our phone call, that can be a difference in their marketing response. And then the second thing is we have really unique attributes. You guys provide us features and timing components that really help us hone in on finding the right partners. So a lot of our data is foundational, but the really interesting parts of what we do is working with specialty partners.

That's great to hear. I definitely appreciate those -- great to hear the results that you're seeing there. As you're looking at data, whether it's foundational or specialty data sources like Enigma that are providing revenue or particular aspects of a small business, how do you evaluate the quality of the data source and whether you think it will have value for your clients?

Yes. So I'm going to be a broken record this entire webinar, but it's data-driven, right? But it's a multi-stop process. I think at the start, there are a few metrics that we look at. The first one is coverage. Again, we just talked about that, but coverage is key. I think there's an added component with coverage, though, in which sometimes I'll evaluate a data source and I'll see businesses I've never seen before, and that's super exciting, but we always validate what we're seeing. So it may be a timing issue that the businesses that are -- I have seen in this data source appear new, but they're actually bankrupt or out of business. So that data is not useful to me, right? That incremental coverage is actually a sign that the data is stale or old. So that's the second thing we look at is data quality, right? We have truth files that we use, so we can compare the data to what we know to be true to validate how accurate it is, how fresh it is. The third thing that we do is we beta test everything. So we'll take the data, and we'll bump it up against the campaign that we've already run. And we'll see how does the data -- if we had this data in-house, how would it have done? Would it have popped in our models? Would it have led us to predict and find more responders? Sometimes we find when we back test that the unique attributes don't pop in their models, right, or they're highly correlated with what I already have. So they're not adding any incremental value. And then the last thing that we do is we test everything in the marketplace. We highly recommend beta testing, everything live, right? That's where you get the key performance metrics you want. We often go out with small test cells that are measurable so that we can say yes, it's working or no, it's not. And if it does work, then we'll onboard it, and then we watch it over time. We don't -- we're not satisfied that the first time it works was great, right, we, over time, will continue to evaluate it to make sure it's performing to our standards.

I love that. And it's so helpful to you to hear -- unpack. I think data-driven sounds like such a simple, snappy term and all of the different work and amount of analysis that has to go into being truly data-driven. Another question for you. What do you think are some common misconceptions about using third-party data for B2B and marketing?

Yes. I would start with that all data is created equal. That is not true. I talk to data partners all day long, and I can tell you that they all tell me they have the best data, right? It's not true. We test. So testing, testing, testing, testing, validate what you have, have a truth file. Just because someone says they have the best data, validate it yourself. That's the best way to tell that data really is performing to the metrics you want it to. The second thing that I would say is core entity resolution, that's super important in this space. It is really hard to [indiscernible] resolution with businesses, often because businesses will have so many names that they operate under, right? I might have a flower shop, and my legal entity name is Elissa Rodd LLC. My storefront says Elissa's Perfect Petals and my business banking checking account says Elissa Rodd. Now we can know as humans that those all probably sound similar and connected. But when you're doing that with tens and millions of rows, it's really hard to make those connections, and often those fall through the cracks. So we often find that people feel like the data, they don't get good at pen rates or they think campaign performance is worse than it is because they're not making those connections. So having a really great entity resolution or having a partner who can do it for you, I think, is key. The third thing I would say and these kind of tie 1 and 2 together is we often hear, I've tried this before, it didn't work. I hear you. But not all betas created equal, and entity resolution can help show you or better entity resolution can show that the data set is working. I try everything. And I never really let anything go. So it may be that I tried something in 2022, and it didn't work. I will sit on it for a year, and then I'm going to come back to it because it didn't work in 2022, but maybe it works in 2023. Maybe something changed. Maybe the market changed. Maybe my data partner changed their algorithm or how they're collecting data. Things change. So I always recommend not trying to fall back on I tried it before, and it didn't work. And the last thing I would say is that you don't need a massive amount of data. We need a massive amount of data. Enigma needs a massive amount of data. Data partners need a massive amount of data. But I think what marketers need is a massive amount of the right data. Having the wrong data is not helpful. If you have data in-house that's not predictive, if it's not getting you what you need, then that's not helpful. It doesn't matter if you have all the attributes. If you don't have the right attributes, it's not going to work. And so really focusing on finding the right data that leads to the right results.

I think those are all fantastic points. And I especially love that you called out entity resolution, which I think is something that gets overlooked very often and feeds directly into those points you were talking about earlier coverage, accuracy. All of those things are really entity resolution is the underpinning underneath that, that's making all those possible. For -- to your last point, marketers just need the right data used in the right way, for organizations that are looking to better use data who are maybe earlier on this journey than Deluxe is, how would you recommend they start to build a solid foundation?

Yes. Well, we've talked a lot about third-party data so far. But I would focus, first and foremost, on your first-party data. That is your bread and butter. Sometimes I'm surprised that the data companies aren't collecting on their customers. There's always a fine line between collecting data and annoying your customers, right? If you're checking out online for a tube of toothpaste and the company asked you for your income, do you like dogs, are you married, do you have kids, did you just buy a house, right, all those questions, you're probably not going to check out. So there's a fine line. But I do think that every opportunity that you have to work with your customer, you should bring in 1 or 2 data points just to continue to build that rich profile and also try and find all the transactional data that you have to try and build that foundation because having great first-party data is huge. It helps enhance what third-party data can do and also can help you build really great models and know your customers better. But in terms of third-party data, I really think it's testing. I think some organizations we get bogged down in our tech stack or we've worked with this data partner for 20 years. They're the best data partner we have or we don't feel like finding someone new, right? I think it's testing, right? Everything we do is testing. You put it in the marketplace, you see if the data works. But you just talk to a lot of data partners, and you see what they have to offer. And you test and then based on testing, you onboard those that are really working for your unique problems.

Makes a lot of sense. I know we're at the halfway point, so I'm going to kind of keep us moving. And related to actually something you were saying earlier about the fact that you keep trying things because 2023 is different than 2022, something could have changed. And I think that's so true for all of us who are in marketing and that the marketing landscape is constantly evolving. And FIs are also having to evolve in order to stay relevant. What is one trend you're seeing in how marketing programs are thinking about leveraging data to try to stay relevant with their B2B marketing efforts in particular?

Yes. I think there's a growing importance and sort of expectation on timing and personalization. I think customers want to be known, right? They know we have all this data on them. They want to be known. I think COVID, if you think back to 2020, it was a hard year for businesses, right? And I think a lot of businesses felt burn by the PPP program, the ups and downs of that. They felt like their suppliers and partners that they work with maybe weren't understanding them. And so I think there's been a really big focus on using data to better personalize the marketing experience and also making sure that you are really timing your outreach and pivoting your outreach as things change, right? Not being inflexible that you always have to go out with this creative or this targeting profile, right? But being adaptable and really trying to talk to businesses with messaging that really resonates.