D&B CMO Rishi Dave Credits Data For Great Customer Experiences

From account-based marketing to programmatic buying to predictive analytics, the B2B marketing landscape will continue its shift in 2017, according to Rishi Dave, CMO of Dun & Bradstreet.

From account-based marketing to programmatic buying to predictive analytics, the B2B marketing landscape will continue its shift in 2017, according to Rishi Dave, CMO of Dun & Bradstreet.

“Companies are increasingly understanding who they want to target, and they’re leveraging deterministic data—meaning, validated data on the actual companies they want to target—to make sure that they find them online,” he explained during an exclusive interview with CMO.com.

Read on for the rest of our conversation.

CMO.com: A lot of B2B marketers are starting to move their capabilities and platforms in-house. Can you talk a little bit about that and why it’s happening?

Dave: With the ability to connect first- and third-party data, bring that data into your enterprise, and build analytics on that data internally, companies increasingly have a strong understanding of their customers and the opportunity. More and more, they’re learning to leverage that to execute some of these functions internally versus opting for third parties.

CMO.com: What are the implications for advertising agencies?

Dave: I don’t think advertising agencies go away. I mean, there’ll be a lot of companies that will want to continue to use them to buy, and there’ll be a lot of companies that will want to bring it in-house; it just depends on the strategy and direction you’re going. But what we’re already seeing is agencies that leverage a lot of the modern mar-tech stack and technologies to manage advertising and buying.

CMO.com: Where are B2B marketers in terms of their use of programmatic advertising tactics?

Dave: The past year, especially, has been a defining time for B2B’s adoption of programmatic ad buying; nearly two-thirds of B2B marketers are using programmatic. Following B2C’s lead, B2B companies have become more knowledgeable about data-driven targeting, and programmatic has moved further into the marketing mainstream with tools capable of delivering the kinds of lead-generation and content-focused campaigns that are essential to B2B success.

CMO.com: Why do you think there’s an increase in B2B programmatic spending? And how will it continue to grow?

Dave: There’s been a large move among B2B marketers to more of an account-based marketing model, which is very different from the traditional model of broad-based lead gen where you cast a wide net.

B2B companies, especially those that focus on mid- to large-size customers and do large deals, are shifting to targeted account-based marketing, which requires leveraging data and analytics based on a clean and complete view of their customers across the enterprise.

They’re leveraging analytics to do two things. One is to prioritize the opportunities that they, as marketers and the sales team, should be going after and then creating experiences against the highest value opportunities. And that’s where programmatic buying really comes in, and why I believe it’s really on the uptick.

CMO.com: How is Dun & Bradstreet applying account-based marketing to its own marketing efforts?

Dave: First, we really modernized our brand, our purpose, and our values so that our company knew exactly why we existed, what differentiated us, and who we needed to target. We then defined a go-to-market strategy linked to that purpose around the specific people within companies we felt were the biggest opportunities for us going forward.

Then once we identified our persona-based approach, we invested in account-based marketing to say, “OK, given that we know the personas that we’re targeting, which are the best opportunities for our sales and our marketing team to focus efforts?” And that’s where we really leveraged data and analytics. We actually drank our own champagne.

So, first and foremost, we made sure that we had an integrated mastered data set, so we had a full view of our target customers. Then we built analytics on top of that, different types of analytics, but really it’s about propensity modeling—leveraging the real-time data as well as the historical data to determine which targets provide the biggest opportunities for us going forward in these different departments. In some cases, it may be existing accounts where we already have a presence. In many cases, it’s new accounts where we don’t yet have a relationship.

Based on our propensity modeling, as well as our lookalike modeling—where lookalike modeling is really looking at customers that are similar to ones where we have had success—we identified opportunities. And, obviously, as I mentioned earlier, we’re investing in architecting the right experience against high-priority accounts.

CMO.com: What exactly is predictive targeting?

Dave: We call it anticipatory, but it is really the next-generation version of predictive analytics. As companies and B2B marketers, in general, we’ve typically built our customer models on historical data. We said, “Hey, we ran a campaign against this historical data set. Here’s the response that we got. Let’s apply that same model to this next set of potential opportunities that we have and predict how they’ll respond, and then target our marketing program that way.”

That’s changing quite a bit because of the speeds at which we can process data and because of just the sheer availability of data. What you’re able to do now is get much more predictive on opportunities. Today you can see all the data in real time and build indicators of where your target is going, and you can use changes in those indicators in almost real time to target your marketing programs.

That’s what we use to determine what accounts provide the biggest opportunities. It’s not always based on the history; it’s based on where we believe they’re going, based on what’s happening to them in real time.

CMO.com: Companies have focused a lot on collecting data, but what needs to happen in order for them to be able to actually glean insights from the data?

Dave: Your ability to create great experiences across all the touch points you have with customers is really based on how strong your data set is. Companies need to both take the first-party data that they’re generating and marry that with third-party data to have a differentiated data set.

The key is to then use that data set across technologies to create great end-to-end experiences. Building really good analytics on top of it is the big mountain that marketers are trying to figure out now. That’s the focus going forward because once you are able to do that, then you have a differential data set that you can use to create unique experiences that your competitors can’t offer.

And as you get real-time data, if you’re able to adjust on the fly, that gives you a real competitive advantage.