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Acquiring New Customers with the Help of Predictive Analytics

Why Precision Matters

The appeal of acquiring new customers is high, but it is also very costly. During my time at Dun & Bradstreet, our focus on new customer or "new logo" acquisition has changed at least several times. I consider this a very good thing, as we are constantly reevaluating our market opportunities, which change as we launch new products, enter new lines of business, and acquire other companies.

There was a time at Dun & Bradstreet when we were highly focused on bringing in new companies across all sizes and segments that were not doing business with us. This was followed by a time when we focused mainly on deeper penetration of and cross-selling within our existing base. We have now landed somewhere in the middle, and I believe this is exactly where we should be.

Customer Facts

I realized that my Analytics, Insights & Operations team had an opportunity to be even more precise in our recommendations to drive our strategy.
 

Let’s start with a fact – Dun & Bradstreet’s customers include 90% of the Fortune 500. Let’s add a second fact – most Dun & Bradstreet customers buy us in one line of business (example Sales & Marketing). For more fun, let’s add another – we have seen the largest momentum in new logo acquisition with micro and small businesses. So as the question of new logo opportunities resurfaced, I realized that my Analytics, Insights & Operations team had an opportunity to be even more precise in our recommendations to drive our strategy.

 

Growth Opportunities With Customer Segments

As I’ve discussed in my previous articles, my team uses both propensity models and demand estimators to identify growth opportunities – new logo, cross-sell, and upsell. However, we tend to use these analytics on an account- or company-level instead of in aggregate. With an opportunity to influence future strategy in our hands, we aligned on a customer segmentation methodology to quantify growth opportunity by (1) type of growth (cross-sell, upsell, new logo), (2) line of business, and (3) sales channel.

What became crystal clear was that the biggest opportunity in new logo continued to be in micro and small company segments.”
 

The beauty of this aggregated view is that it provided clear direction in terms of the opportunity for growth within our existing customer base versus new logo. What became crystal clear was that the biggest opportunity in new logo continued to be in micro and small company segments. We also validated that our Credibility suite of products was typically the best credit and risk entry solution for these companies. Micro and small businesses tend to focus on building their own business credit first, using Dun & Bradstreet’s Credibility products. The need for risk management solutions typically comes later as their suppliers/partners and customer base expand. This was the perfect opportunity to become more precise in our Credibility outbound-marketing approach.

 

Our Predictive Analytics team built a Credibility model and partnered with our Demand Generation team to test the model using an integrated marketing campaign of direct mail, email, and outbound telemarketing. A test plan was created to measure the performance of the model and compare the results to the legacy segmentation methodology.

“It was great partnering with our Demand Generation team to understand the current approach to targeting and segmentation and identify how we could leverage our multivariate modeling capabilities to improve conversion rate,” says Burt Stillwaggon, Director of Predictive Analytics.

Customer Acquisition Strategies

As we studied the campaign and test performance, we were thrilled to see that the results for the model showed a 52% higher conversion rate of lead to sale versus the legacy method! This was coupled with steady Average Selling Price (ASP) despite product portfolio changes and higher ROI for the integrated campaign overall. This proved that the propensity model could in fact identify the need for our Credibility solutions.

There was no question that the model outperformed the legacy approach and delivered more precision in identifying and prioritizing the best targets and prospects. With the direct mail component being costly, it is critical that we find the best universe in order to deliver the maximum ROI.

Predictive Customer Analytics Is a Win-Win

“The implementation of the Credibility propensity model in Acquisition marketing has been a game changer for the way we use data to improve conversion while keeping spend the same. Through our partnership with Predictive Analytics, we were able to develop a model to benefit our own demand generation efforts and get it in-market for the first time. Our teamwork shows that we can work together to leverage data and analytics capabilities that we provide to Dun & Bradstreet customers for ourselves and lean in on each other’s expertise to get in-market quickly and improve campaign performance,” says Bernice Brennan, Director, Demand Generation.

This was a double-win for us. Not only were we able to solidify our best new logo opportunity among micro and small businesses using predictive customer analytics, we were able to build an ongoing targeting approach for our Credibility direct mail campaigns that maximizes ROI. As I always say, best-in-class analytics, targeted applications, and relationships are the three key ingredients to successful business outcomes. This time, I will add test-and-learns to that mix. It is super critical to be able to test an analytic approach in-market with a sound measurement plan. This gave all of us the confidence to shift to an analytic-driven approach to generate our target lists for direct marketing campaigns. Next up, we are testing the model for other types of marketing campaigns. Stay tuned!

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