Using Data and Analytics to Enhance Account and Prospect Segmentation
At Dun & Bradstreet, we understand that sound business decisions begin with sound information. Guided by this philosophy, we’ve helped our customers and partners build the most valuable relationships by uncovering truth and meaning from data. With the most comprehensive and accurate repository of business data on the planet, we believed it was time to put it to work for ourselves as a way to internally identify and connect our sales team with the most valuable relationships.
Modernize and streamline our sales account and prospect segmentation through data and analytics – our very own data and analytics. We wanted to recommend relevant, high-value customers for sales to call on based on real-time insights and move away from categories like spend as the primary segmentation attribute. Analysis indicated that Dun & Bradstreet had been overlooking valuable sales opportunities with high-value customers because its resources were not matched with customer complexity and needs. By consolidating resources, prioritizing customer needs over internal measures such as spend and shifting accounts to the appropriate sales model, the expectation was to foster an environment for sales to grow, nurture and retain customers.
Historically, Dun & Bradstreet’s sales mindset was driven by an inside-out approach – allocating our resources to clients based on customer spend and broadly targeting what we determined to be the “best” prospects. To better serve customers and prospects, the team would need to modify its segmentation methodology and institute a more outside-in, data-inspired approach. The new account segmentation policy (ASP) would be built with more advanced insights such as opportunity, risk and complexity of need to help sales appropriately allocate resources to customer need. Finally, some customers were being served by multiple sales reps, with different points of their organization (family tree) assigned to various channels. This resulted in a sub-optimal customer experience and duplication of efforts. The new ASP would examine the entire relationship and consolidate ownership to optimize the customer experience.
Dun & Bradstreet’s customer analytics team recognized the opportunity to enhance its account segmentation policy based on external best practices and emerging data and analytics capabilities. With a full understanding of the limitations inherent in the existing segmentation process and embracing the newly launched corporate value of an outside-in mindset, sales leaders sought a more data-driven customer-centric approach to account allocation. Dun & Bradstreet’s customer analytics team led the charge, combining art and science to establish a data-driven, analytic approach that was optimized by leveraging sales intelligence and put into practice through a partnership with sales operations. The new segmentation plan was developed using Dun & Bradstreet’s proprietary data and firmographic information as well as applying advanced analytic techniques to identify the right set of criteria for each account, leveraging:
- Customer-centric data such as company size and industry metrics (e.g. growth/decline)
- Predictive models that measure proclivity to purchase Dun & Bradstreet solutions
- Attrition risk models developed by Dun & Bradstreet for its customers and solutions
- Historical factors such as renewals, payment history and complexity of purchase
The new approach would re-segment accounts within the three existing sales channels (Strategic Vertical Accounts, National Accounts and Inside Sales) to map our “best” customers / prospects with our “best” Sales Executives and to take advantage of team-based selling. This meant rebalancing portfolios and reprioritizing accounts. To mitigate any potential customer or internal disruption caused by account reassignment, the sales, sales operations and service teams were involved in every step of the process. It was critical to integrate their feedback, address concerns and devise resolutions to conflicts before they became obstacles to smooth customer transition.
Account Segmentation Policy ("ASP") For New Tiers
Game Changer: Analytics
In the segmentation game, the gold standard is to create segments of one – companies being flexible enough to meet each customer’s needs in custom ways. Pandora is a great example of this. While segments of one are difficult to achieve in a direct sales model, analytics, including anticipatory analytics, is the lynchpin to creating successful outcomes. Strong analytics facilitate firms in grouping customers with similar needs into sales and service models that best serve their needs, leading to increased opportunities for cross-sell, upsell and superior retention and customer satisfaction. Beyond purchase behavior and firmographic indicators, the predictive analytical ingredients used for Dun & Bradstreet’s segmentation were:
- Propensity models, which predict the likelihood of a customer or prospect to purchase Dun & Bradstreet products and services. These use firmographics, purchasing behavior and other predictive variables and are tailored for Dun & Bradstreet’s line of products.
- Attrition risk models predict the likelihood of a customer to attrite from a product and these use some of the same indicators as are used in propensity models.
Given the length of any enterprise sales cycle, it is still early to determine the long-term revenue impact of the segmentation. However, we have seen early signs of an increased pipeline indicating a majority of the upward moves are having the desired impact in terms of either shifting or increasing the account trajectory.
- Overall, accounts that moved up-channel, National Accounts to Strategic and Inside Sales to National Accounts, as well as those that moved from Verticals down to National Accounts (low sample) look relatively healthy. There is no indication that we should discontinue aligning accounts based on this segmentation.
- The growth rate of the accounts moved from Inside Sales to Strategic slowed, but outpaced the negative growth of the non-transfers.
Thus far, the response has been very positive, with the sales team feeling more empowered to focus their time on addressing the highest opportunity customers. Customers themselves are getting the service and attention they deserve. The marketing and sales teams are more precisely enabled by an analytically prioritized prospect target list, making them more efficient in allocating resources and launching programs with ranked targeting. Moving forward, Dun & Bradstreet will continue to assess market conditions and evaluate new data and analytic capabilities. The goal is to further enhance the new account segmentation policy and drive our modern go-to-market sales and marketing strategy.