Optimize Sales with Predictive Analytics

How Predictive Analytics Can Get Your Sales Reps Through the Right Door

Looking to predictive analytics to identify and connect with prospective customers

Sales and marketing organizations increasingly find it difficult to identify and connect with prospective customers. Identification requires understanding the specific needs of prospective customers and determining who has the actual authority to make a purchase. Connection requires delivering targeted sales and marketing messages at the right time for those customers to make the purchase.

These are all areas where companies are turning to predictive analytics to optimize selling strategies and marketing plans and gain greater customer engagement and loyalty.

Addressing today’s sales and marketing challenges

The sales and marketing challenges companies face today can be summed up as follows: “Salespeople are investing their time poring through a heap of possibilities to find the good ones. If sales is [looking for] a needle in a haystack, analytics can make the haystack a whole lot smaller,” according to Eric Siegel, author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

To be more effective, sales and marketing efforts need to pinpoint the sites where purchasing decisions are most likely being made. These same efforts need to help sales teams focus resources on the optimal locations of customers and prospects and help them precisely and smartly allocate marketing dollars on the right audience with the right message at the right time.

To tackle these tasks, businesses need a solution that considers linkages within family trees of an enterprise and business activities at each site to identify locations with buying-decision authority. This type of information can then be used to create a “decision-making power score.” The score should be based on:

  • information about a firm, including physical size, financial size, line of business
  • inquiry information, including industry inquiries and batch match audits
  • data that identifies the presence of C-level executives in various locations and sites
  • corporate linkage information that highlights influence over subordinates, branches, and subsidiaries and influence from superior business entities.

Scoring companies in this manner helps businesses shorten the sales cycle, by pinpointing sites where purchasing decisions are most likely being made, and helps sellers focus resources on the optimal locations of their customers and prospects – so they can spend more time selling and less time conducting research and making calls to the wrong offices. The result is that sales leaders benefit from more intelligent account assignment and sales territory planning.

By reducing the number of sites requiring an interaction, this approach improves sales and marketing effectiveness and enables the sales teams to capture a larger percent of potential sales and revenues.

Use cases abound

The business intelligence derived using this predictive method – which identifies where buying decisions are made and by which people – can be applied to many functional areas and operational processes. Some examples of what can be done include:

Opportunity qualification: BANT (Budget, Authority, Need, and Timeline) is a selling qualification practice solution that has been deployed in many advanced sales organizations. Understanding if an opportunity is truly qualified and that a salesperson is speaking with the decision maker can make or break a sale.

Pre-qualifying the authority of an individual or group to make decisions will help a salesperson understand if they need to move up the corporate hierarchy to gain approval and support for a sale.

This lets salespeople know whether they are engaged with the actual decision maker and, if not, where and how far away a decision maker is relative to the current engagement. This can help salespeople prospect more effectively.

Whitespace capture: Identifying incremental opportunity and under-served divisions of the largest customers can help realize the true potential of the relationship.

This helps identify buying authorities in divisions, subsidiaries, and departments in existing accounts that are under-penetrated and under-engaged.

Assessing procurement style: The way a company makes its major purchasing decisions affects how a seller manages and engages the account. Having too many reps on an account costs money and wastes resources. Conversely, having too few reps engaged provides less than optimal support and leaves money on the table.

This assessment helps sellers understand the procurement strategy a company employs, and allows them to align resources to capture demand.

Wallet-share calculation: Understanding the share of wallet a seller has with a customer informs go-to market strategies, determines resource allocation, pinpoints cross-sell and up-sell strategies, and allocates investment in customer acquisition. Arriving at an accurate understanding of contestable wallet share is getting even more difficult due to shifting of budgets.

The information that gives you the “decision-making power score,” coupled with other analytics-infused data elements, allows a seller to understand the intricacies of where budgets are allocated within large family trees, giving a more detailed view of how a company allocates and spends its budgets.

Optimizing your sales efforts requires a global solution that considers linkages within family trees of an enterprise and business activities at each site in order to identify locations with buying-decision authority. For more information about this approach using D&B’s Decision HQ model and other advanced analytic solutions, visit: http://www.dnb.com/analytics