Case Study
Predictive Analytics Reveals Growth Opportunities

Using predictive analytics, this technology company was able to identify 400 accounts primed for growth

Customer strategists focus on what has already happened to determine their next moves. They listen to customers and devise strategies to make improvements. But, there are more proactive ways to better anticipate customer needs.

A large technology company's B-to-B sales division wanted to understand factors resulting in new product sales, and develop predictive profiles to target future sales opportunities.

Walker worked with the company to understand the business issues they wanted to address, and help increase sales of new products to drive their company’s long-term growth. To accomplish this Walker designed an analytic approach to understand the key differentiators between accounts with a sale and those without a sale and to identify accounts to target in the sales process. The outcomes of this program include a profile of customers most likely to purchase the products, identification of areas of focus to increase the probability of a sale, and a list of accounts to target first for a new sale.

Instead of relying solely on surveys to gather the data needed, Walker combined information from 18 datasets with data over a 4-year timeframe, 17 of which were comprised of non-survey data. Many detailed and sophisticated analyses were performed to discover the customer profile most likely to result in a substantial win. To move from general profiles to specific targets, Walker followed the three-step process below:

Step 1: Profile

The team identified the key inputs determining whether accounts are substantial wins or no-wins.

Step 2: Predict

Walker built an algorithm to identify accounts that a) don’t have a win, but b) the algorithm predicted should have a win. These accounts fit the profile of those with a successful sale of the product, so they are most pre-disposed to needing or wanting the product.

Step 3: Target

Walker delivered a list of 400 accounts that the company should target, and a set of recommended improvements that would generate a better hit rate.

By using predictive analytics to develop profiles based on behavioral data, attitudes, and perceptions the company was able to not only identify 400 major accounts that were likely to buy their product, but also identify a set of items that if improved, would create a greater likelihood of sales. Going forward, the sales teams are continuing to review the identified accounts and develop plans and strategies to drive more sales, as well as monitor the conversions as a measure of success.