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Client: A $50 million/year national distributor of telecommunications equipment and telephone system components. |
Challenges: Based upon the number of their customers, our client was selling to nearly every company in their target segments. Based upon revenues, however, they knew that they were not selling nearly as much as their competitors seemed to be. The challenge was to know which of their established customers might potentially buy a lot more.
Solution: We developed a specialized "share of spend" database by combining data extracted from our client's mainframe systems and with data purchased from a major B-to-B list compiler. Next, we used predictive analysis tools to segment our client's customers. We then developed an analysis procedure that compared the "segment profile" to the purchases of each customer in the segment with a special analytical technique.
Result: Our client spotted the customers that appeared to be buying mostly from other vendors. Contacting these customers with negotiated "bundle offers" encouraged the customers to spend more with our client in preference to other vendors.
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