Industry leaders are constantly searching for new business prospects in order to maintain their leadership role. To accomplish this, they often look for partners that can help them more efficiently and effectively interact with potential customers. One global company, headquartered in the Midwest, serves as that type of trusted partner, acquiring prospects for its clients via telemarketing and offering solutions that enhance bottom-line performance.
This leading company's customer acquisition campaigns typically include millions of customer contacts spread over many months, and involve hundreds of sales agents. The prospect contact lists are traditionally drawn from population databases, and are supplied either by the client or the company itself. Given the scope of this effort, approaching prospects through a haphazard series of random calls was clearly inefficient.
The company's sales force used SPSS Inc.'s data mining tool, PASW Modeler, to segment and score each list, enabling them to call only those prospects that would most likely purchase products. In addition, the company was able to assign its best sales agents to the strongest leads and to schedule the contacts at an optimal time, resulting in an increase in prospect acquisition success rates.
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Market leaders in countless industries, from financial services and insurance to telecommunications and healthcare, often need assistance in uncovering potential customers. In order to efficiently make contact with important consumer audiences, organizations look for partners with specialized knowledge and expertise in telemarketing. One such Midwestern company serves as that skilled, trusted partner, with blue chip clients relying on it to manage and maintain all aspects of their acquisition programs.
To provide clients with the best opportunity for success, the company uses advanced data-modeling techniques to identify prospects with the highest propensity to purchase a particular product. The next step is to closely match these prospects with the best-suited phone agents and schedule the contact for the most appropriate time. The use of data modeling to refine these processes has resulted in higher acquisition rates at reduced costs, and higher long-term profitability for clients.
The company uses PASW Modeler to build customer profiles and identify which individuals are most likely to purchase their clients' products or services. Then, PASW Modeler generates both the statistical models that drive execution as well as the reports that outline performance forecasts and operational results.
Prior to PASW Modeler, the company's data analytics team received monthly or bi-monthly lists from clients with as many as one million leads per list. When the month was over, the old list was abandoned and a new one was started. This system was ineffective for both the company and its clients because they had no idea which contacts were the best leads.
In mid-2001, the company's data analytics team purchased PASW Modeler from SPSS Inc. They did so for several reasons: 1) PASW Modeler's premier statistical and modeling functionality surpassed competitors, 2) PASW Modeler's graphical programming desktop provided maintainable and transferable production solutions, and 3) PASW Modeler's intuitive implementation allowed the company to staff with business analysts rather than specialized programmers.
Sales agents are ranked "A," "B," or "C" according to that agent's close rates. To make sure sales leads are effectively utilized, the best agents (A-level) concentrate on calling individuals that are most likely to purchase a product. The team's reasoning is that if a great lead is given to a beginner agent and he or she doesn't close the sale, that lead was wasted.
The data analytics group uses PASW Modeler to score potential customers on a scale from zero to 100 based on propensity to purchase. Sales representatives then call only the top 60 to 80 percent of the list. That strategy can increase sales per hour [SPH] by as much as 30 percent.
Improving SPH has helped the company rise above its competitors. Many clients will use several vendors for prospect acquisition services, but tend to invest more with the top vendor. PASW Modeler helped the company increase SPH, giving it the boost it needed to become the top-rated vendor for a number of clients. The result was more lists and increased revenue.
In addition to generating more revenue, the company's ability to identify the best leads offered clients substantial savings. Before PASW Modeler, clients had to purchase entire lists because they couldn't identify which individuals were most likely to convert to customers.
With PASW Modeler, clients can selectively purchase the names that have the highest scores. For example, the company may only buy the top 60 percent of 1 million potential buyers based on PASW Modeler scores. This translates into immediate savings for the company's clients.
PASW Modeler has not only helped improve the bottom line, but also spurred internal and external operations improvements. The ability to report and measure campaign success, as well as uncover reasons for failure, drove change throughout the organization. In fact, implementing the process of calling best leads first was a major change in company procedure.
Within the company, the data analytics group meets with the CEO and executive committee bi-weekly to present progress reports on all ongoing acquisition programs. By using PASW Modeler to help gauge their effectiveness, they can develop appropriate strategies to ensure programs stay on track.
Currently, all weekly reports, which contain PASW Modeler produced graphics and tables, are available on the company's intranet. These reports allow the company to re-segment leads more often and re-evaluate penetration strategies to make sure sales agents are continually calling the best leads.
While cold calling is a part of doing business for most companies, thanks to PASW Modeler, this organization is helping its customers form new relationships by following up on only the hottest leads.
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