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SPSS helps transform inbound call centers into profit centers with launch of PredictiveCallCenter™
Source: www.spss.com
Copyright SPSS, Inc. 2004
06/07/04

This is a dated announcement. The material in this announcement could be superceded by more current announcements.

PredictiveCallCenter offers real-time predictive analytics to provide personalized recommendations at each customer contact

CHICAGO, 05/17/04 — With the advent of the do-not-call list and other opt out regulations, the inbound call center is no longer looked upon as strictly a service channel, but as a critical customer interface and viable sales channel. To help call centers transition from a cost center to a profit center, SPSS Inc. (NASDAQ: SPSSE) is launching PredictiveCallCenter™, an application that integrates with call center CRM and call management systems to instantly determine which inbound callers are good candidates for up-sell, cross-sell or retention offers. PredictiveCallCenter, which is available now, is based on proven real-time predictive technology from DataDistilleries, a Netherlands-based company SPSS acquired last November.

“The backlash against unsolicited telemarketing, together with increasing competition and the need for more precise, efficient marketing has placed a renewed emphasis on maximizing inbound contacts with customers,” said Bill Vance, a call center industry veteran of more than 15 years and vice president of customer acquisition at Upper Quadrant, a marketing effectiveness company based in Reston, Va. “Predictive analytics can help inbound sales and customer service call centers shift from per-call efficiency to a call-effectiveness culture, which may reduce the need to outsource in many cases. An application like PredictiveCallCenter will arm service agents with all the customer information they need to make the right offer, to the right person, at the right time.”

PredictiveCallCenter analyzes each inbound call and combines this information with the customer's historical and transactional data from other channels. It then evaluates potential cross-sell and retention offers against this analysis, and uses predictive analytics and business rules to select the offer that is most likely to both be accepted by the customer and generate the highest value for the company. This offer, together with sales guidance, is displayed on the agent's desktop.

Using a proven combination of predictive analytics, business rules and real-time technology, PredictiveCallCenter achieves high levels of recommendation accuracy and can increase cross-sell and up-sell hit rates by 50 percent or more. Predictive analytics accurately anticipate the needs, preferences and attrition risks of the individual customers. Business rules enable organizations to incorporate their own marketing expertise when selecting target groups for offers, and to adhere to externally and internally imposed restrictions such as do-not-call and opt-out lists. The real-time capabilities of the application provide recommendations that are based on the most up-to-date customer data available, including information received during the call or from other channels and back office systems. This ensures that each offer takes into account last minute changes in customer behavior or needs.

Ronald Oudendijk, head of customer intelligence at ING Retail, part of ING Group, a global financial institution headquartered in the Netherlands, uses SPSS predictive analytic technology to successfully optimize customer relationships. “Now, thanks to PredictiveCallCenter, we plan to increase the value we already derive from our existing call center by making our clients offers that fully match their individual needs and wishes at that particular moment. We expect that using real-time scoring will lead to a considerable improvement in our sales results from telephone contact with our customers,” said Oudendijk.

PredictiveCallCenter readily integrates with existing call center systems to provide complete, automated recommendations and support without the need for additional databases. Additionally, this predictive analytic application:

· Offers cross-channel optimization by factoring in campaigns that run across multiple sales channels in order to prevent overloading callers who have already received offers through other channels. If an offer is made through the call center, PredictiveCallCenter will remove that customer from a similar campaign generated through a different channel.

· Minimizes sales load/overhead on the call center by suggesting only those recommendations with the highest likelihood of acceptance by a specific customer.

· Guides agents in making the offer by displaying supporting information, such as the response probability, the reasoning behind the offer and the sales strategies and arguments that are most likely to appeal to the individual customer.

· Stores information on offers being made, enabling companies to monitor and refine their marketing strategies.

“Our vision in developing predictive analytic applications like PredictiveCallCenter is to enable companies to understand and predict each customer's needs and preferences as well as any inherent risks, and to use this customer intelligence to create cross-channel campaigns for inbound call centers, direct mail, Web channels, and more,” said Marcel Holsheimer, vice president of vertical product marketing at SPSS and founder of DataDistilleries. “This allows them to centrally orchestrate their customer contacts, improving customer satisfaction and increasing sales, while at the same time decreasing costs and risks.”

PredictiveCallCenter can also be used in conjunction with Clementine® 8.5, the latest version of SPSS' award-winning data mining workbench. Clementine's data mining streams can be authored and deployed directly into PredictiveCallCenter, giving call centers access to data mining results in formats that are useful to them, without placing additional demands on data miners or analysts. Future versions of PredictiveCallCenter will include integration with SPSS text and Web mining technologies.

This launch follows the Company's recent release of PredictiveMarketing™, a campaign optimization and execution application for marketers that combines SPSS predictive analytics with the recently acquired DataDistilleries application technology.