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Market Watch: Analytics
The trick for vendors is to make analytics more a part of the everyday workings of a CRM solution.
For the rest of the October 2003 issue of CRM magazine please click here
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Now that analytics has taken a secure place in the big picture of CRM, the trick for vendors is to make it more a part of the everyday workings of a CRM solution. "The trend is to bring analytics in line with the CRM applications," says Erin Kinikin, vice president and research leader at Giga/Forrester Research. "It's not enough to deliver analytics on the side--it's got to be in the context of the application. CSRs and sales representatives do not particularly need more information; they need better decisions." Some vendors have been taking this principle into serious consideration as they offer new analytics tools for CRM systems. "We have seen two major trends around analytics: putting the analytics tools more into the hands of marketers instead of IT professionals; and a trend of pulling even more disparate types of data together to provide that coveted 360-degree view of the customer," says Colin Shearer, vice president of customer analytics at SPSS. "And we are creating products to do just that." One marketer who has taken advantage of advanced analytics capabilities is Lori Chan, a marketing analyst with Carfax.com, which provides vehicle history reports to car buyers and dealers. Chan says she has been using WebSideStory's HitBox product to make critical marketing decisions for the Carfax Web site. "Most of our revenue comes from selling reports, and HitBox can show me if a lot of visitors are not clicking on areas of the site that will lead to revenue," she says. "Thus I can quickly make a decision on how to alter the site to increase traffic to revenue generating areas." Chan adds that HitBox can help Carfax.com gauge visitor response to different site designs, showing which versions of the site drive more revenue, so the company can attain optimal site design. Kinikin says the next step is for analytics vendors to allow nontechnical users like Chan to get more proactive, using predictive data to find out what the customer will buy next, which customers are likely to leave the site quickly, and to discover what can help the customer avoid future problems.
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