“B” Before “e” When Marketing to “C”

  • Written By: D. Geller
  • Published On: May 15 2000



“B” Before "e" When Marketing to "C"
D. Geller - May 15, 2000

Event Summary

The name of ResponseLogic, Inc.'s newly released product is ADAPTe. While the "e" is probably intended to represent the expert systems technology at the product's heart, they are sending another message by putting the "e" after the name. While definitely an e-commerce company, ResponseLogic has its roots and focus in business. Their technological approach is, as President Jim Scott explains, "wrapped in the best practices of traditional direct marketing."

Expert systems technology is primarily rules-based, where the marketing specialists set the rules. An inference engine observes the behavior of shoppers and generates recommendations for cross-sells and up-sells. With the inference engine focusing on behavioral aspects the marketer is freed to devise rules based on business objectives.

Expert systems technology is sometimes thought of as an older technology than "collaborative filtering," on which many other personalization products are based; collaborative filtering technologies attempt to identify one customer as being part of a group with similar behaviors. Its best known application is on sites where a shopper sees a list of recommendations based on previous purchases, and after a purchase also sees cross-sell recommendations of the form "others who bought this also bought "

Collaborative filtering is often successful, and is part of the ResponseLogic inference engine, but it has some notable weak spots. As CTO Dev Sainani points out, if a merchant's database is not statistically valid collaborative filtering may end up de-personalizing the shopping experience. Also, Dr. Sainani notes that "everyone has had the experience of buying a gift for a friend and then seeing recommendations for months afterward that are based on the friend's preferences and not yours."

Response Logic's solution to the second problem is embedded in its permission-based approach. While using large direct marketing databases of anonymous profile information, ADAPTe displays itself to the user as a personalized shopping assistant. It builds individualized profiles only for shoppers who request such assistance. One of the features of the shopping assistant is that it allows the shopper to notify it about gift shopping. So, when you are shopping for something special for Aunt Minnie ADAPTe will not mix those purchases with your own personal preferences; but it will remember them the next time Aunt Minnie's birthday rolls around.

The company intends to charge for the product based on success. Pricing will be based on the number of successful matches of shoppers to rules by the inference engine; these represent presentations of "the right product to the right person." In the future the company hopes to develop pricing models that are tied to the sales lift provided by the product.

ADAPTe not only makes the recommendations, it also manages the content to be displayed, tracks customer actions, and reports on customer demographics, segmentation, and buy versus browse behavior. Like other products in this space, ADAPTe can work with the data it collects, anonymous third party profiles and data on individuals that comes from a company's own databases.

Market Impact

This is a growth market right now, and the inevitable shakeout is far in the future. Companies like ResponseLogic are still staking out their turf and laying foundations. In the short run they need to develop identity, niche, and proven successes. While there are already powerhouse companies in personalized marketing, there is plenty of room for startups to make inroads. Perhaps more so in this area than in most areas, in fact, because the sale is much less dependent on persuading technologists than on persuading marketing people.

ResponseLogic has been forging some interesting partnerships, including one with a high profit direct marketing agency and one with a Latin American technology investment firm, that should give it both visibility and experience.

User Recommendations

While specialists can make general statements about the efficacy of one technology over another, we think there is no clear way to differentiate without seeing how products work on your data. Any of the vendors on your short list should be able to take a sample of your data and give you an indication of the kinds of recommendations it would make. This is a very competitive market, and you should accept nothing less.

With vendors like ResponseLogic, where the infrastructure investment and impact are relatively small, we believe that the IT professionals should be comfortable in letting Marketing drive the selection process (they will anyway). What is most important about products like these is whether the marketers can control them easily, and whether they can see the results of their actions. IT can provide a useful supporting role in the earlier stages by looking for potential interface and functional problems that might not be readily apparent to non-technical folk, and in validating the ease with which corporate content management systems will interface with the product's.

 
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