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Published: August 26, 2008

 
 

Web Sales with a Human Touch

Bringing personalized service to e-commerce consumers.

The late Ben Feldman, known as the greatest life insurance salesman of all time, once said, “Selling is 98 percent understanding human beings and 2 percent product knowledge.” Call it Feldman’s Law. That view has never gotten much traction in the world of e-commerce, where the mantra has been to minimize human contact with customers. To be sure, many e-tailers endeavor to gather as much knowledge as possible about customer behavior and buying habits by aggregating and crunching massive amounts of data on users’ online buying habits. But those are just dry numbers and statistics. The plain truth is that even the most successful, tech-savvy retail Web sites still convert only 1 to 3 percent of visitors into buyers, largely because Web-based salesmanship is such a blunt instrument.

Suppose, however, that you could migrate Feldman’s Law to the Web, using the very technological virtues that make e-commerce so potent a sales channel, and bring in the human touch at exactly the moment it would be most effective. How much would that be worth? According to 24/7 Customer, a business process outsourcing firm based in Campbell, Calif., with clients as varied as Adobe Systems Inc. and Capital One Services Inc., the human touch used in this way can increase online consumer conversion rates by 15 percent or more. To prove this, 24/7 has developed predictive software called SalesNext that sorts online visitors into hot and cold leads and then makes personalized contact through online chat with the most promising prospects to close the deal. “It’s as if you could translate the judgment and timing of a top salesperson at Brooks Brothers or Best Buy straight onto the Web,” says 24/7 CEO and cofounder P.V. Kannan.

The flow of consumers from the category of mere visitors to that of actual buyers, in any sales channel, is like liquid passing through a funnel. At a real-world retail outlet, the marketing portion of the funnel at the top is poorly targeted because companies have limited control over who visits a store. The power of the funnel lies at the bottom, where seasoned salespeople convert store visitors into buyers. However, the top part of the typical e-commerce funnel is potentially very efficient. Advanced Web marketing techniques can target prospects entering the online retail site on the basis of prior Web behavior and other historical data and drive them to items that match their past preferences. But the bottom part of the funnel narrows to a trickle, because most Web sites’ one-size-fits-all consumer experience — which at best may include a chat feature that relies on wooden scripts with little variation for different customer types — makes conversion of those visitors into buyers much more difficult. However, by separating the tire kickers from the hot leads, then chatting with those leads in a way that personalizes their experience and drives them toward a transaction, Web retailers can open up the bottom of the funnel significantly.

Plenty of retail Web sites offer live human-to-human chat with consumers; what distinguishes 24/7 Customer’s approach is its ability to offer chat only to those who might not otherwise buy. Getting to the stage at which a visitor is invited to chat involves a series of filters de­signed to predict which individuals are most likely to buy as a result of a chat, rather than through self- service. After all, there’s no point in needlessly cannibalizing the lower-cost automated channel. As a visitor browses the Web site, she is evalu­ated on a variety of criteria, including how she was referred to the site, whether she’s visited or bought anything there before, the time of day, the day of the week, her geographical location, and the product category. Equally important is the path a consumer takes through the Web site. If she heads immediately to the spec sheet for a particular digital camera, it’s unlikely that chatting with her will influence her buying decision. But if she appears to be wavering among three different models, a chat just might help her make up her mind.

 
 
 
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