Excerpted from Strategy & Business, “Web Sales with a Human Touch”, by Edward H. Baker, August 28, 2008
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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 use 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, CA, 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.
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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 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.
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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.
The goal at this stage is to match likely consumers with likely product choices.
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Once a visitor is identified as a hot lead, another filter determines whether to invite him to chat — that is, the program analyzes whether talking to him is virtually the only way to convince him to make a purchase. On one level, deciding who to invite for a chat is a simple scheduling problem: Are there enough agents available to handle the chat? Increasing the number of agents means increasing the number of invitations to chat, which in turn means approaching colder leads who are less likely to end up making a purchase. The colder the lead, the lower the potential profitability.
On a more strategic level, the software must determine the number of agents that will maximize profitability. Further statistical modeling is needed to select the right agent for each consumer, depending on such criteria as the best-performing agent for the product category that individual is looking at.
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Now, it’s time to chat. The 24/7 chat format, of course, does not allow for all the nuances any decent salesperson picks up in a face-to-face conversation. It does, however, perform analyses of thousands of chat transcripts, through text mining and data mining, to perfect the techniques that human customer service representatives use to close the sale.
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Adobe, the software giant, rolled out SalesNext in July 2007 with excellent results. Since then, the company has seen a 15 percent jump in conversion among consumers who chat, says Dawn Monet, senior manager of Adobe’s worldwide call centers. And, she notes, the satisfaction of consumers who use chat is higher than that of both consumers who shop online without chat and those who shop by phone.
Edit by DAF
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Full article:
http://www.strategy-business.com/press/article/08313?pg=all&tid=230
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