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. “SalesNext really enables the ‘magic moment,’ when we can be there with the customer when and where they have a question. The customer doesn’t have to search for answers or wait in a call queue,” says Monet. “This is the beginning of how we will communicate with customers in the future. It combines the human element with the technology in a new, powerful way.”
A well-run sales chat program driven by predictive mathematical models can greatly boost a Web site’s profits and consumer loyalty, while reducing costly returns. The solution, however, doesn’t work right out of the box. Like that crack salesperson on the floor at Sears, who learns something from every encounter with a consumer, chat can get smarter day by day. The true power of sales chat, when coupled with predictive and text-mining technologies, lies in the ability to learn what works and what doesn’t, and to constantly refine the system’s filtering and selling techniques.
Edward H. Baker, former editor of CIO Insight magazine, is a contributing editor at strategy+business.