Some retailers launched online deals well in advance of Thanksgiving, Black Friday and Cyber Monday.
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A related issue is the lack of structured data in some product categories, one reason that categories that have structured data, such as consumer electronics, have lent themselves more readily to comparison listings. "That was the case three years ago, but all of us in the industry are getting more sophisticated at structuring data. We`re providing multiple opportunities for comparison in new categories, whether apparel or home and garden. We`re finding it`s taking a little time to structure data in these other categories, but it`s happening," says Rob Solomon, vice president and general manager of Yahoo Shopping.
Yet another limiting factor is the technical requirements of the data feed, a significant issue for smaller merchants without big IT resources. "You talk to ChannelAdvisor, Channel Intelligence, Mercent and Performics, and they are all doing a great job of managing, submitting and optimizing feeds for companies with annual revenues of $10 million to $25 million plus," Smith says. "But they are not dealing with small businesses. For every large Internet Retailer 400 company out there on the shopping comparison engines, there are about 10 or 20 small businesses with no one helping them out."
While the industry works to address those issues, the best advice for merchants looking to profit on comparison marketing is vigilance on monitoring ROI. When determining the likely gain from listing offers from Overstock on any comparison engine, Hawkins looks at some key factors. For one, different engines have different strengths, he notes. "Price Grabber, for example, is good with books, music and videos. NexTag is good at electronics. Shopping.com is good at some of the softer categories, like home and garden. Shopzilla does well with apparel and accessories," he says. The retailer should look at how much volume overall the engine gets, how much traffic the retailer gets in a comparison site`s areas of product strength, how many different advertisers are there for that category on that engine, and finally, how well the traffic from that engine converts.
"We actually go out and put products on all the engines, and as we find which ones don`t work, we pull them off," Hawkins says. "It`s a comparison-engine-by-comparison-engine decision, a category-by-category decision, and even a product-by-product decision."