Have you heard about “Searchandising”?
Companies that compete in the search and merchandising arena provide decision-making tools for customers to allow them to find products quickly and easily. Although the concept is called faceted search, vendors have different names for it and are busy registering and trademarking their segmented search descriptors.
Search analytics data is currently used by 65 percent of Best-in-Class retailers to build customer profiles, evaluate buying patterns and discern successful keywords and conversion paths.
This data can be modeled to anticipate customer behavior and is leveraged by 26 percent of Best-in-Class merchants to tune search results in order to merchandise to customers and customer segments on a predictive basis.
It should be noted that this process can be achieved in real-time — but it is extremely difficult to do. Sophisticated search technologies can deliver real-time merchandising results based on information gained during a consumer’s current online session, but most often this is not the case.
Predictive analysis and collective behavior are capabilities inherent to some search applications, but retailers must start with segmentation and faceted search basics prior to getting accurate predictions of what customers want and what they will purchase.
Additionally, 68 percent of leading sites use data collected from search to feed back into their merchandising tactics to influence results. What’s even more important is the ability to measure and manage the conversion process to key into what works and to modify tactics that fail.
If these processes are put in place, sites can maximize the profits of searchandising to provide a more relevant shopping experience for customers — and higher profits.
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Tags: data mining, e-Commerce, retailers, web2.0