The comprehensive data collection and information analysis capabilities of the Internet allow ecommerce retailers to continually update their knowledge of what their customers are buying. In fact, with the sorts of facts you can learn from even a frequent shopper program, you can do a quite good job of figuring out what sorts of current customers are buying what sorts of items from your store.
Moving beyond this—or maybe it’s more accurate to say we’re moving earlier than this in the purchase process—think about reading the minds of not only your current customers, but also your potential customers. And not only what they are buying, but also what they intend to buy.
Online periodical Media Post News is currently reporting about “intent actions” collected by data auction marketplace vendor BlueKai. Intent actions are defined as specific store, product category, brand, and model names that consumers view during their Internet searches on ecommerce and retail price comparison sites. These data can serve as early pointers toward the interests Web visitors are exhibiting in advance of completing their purchases.
When using intent actions findings, look for surprises and trends. Ignore the rest or you risk being flooded by useless stuff. For instance, BlueKai found that as we entered spring this year, online consumers became less interested in winter clothing and snow sports. No surprise there, so pretty useless news.
But during this same period, there was a month-to-month increase of about 65% in intent actions data volume having to do with plants and trees for landscaping. This was accompanied by an overall spurt relating to other outdoor items, such as garden tools and patio furniture. This dramatic growth might be surprising to you. You’d suspect that consumer preferences would turn to thoughts of warm weather ahead, but this large an increase signals that you’d better gear up quickly to avoid missing opportunities. Spring fever is out of the question for you.
Click below for more:
Give Loyalty Program Members Prestige
Use Cluster Analysis on Customer Data
No comments:
Post a Comment