Can you tell if personalization is working effectively on your commerce site, right now? Not just the “what” — content or products/offers is being shown — but why and how?
As companies forge ahead and invest in artificial intelligence and machine learning technologies for their e-merchandising teams, the goal is to treat every website visitor as an individual and let them pick out their own experiences instead of defining an one-size-fits-all “journey”.
A quick story.
About two decades ago, a relatively small ecommerce company focused on selling books introduced a new feature that allowed customers to see what others had liked and purchased, called collaborative filtering, for product recommendations. This feature became popular with the business guys as the “wisdom of crowds” and very soon, every retailer on the planet was scrambling to implement it.
Personalization traditionally works best when you have tons of behavioral data for each product. But how do you personalize for new products or ones that are considered “long-tail”? How do you ensure that this inventory is immediately visible and recommended to your customers? Well, you couldn’t until recently .. not without NLP.
Personalization, at its core, is the idea that as a consumer, you are served exactly what you want, when you want it. AI is being deployed by retailers and brands who understand that this is a “big data” problem and when product catalogs become larger, machines start to perform as good as, if not better than, human merchandisers.
But does this quest for delivering “exactly” hurt consumer choice?
Love the first half of the year. It’s the time I get to speak our customers on their initiatives to grow their digital revenues via experience personalization. If there’s one thing that’s different than last year, it’s the shift in the key challenges as personalization moves from helping shoppers BUY, to helping them SHOP!
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