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.
You can’t have a meeting these days without someone throwing out the platitude “data is key”, but all too often, we find that even with the vast amounts of data being collected, business leverage of this valuable data is a problem
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?
A McKinsey survey of senior marketing leaders found that only 15 percent of CMOs believe their company is on the right track with personalization. In this recent article, they summarize 3 trends in the future of personalization:
- Digitization of Physical Spaces
- Scaled Empathy
- Usage of Ecosystems by Brands
San Francisco & London 9th July 2019 – RichRelevance, the global leader in experience personalization and the first to deliver on hyper-personalization, has been named a ‘Leader’ in this year’s Gartner Magic Quadrant for Personalization Engines[1].
San Francisco & London 9th July 2019 – RichRelevance, the global leader in experience personalization and the first to deliver on hyper-personalization, has been named a ‘Leader’ in this year’s Gartner Magic Quadrant for Personalization Engines[1].