This week I attended an event called Retail Summer School at Columbia Business School in New York.
Much of the talking was about how to get insights on your (prospective) customers by collecting data in all kinds of ways – while observing the thin line between cool and creepy.
My thinking, of course biased by my current Product Data Lake venture, is that you should also pay attention to product data. For at least two reasons:
Algorithm effectiveness: Your algorithms on what products to present based on your rich insight into your customers need will only work if you are able to automatically match the needs against very specific product attributes. And most retailers don not have that today if you look at product descriptions on their ecommerce sites.
Also, I am not impressed by the suggestions I get today. They generally fall into two buckets:
- Things I absolutely do not need
- Things I just bought
Self-service craving: As a customer, we strike back. We do not need to be told what to buy. But we do want to know what we are buying. This means we want to be able to see rich product information. Therefore retailers must maintain a lot of product data and related digital assets that they should fetch at a trusted source: From the manufactures. And if the manufacturer wants their products to be the ones selected by the end customers, they must be able to deliver these data seamlessly to all their distributors, retailers and marketplaces.