How Visual Data Helps Shops Make Better Buying Decisions

The humble avocado. The super food of choice for Instagram users and a best seller up and down the country. If anything were to sum up society today it’s an avocado. A glimpse into the shopping and eating habits of Britain.

Demand is such that you can pick up an avocado just about anywhere today from petrol stations to the food halls in Knightsbridge. It’s a reflection on how we like to shop. Large monthly online shops, supplemented by smaller, frequent top-ups of fresh fruit and veg, and the staples of bread and milk.

But for all that is good about the avocado, it’s actually a pain in the side of the retailers’ buying teams. That’s probably a little exaggerated, but the principle is true – knowing how many you need of a product and where to sell them isn’t as easy as it sounds.

Avocado_zoined

Of course, there’s always going to be the notion that if you don’t offer it, then people will never see it to buy it. I’m sure there are plenty of things we put in our shopping baskets today that we didn’t know existed five years ago. Coconut water anyone?

But it’s not by accident. Supermarkets looking for ways to differentiate their range have huge buying teams dedicated to finding the next big trend. And when they find it they test it and sell it.

But differentiation isn’t just about range. As we know from the battles to win customers, price has a massive influence on where we shop and what we buy and so does service and quality. Every one is looking for something different to suit their own budgets and tastes, not to mention the experience they want to have when they come into your store.

This isn’t new. But how buying teams are managing the challenge of balancing these needs is changing. In fact we are starting to see a shift from the head office to the stores. Read how in my article on Minute Hack >


Read also:

Like this article?

Share on Facebook
Share on Twitter
Share on Linkedin
Share on Pinterest

Leave a comment