How tech can help retailers with in-store product placements

Here are some really exciting insights into how retailers actually collect and use in-store data
11 October 2018 | 10 Shares

Tech is helping retailers get smarter. Source: Shutterstock

When you go shopping, you’re giving the retailer of your choice access to a whole lot of data about yourself — data they can use to delight you, wow you, and keep you coming back.

Okay. Let’s take a step back. If you think that buying your groceries at the retail store and paying in cash means that they know nothing about you, you’re wrong. They’ve got cameras, and cameras — even without facial recognition — can identify people, determine and log gender, follow physical, in-store movements, and learn about your choices, tastes, and preferences.

If there’s something that attracted you but you didn’t make the purchase, it’s still an indicator of your choices, and is valuable data.

But we’re not going to talk about the cameras that help retailers track customers today. Instead, we’re going to learn about some of the things that retailers can do with the (big) data they collect:

# 1 | Make products easier to find:

A typical store carries more than 5,000 different kinds of products in inventory. Finding what customers want might be hard sometimes.

But there are only so many shelves at the eye-level, the easy to find shelves, that are available in any store. Not everything can be ‘easy to find’.

Fortunately, the data that stores capture can help identify which products customers struggle to find the most, plot the number against the total number of customers as a percentage, and then take a decision.

If a lot of people look for the product but don’t find it, and it causes them to ignore all substitutes that are somewhat easier to find and maybe go to other stores looking for the product, then it might be a good idea to give the product better or prime placement.

On the other hand, if the product is hard to find — and although a lot of customers look for it, people tend to pick a substitute instead when they can’t find it, then it could help to determine which one is going to earn the store more money and stock the products accordingly.

# 2 | Make insightful placement decisions

Product placement is an art just as much as it is a science — but using big data, it’s something that can be perfected quite easily.

Let’s take an example. Confectionery and candy are usually placed near the check-out counter. It’s common knowledge by now — and makes a lot of sense. Customers might resist the purchase if the goodies are stacked right next to the vegetable station where the customer picked premium produce for his salad.

Instead, when confectionery and candy are placed near the check-out counter, it’s something that the customer tends to think is okay to buy as a reward for their work in the store (shopping can be hard).

Let’s take another example. Ice cream. Although modern ice-cream tubs don’t spoil easily, customers tend to fear that they’ll melt before they get to the check-out counter. Hence, stores generally place these closer to the billing stations than they do other frozen products like meat and frozen vegetables.

# 3 | Sell better product placement

When retail stores know which product placements are prime, they’re in a better position to charge a fee from distributors for the special treatment.

Although not all packaged goods companies pay for these, many of the new companies looking to help customers take note of their products tend to be inclined to make the investment.

Further, when retailers know which are the prime placement slots, they’re much more likely to be able to promote products that provide higher margins — make them fly off the shelves, earning themselves a good income.

Truth be told, it feels like all eye-level placements are prime — but it depends on who’s looking. What’s prime to most adults might not be even discoverable for kids although the latter could be the target audience for the product.