Category management is one of the most important, yet hardest, aspects of retail. How do you maximize profits within categories? And how do you determine how much space each category should get and where in the store the it should be located to make your store more shopable? After hours of meetings and numerous spreadsheets, you’re still not sure whether you made the optimal decisions.
Currently, most retailers only look at sales and market data to manage their categories. Revenues, market share and growth are of course important, but without understanding customer behavior you will fail to see the full picture. How can retail analytics and understanding store behavior help you maximize value within a category?
Where to invest your money and space
The BCG growth-share matrix is a popular model for determining how much to invest in categories and make strategic decisions on the future of product categories.
While this is certainly a good start, an even more advanced way to look at categories is by taking customer behavior into account. For instance, imagine you have an electronics store and your tablet category has high engagement (high dwell time, visitors, interaction with the products), but low revenues. And say it falls within the ‘question marks’ box: high market growth, low relative market share.
Nowadays, it might get allocated less space, because of its high risk. But what is the real problem here? If there are a large number of consumers, spending more time and touching more products in this ‘low-revenue’ zone compared to a zone with higher revenue, the root cause of the low revenues might be the pricing, assortment or staff. Especially given that the overall market growth of this category is high, store behavior can provide answers as to why the relative market share of your company is lagging behind. High engagement levels in this case indicate that people find this product category interesting, so it should not get less space. But maybe the assortment and price within the category just isn’t quite right. Or the staff should get trained to convert those interested shoppers in customers.
The perfect spot for each category
Combining behavior and market growth can help you optimize space allocation. If products in a certain category get touched a lot, but the category’s overall market growth and sales are declining, you’ve discovered that it might be in a too prominent place in the store. You can better swap spots with a category with high market growth.
Moreover, by understanding the customer flow and path you can make your store more shopable and increase your profits. If you know, for instance, that most of your male consumers like to take the left path and don’t get further than half the store, but your most of your females do go all the way to the back you can take this into account when planning your store lay-out. And when combining insights on basket mix and shopper path, you can determine how categories should be placed in relation to each other.
Optimize assortment within the category
Customer behavior can also be used to optimize assortment by comparing the amount of touches every product gets against its revenues. A product that gets touched a lot but doesn’t get sold would have possibly been removed from the category before. With new types of insight, however, you’d come to different conclusions. The product might, for instance, be priced too high or it’s a product that everyone finds very interesting to touch, but is too ‘new’ or ‘different’ to be a bestseller. This doesn’t mean it should be removed. The product can still be important for your positioning as a fashion-forward retailer, but it needs better marketing to introduce it to the consumer or simply needs some time before getting popular with the mainstream.
Next time you think about your categories, go beyond looking at revenue, but understand behavior in your store through retail analytics. This will both make your store more shopable for consumers and increase your profits.