Why add Shopper to your Next Category Review?

“The future of retail lies in a single word: experience”

As shopper demands have changed, the relationships shoppers have with brands and supermarkets has also changed. Historically, the relationship focused on having ‘the best product at the best price’.

Today, manufacturers and supermarkets can harvest low hanging fruit simply by beginning to focus on delivering ‘the best overall experience’ to shoppers.

For your next category review, consider making a change to your category metrics: Traditional measures, such as unit sales per week, sales per facing etc. remain vitally important. But what if you overlay product metrics with shopper metrics? The emphasis would now be what products drive shopper loyalty and satisfaction. Importantly, these added metrics would revitalise category reviews by also adding the all-important ‘why’. For example, why does brand A outperform Brand B.

With a focus on shopper metrics, you can develop strategies that have more of an impact on key retail metrics. You can also address how different initiatives influence specific category objectives.

To illustrate, here are 5 fundamental shopper metrics, including real World examples, that when overlaid over product metrics dramatically improved the overall category story.

1. Store footfall – Quite simply, how many shoppers enter the store
2. Category footfall – What percentage of store visitors pass by your category
3. Category engagement – What percentage of passers-by meaningfully browse your category
4. Category conversion rate – What percentage of store visitors, category passers-by, active category browsers go on to make a purchase
5. Average weight of purchase – How many items does each purchasing shopper buy

When the shopper metrics are added to the more traditional category review measures, they can often reveal new insights and opportunities. Here are just a selection of examples:

1. Overall category sales and store footfall

Overall sales is quite simply the number of units sold by a category, split by brand, price point and a host of other factors.

Real world example: Over a period of time, category sales dropped and share of market suffered too when a particular retailer delisted Brand A, as part of a trading negotiation. The shopper metric revealed that because that retailer didn’t stock one of the leading brands in the category (Brand A), their range was not perceived as credible, so shoppers simply went elsewhere.

A further shopper metric also revealed that the category of which Brand A was a part, was the primary destination in-store for 8% of visitors: It was a real footfall driver, so removing a market leader had wide ranging consequences.

2. Average order value and category footfall

Average order value or average transaction value determines how much customers typically spend in your category (per transaction).

Real World Example: When Brand A was presented to shoppers as part of a category that had purchase options heavily promoted as starting at just ￡1, sales of Brand A underperformed, compared with other retailers. But conversely, when the category was showcased by a new luxury variant, costing more than any other alternative in the category, sales of Brand A leapt, by more than 20%.

The shopper metrics revealed that the ￡1 anchor point had a positive (albeit minimal) impact on driving the number of shoppers to the category. However, the percentage that bought anything dropped. Conversely, when shoppers were presented with the luxury option, category footfall and the conversion rate both increased significantly. And here’s a key point, sales of the luxury variant were almost nil! Viewing its data in isolation may well have resulted in delisting. But when viewed as the impact it had on driving footfall to the category and then selling to them, it was a roaring success.

3. Sell-through rate and category engagement

The sell-through rate indicates which specific products are overperforming or underperforming, enabling you to adjust how many of each SKU is the optimum.

Real World Example: When the category was remerchandised after a category review, Brand A saw an increase in sales of 14%. Firstly, the new category layout was applauded, but this changed when new shopper metrics revealed a different story. In this example, it was all to do with the order in which the sub-categories we presented to shoppers, much more than how they were laid out individually. In summary, when shoppers reached Brand A before other brands, sales fell, but when it was located later (much later) in flow, sales increased.

The shopper metrics added a layer of detail that when analysed more thoroughly, revealed that there was a definitive order of purchasing preferred by shoppers.

4. Sales per square foot and conversion rate

This metric is essential because it lets you see how each SKU is performing based on the amount of space it has. When you overlay the shopper metrics, you can also identify how different layouts, share of shelf, store format and a host of other variables truly impact.

Real World example: Sales of brand A increased by more than 40% when it was dual sited both in aisle and on gondola end. Although traditional data suggested shoppers bought more from the gondola end, more specialised shopper analysis revealed the additional sales actually came from the core aisle. In summary, the gondola end worked because it drove up awareness, but most shoppers responded by then going to the core aisle. The conversion rate was 14% for the gondola end, but 89% for the aisle!

5. Basket size and average weight of purchase

Basket size tells you the typical number of items sold per transaction.

Real World example: When Brand A ran a ‘3 for’ deal, it generated a double digit increase in share of category sales. A further secondary siting resulted in both an increase in sales of Brand A and category sales overall. When shopping activity was presented alongside the traditional category review metrics, it revealed that although the promotion increased sales of Brand A, more than 70% of purchasing shoppers didn’t buy enough to qualify for the deal, selecting just 1 or 2 units.

The key insight here is that the promotional POS drove visibility of Brand A resulting more sales. However, only a small minority of shoppers mentally processed the mechanics of the promotion sufficiently to actual take advantage of the added value.

For your next category review, consider making a change in category metrics: Traditional measures, such as unit sales per week, sales per facing etc. remain vitally important. But what if you overlay product metrics with shopper metrics? The emphasis could now be what products drive shopper loyalty and satisfaction. Importantly, these added metrics will revitalise category reviews by also adding the all-important ‘why’. For example, why does brand A outperform Brand B.

With a focus on shopper metrics, you can develop strategies that have more of an impact on key retail metrics. You can also address how different initiatives influence specific category objectives

Adcock Solutions have been improving the marketing communications of leading brands and retailers for more than 25 years.

We explain how your customers really think and make decisions, so that you can engage with them more effectively. Come to us for Behavioural Science insights and expertise that improves the visibility, appeal, engagement, and sales of your brand.