What Retail Analytics and Loyalty Card Data Can Teach You About Shoppers
Loyalty cards, and the customer data that is collected from them, can influence the way in which you run your retail business. That’s because it’ll allow you to know your shopper. And with this type of retail data at your disposal, you can only expect to profit. Of course, loyalty card data can do far more than tell you about your shoppers’ identities.
The data can also tell you about the reasons why your shoppers come back in the first place, and how much your shoppers spend on average per trip to your store. The data can even tell you which brands are your greatest traffic drivers and which generate the most spend.
A closer look at the importance of loyalty card programmes
Considering the amount of customer data that you can obtain from loyalty cards, you’ll be hard-pressed to find any argument against using them. That’s because besides allowing you to gather information about your customers, they can also help you to put your shoppers first.
You’d only need to look at Nielsen’s latest Global Retail Loyalty Survey which came out in late 2016 to confirm that. Of the 30 000 online respondents that they surveyed across 63 countries, 72% agree that, all other factors equal, they would buy from a retailer with a loyalty programme over another retailer that didn’t have one.
If you want to look at the survey from a South African perspective, you’ll find that the country had the highest number of respondents who stated that they were current members of a loyalty programme. “Bolstering this view, 62% of South African respondents in the study revealed that they belong to between two and five schemes, while 6% said between 6 and 10 schemes.”
All the above points to the importance of loyalty card programmes. But what about using that data to improve your business?
How loyalty card data can help you improve your retail business
If you want to make full use of the retail analytics data that you collect from your loyalty cards, you need to see how you can plug it back into your retail business. One way of doing that is to use it to help you build your ranging strategies.
Your ranging strategies are built around understanding who your target customers are as well as their basket behaviour and category performance in each format (cluster) and store.
Just to note, despite similar spend across your stores, you do still need to take the store profile into account when ranging a store.
1. It can tell you which segments to prioritise
Based off of the information that you gather from your shopper profiles, you’ll be better placed to understand which segments you need to prioritise.
Let’s say that you’re a Pharmacy Retailer, for example, with a variety of different stores spanning Destination, Convenience, and even Regular Stores. So how do you decide where you need to prioritise? With the help of data, of course. And with the data, you can determine the turnover of any particular category across your stores.
So let’s continue to use the above example and say that we’re comparing all of your stores’ turnover for Category F. In doing that, we find that between them all, your Destination stores are performing the best while your Convenience stores are performing the worst.
The data also lead us to believe that your Destination stores have a higher turnover per store within Category F and that’s driven by shoppers shopping there more often. Meanwhile, your Convenience stores are underperforming because while shoppers are buying Category F, they're making fewer trips to your store so there is lower traffic.
In the case of Category F, we also find that the highest share of wallet across both store types is Sub Category A followed by Sub Category B. As such, optimising the range on these would be your priority.
2. It can tell you which strategy to consider for growth
When it comes to deciding which strategy to consider to grow your retail business, a good place to start is by looking at the basket behaviour of your customers. What are they buying, and how can you use that information to improve your stores.
In the above example, we found that Sub Category A and B have the highest share of wallet amongst your loyalty card members. But that’s not all. We’ve also found that Sub Category C and D drives traffic to your Convenience stores.
Meanwhile, two thirds of all trips made to your Destination stores by shoppers is to buy a products within Sub Category A. Thus, increasing the range of products within Sub Category A would not only drive traffic upwards but it would also improve conversions.
Another opportunity for growth in your Destination store would be to encourage your customers to buy across Category F’s repertoire. To ensure growth in Convenience stores, you can look at driving up store visits.
3. It will help you decide on your must-stock SKU Lists
The data you collect from your loyalty card members also allows you to decide which SKU’s have low levels of transferrable demand and which are worth leaving off your list. This is based off of your SKU performance data.
Of course, your range size does matter here. A wider range of products within Category F can be a contributing factor in the performance of your Destination stores since they will have a higher number of SKU’s in comparison to your smaller Convenience stores.
That said, not all SKU’s contribute equally, and so ensuring the correct SKU’s are stocked will be imperative to your space optimisation. Let’s look at Sub Category A to clarify. While it has the highest share of wallet, if you dig deeper, you may find that there are quite a few SKU’s that contribute very little per month, per store.
A little more work would need to be done, but you could consider delisting them and using the shelf space for other better performing products.
If you do want a better indication of must-stock SKU’s, its worth looking at the average turnover per SKU in the stores where they are stocked. If your SKU’s are performing well in your Destination stores, for example, and you have similar store profiles, it’s worth extending your distribution in Convenience stores.