Over the last decade, data has exploded.
Many consider it the new oil – a rich resource that businesses can use to fuel deep insights, make smarter decisions, and grow profits.
This is especially true in retail marketing. Data gathered at point of sale (POS) can tell you so much about your customers that you can use to market to them more effectively, including:
But there’s a catch. Data is only as valuable as the insights you learn from it. You can’t collect reams of raw information and expect it to automatically translate into increased sales. You need a methodical and strategic approach to gathering data, analyzing it, and measuring the results.
Before you dive into the world of retail data analytics, take a step back, look at the big picture, and establish your goal. Do you want customers to spend more in-store? Are you trying to encourage online engagement with your brand? Is there a new retailer on the market you need to compete with?
Once you know your goal, it’s time to get acquainted with the people that are most important: your customers.
Personalization is the key to effective marketing. 80% of companies have seen an uplift in sales after implementing personalization. But many retailers struggle to achieve this. 64% of customers feel that retailers don’t truly know them.
When you have thousands of people walking into your stores every day, how do you get to know each one of them better at scale?
This is where transactional and customer data collected at your POS can help. What your customers buy will tell you about their preferences, behaviors, and circumstances. You can use this data to get a better picture of who they are and then segment them into groups so you can target them more effectively.
There are two ways of doing this.
A basket from a single store visit tells you a lot about why a customer is shopping with you that day. You can look at factors such as:
With this data, you can segment baskets into different ‘types’ of shop. For example, 1-3 items made up of store cupboard essentials like milk, eggs, and bread suggest a top-up shop. A $25 basket consisting of cakes, wine, and cards, meanwhile, indicate someone shopping for a birthday or anniversary.
Segmenting baskets gives you a snapshot of a customer at a moment in time. You can use this to deliver offers via channels like coupons at till that are personalized to that basket segment – money off eggs and milk for the top-up shop, for example.
However, to really get to know your customers, you’ll need to track their data over a longer period of time.
To track and analyze historical customer data at POS, you’ll need one of the following:
Track customer data over time, and you can segment customers into groups that enable you to target marketing messages and offers at a much more personal level.
Here are a few examples:
Children’s yoghurt, baby wipes, diapers – a customer buying these items regularly almost certainly has children at home. This can even reveal how old the children are from product types and sizes, for example, whether customers buy size 1 or size 6 diapers.
You won’t catch the foodie buying frozen pizza or ready meals. A customer who buys items like flour, spices, or other ingredients is most likely prepared to spend the time cooking from scratch.
This customer is conscious of how much they spend. You can tell because they almost only buy products from your own-brand ‘value’ range.
Most retailers typically have between 6-12 customer segments. Once you’ve segmented your customers, look at how many of each customer you have, analyze how these numbers change over time, and use that to inform your marketing strategy. For example, if one month you find that your retailer is losing ‘foodie’ customers, you can alter your marketing tactics to better appeal to that segment and win them back.
Now you’ve segmented your customers, you’ll need a strategy for each. This will help you get as close to 100% of their grocery spend as possible.
Your payment providers can give you a cross-view of how customers are splitting their wallets between you and your competitors. Generally, customers will fall into one of three spending categories:
You’ll need a different strategy for each type of customer.
Your most loyal customers are your most valuable. Because they spend the most with you, losing them will have the biggest impact on your bottom line. You need to do everything you can to keep them happy and engaged – so they keep coming back to your stores.
Your marketing strategy for these customers is to thank them for their loyalty with rewards. You can offer gifts, prizes, or cashback, but less tangible rewards can be effective as well, such as early access to new product launches or 24-hour notice ahead of a major sale.
This strategy encourages the customers who shop with you occasionally to explore and expand how much they engage with your brand. Look to see if there are any product categories routinely missing from their basket. For example, if they only buy shelf-stable food, they might find buying fresh produce from a local greengrocer more convenient or feel that a competitor’s fresh produce is better.
Tailor your marketing to convince them to give you a bigger share of their wallet. For example, you could highlight the unique or high-quality items you stock that your competitors don’t, or feed the information back to your product development team to improve your fresh produce selection.
For the customers spending 0% of their wallets with you as a retailer, you need an acquisition strategy. You can focus on different channels to bring new customers back to store, including traditional media like TV and radio advertising, or more commonly, online advertising. To make this acquisition most effective, the best way is to profile your best customers and then market to 'look-a-like' customers through online channels.
You’ve segmented your customers and decided on your strategy. Now it’s time to market to them.
Marketing channels offer varying degrees of opportunity to use retail data analytics for targeted messaging. Targeted channels, such as apps, digital receipts, and coupon at till, are where the data can make the most difference.
Take digital receipts. You can design your receipts with a completely different look, message, and tone of voice to appeal to a specific customer segment. For example, a digital receipt targeted at a foodie customer might include links to recipe ideas that incorporate the ingredients they just bought in that basket.
Retailers have begun reducing marketing spend on some of the more traditional channels, such as TV and radio, because they’re high-cost and less targeted. Why spend millions on a TV ad when you don’t know who is going to watch it?
Promotional budgets can also be used differently, by choosing to run fewer instore promotions (e.g., 20% off a department). Instead, you can use the budget you save to provide more targeted discounts.
Steps 1-3 are a waste of time if you don’t measure whether your efforts are working.
When you send your customers targeted marketing, track who responds and what effect it has. You need to establish whether your marketing is causing a customer category to increase or decrease.
For example, if you can see that your marketing campaigns to foodie customers are increasing spend in that category, that’s a sign your campaign is working. On the other hand, if that customer group is shrinking or remaining stagnant, that indicates you need to try some different marketing tactics.
To test the success of your marketing, you need a large and robust control group to measure against. Say you’re targeting 100,000 customers with a coupon marketing campaign. Hold back 10,000 customers (10% is usually the right amount) so that they don't receive the coupon and can act as the 'control' for the experiment. This way you can understand whether your efforts are having an impact.
You’re looking to see if the customer spent more. If they did, it will either be because they visited more, or increased their spend per visit. Then you can compare this against what you expected from your control group.
Retail data analytics offers exciting opportunities to make your marketing more personalized and effective. But remember that data is only as valuable as what it can teach you and how you use it.
To get the most out of your data, you need a channel-agnostic retail marketing analytics platform that’s easy for any marketer in your business to use. With the right platform, you can use audience building tools to segment customers quickly, then deliver targeted messages via your channel of choice, whether it’s via a coupon at the till or a digital receipt.
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