Leveraging Loyalty Data to Optimize Personalization

It’s no secret in the marketing world that the goal of a loyalty program is two-fold: to improve customer acquisition and retention while collecting customer data. The idea was that the latter would contribute to the former by allowing a business to gain a better understanding of their best customers’ buying habits and preferences in order to keep them and attract more like them. That has been accomplished primarily by marketing to a set of personas based on patterns identified in the data collected.

Those generalized personas were a boon for businesses when loyalty programs were in their infancy, but in today’s data-rich age, an evolved loyalty program will put that data to work in order to hyper-personalize individual customer experiences. And that’s what customers have come to expect. Recent research found that 91% of consumers are more likely to shop with brands who recognize and remember them well enough to provide relevant offers and recommendations. If your business has a loyalty program, you have the data that will allow you to provide exactly that, to the nth degree.

The first step is to integrate loyalty data with all the other customer data you collect, from all sources. This includes purchase history (both online and in-store), app usage, browsing behavior, and social interactions. Once you have all that data in one place, you can optimize personalized content based on that data across all touchpoints.

Here are just a few examples:

Connect Loyalty Data and Purchase History

Loyalty programs have traditionally been based primarily on spend amounts, i.e. spend $1.00 to earn 10 loyalty points. But how much a customer spends fails to take into account what they’re spending their money on. Imagine a long-term Designer Shoe Warehouse loyalty member who is repeatedly presented with loyalty deals on high heeled pumps and dress boots, despite the fact that data shows years worth of past purchases for casual flats exclusively. That’s a bad customer experience. But it’s one that can easily be improved simply by connecting what the user buys with the rest of their loyalty data.

Connected data will allow you to tailor loyalty offers to each individual customer’s purchase patterns — no matter how loyal a customer might be, there’s simply no point in offering them a deal on something they’ll never buy. When you customize your loyalty offers based on purchase history, your customers are far more likely to both appreciate and take advantage of them, solidifying their loyalty and positively impacting your bottom line.

Surface Loyalty Status Online and In-App

If you connect your loyalty program to your app (if you have one) and/or your website, and encourage your customers to browse while signed in, you will be able to present loyalty offers while the customer is shopping. A customer browsing a particular product line will be more likely to purchase if they are aware of things like, “Purchase this item to receive xxx bonus rewards points,” or, “Your Gold status entitles you to receive xx% off at checkout.”

Connecting your loyalty program with your website/app experience will also allow you to surface program benefits available to a user while they’re actively making a purchase decision. For example, a customer shopping for airline tickets would appreciate being reminded that, “Your gold status allows one checked bag per passenger at no extra charge.” Or a traveler booking a hotel room might book an extra night if you remind them that, “You’re just xx points away from Premier Loyalty status. Book three nights to qualify for a free upgrade and complimentary WiFi.

Tying it All Together in Emails

The perfect place to tie all that data together is in your emails. Promote your loyalty program in your marketing emails but if you already know the customer’s loyalty status — and ideally, you should — then use that real estate for personalized offers based on loyalty status, purchase history, or both.

Beyond marketing emails, you should also be encouraging loyalty program sign-ups in your transactional emails. Avoid annoying people who are already loyalty members by making that sign-up offer dynamic, to display an alternate offer to existing members.

Once your loyalty program data is sufficiently integrated, you’ll also be able to go a step further to personalize the content and offers presented in digital receipts and shipping confirmations based on both the customer’s purchase history and their loyalty status.

For example, if a customer buys an item online, a typical receipt email might include a selection of related products, such as ‘You might also like…’  But those recommendations are usually based on the product, not on the customer, which means the list can potentially include items already purchased. And let’s face it, no one likes being offered something that’s already hanging in their closet.

But if you have your user’s purchase history and their loyalty status combined, imagine how specifically personal those offers can be?

  • You already have [product A] and [product B] – buy [product C, D, or E] for 50% off by redeeming xx rewards points.”
  • “Exclusive to Platinum Loyalty Members! Buy [accessory A, B, or C] for [previously purchased product] and get [accessory D] free!”

Transactional emails are also the perfect place to surface loyalty status and upcoming rewards. For example, “You earned XXX points on this purchase. You’re just XX points away from Super Loyal status!.”

You might be thinking you already do this in your loyalty program emails. But loyalty emails are almost never personalized based on purchase history, just as transactional and marketing emails are rarely personalized based on loyalty status. Personalizing both types of emails, based on both sources of data, can put you that much closer to true, one-to-one personalization.

See how more personalization and better use of data can make all the difference with “Accelerate Your Marketing Efforts.”

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