How to use rewards data to improve your customer experience

As eCommerce retailers find it more time-consuming and expensive to generate new customers, they are increasingly looking to their loyalty programs. And customers are certainly eager to sign up. In 2017, there were 3.8 billion memberships of loyalty programs in the US alone.

But overall growth has also slowed. Many retailers are struggling to retain members. They’re also finding it difficult to prompt them to take meaningful actions like make purchases and send referrals.

So what’s the solution?

One option is to use data derived from your rewards program to improve the experience of those who have signed up.

By leveraging a number of data-points, you can build a program that boosts engagement while also driving a number of key metrics, like purchase frequency, average order value, referrals, lifetime value and more.

In this post, we’re going to identify the most important types of data and how to use that data to create meaningful changes.

What data can you generate from a rewards program?

 

  • Segmentation dataThis is data about the demographic makeup of your loyalty program membership, and encompasses age, location, marital status, gender etc.
  • Reward-specific dataWhich rewards, promotions and giveaways are most popular? Determining which products and voucher codes are redeemed most often is usually a relatively simple process.
  • Membership activityActivity refers to the degree to which your members are interacting with your program. How many points have they redeemed? How many have been left sitting? How many vouchers have been used? This data is immensely useful for deciding which members to prioritize.
  • Personal detailsThis is individual data that you have extracted on the basis of membership of your loyalty program. It can include birth dates, reward preferences, specific location and so on.

 

So how do you get started? Here are four data-based ways to improve the customer experience of members of your loyalty program.

1. Segment rewards by activity and demographics

 

Segmentation works for both VIP members, who have high purchase frequency and regularly redeem their points, and for members that do not exhibit a high level of engagement.

For your top members, offering high-value rewards will encourage engagement with your program over the long term. By picking and contacting certain groups, and even individuals, for exclusive rewards, you can provide the best possible incentives in a cost-effective way.

Showcasing unique rewards and giveaways via email to members that are inactive, under-engaged or sitting on a large number of unredeemed points will also further increase retention among those most likely to drop off. It’s usually viable to allocate extra resources to this segment because they represent a high-potential group – they’re existing customers who have already signed up – with the greatest contribution to your overall churn rate.

Segmentation can also work effectively when unique promotions and rewards are designed on the basis of demographic information like age, location, marital status etc. By tailoring reward initiatives to meet the unique preferences and needs of specific sections of your customer base, you are much more likely to drive action (and thus engagement). Amazon used this strategy to immense success by targeting students for its Prime program.

2. Create highly personalized initiatives

Personalized reward initiatives

 

Personalization is a hugely under-leveraged strategy. It’s one thing to include a personal name at the beginning of an email. It’s another to encourage members to enter the birth dates of family members at sign-up and use that information to send tailored discounts and offers in the run-up to the big event.

Most managers responsible for running loyalty programs don’t take advantage of the huge array of personal details at their disposal. Customer experience can be dramatically improved when you tailor email promotions and rewards to include personalizaton; think relevant buying holidays (such as Mother’s or Valentine’s Day), personal celebrations, specific genders, locations and so on.

We’re not talking about general demographic or segmentation data here, but rather individual-specific details that you can use to automate highly targeted promotions or reward offers.

An added benefit of sending these highly personalized rewards is that they will increase trust over the long term. If you send your customers free points via email on their birthday or favorite shopping holiday, particularly when your competitors don’t, you’re much more likely to stand out.

3. Tailor your program to preferred platforms

Tailor your programs

 

Which platforms are your members using to check and redeem their points? Data about the kinds of devices and channels your customers prefer can be useful for deciding which platforms to prioritize.

If, for example, the majority of your eCommerce visitors shop on mobile, it makes sense to make your loyalty program directly available through mobile devices. Research by Exodus shows that 31% of consumers use an app to manage their loyalty rewards, so there is clearly a preference for certain access-points.

Most loyalty program managers take an omni-channel approach. And while this is certainly a laudable strategy, it usually falls short. The key is to hone in and optimize those channels that are most effective at engaging your membership.

4. Build feedback into your program

Build program feedback

 

Do you have any feedback mechanisms in place to determine unserved needs and pain points among your members?

Indirect feedback exists in the form of data about your most popular rewards and promotions. You can use this information when creating new rewards or putting together future promotions. If, for example, most members swap their points for cash-back rewards, then you can offer variants and similar offers going forward.

But it’s also important to utilize other ways of collecting feedback. How often do you send email surveys to your loyalty members or include survey questions on your rewards pages? Are you listening to customer service recordings? Do you undertake user testing?

This is one of the big reasons that retailers often experience high rates of churn. They apply a rigorous set of methods to pinpoint customer needs and pains related to the buying process but none to the customer experience of their loyalty program members, where a unique set of issues are often present. If you want to boost retention, it’s vital that you listen closely to your existing members.

Conclusion: Loyalty programs are a powerful but underutilized tool

Loyalty programs are so popular among eCommerce retailers because they work. But it’s also vital to keep in mind that the market is incredibly saturated. The average American is a member of over 14 programs.

As ad costs soar and search engine traffic becomes scarcer, holding onto your existing customers is ever more important. This is why a data-driven approach to improving the customer experience of your loyalty program will almost certainly be relevant.

On the one hand, it will enable you to generate concrete insights for reducing churn. On the other, you have an opportunity to create a key competitive advantage by building a rewards program that is genuinely based on customer needs and preferences.

Now, time to start mining that data.


This is a guest post written by Skubana. Skubana provides an omni-channel eCommerce platform for unifying all aspects of your store’s operation. Skubana’s tools make it easy to manage inventory and shipping, automate laborious tasks and generate meaningful insights from on and off-site data.

 

The post How to use rewards data to improve your customer experience appeared first on The Marketing Automation Blog.

Reblogged 3 months ago from blog.dotmailer.com