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Taking a Data-Driven Approach to Loyalty Programs - Total Retail

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Chances are you belong to a customer loyalty program. A recent Mintel report shows that 90 percent of U.S. adults have at least one loyalty membership. But here’s the question: Have you ever used the program or benefited from membership? If your answer is a hard no, you're not alone. The average consumer belongs to over 14 loyalty programs, but more than half of the memberships are inactive.

This inactivity is driven by a combination of consumer frustration around program mechanics. Rewards may take too long to accumulate, or they expire too quickly, making them unusable. Many rewards lack relevancy; if a customer repeatedly buys an all-natural facial cream, for instance, you don’t want to “reward” her with a product that includes harsh ingredients.

However, a rewards program done right is a gift that keeps giving. An effective loyalty program ensures you retain customers, and retention is fundamental to any business growth model. High retention rates help steady revenue flow. And while you always want a robust pipeline of new customers, the cost of keeping existing customers is far less than acquiring new ones.

Data is the solution to architecting a loyalty program that will create brand love and loyalty at a time when customers are more open to switching brands than ever.

A Modern Loyalty Program

A data-driven approach to customer loyalty will help you gain a deeper understanding of your customers. Combining customer insights with research on the overall loyalty landscape will help you shape your modern loyalty program.

Typically, companies ramping up a loyalty program rely almost exclusively on basic transaction information like frequency of purchase. But that only scratches the surface. There's much more to loyalty than repeat purchases.

The most successful loyalty programs are built using a measurement framework that takes into account quantitative and qualitative data points capturing meaningful behavioral and emotional data. Combining this data with the demographic data your customers willingly share with you through their account profile will allow you to better recognize who your customers are, what motivates them, how you can meet their needs, and how to reward them.

So, what types of information should you include in your measurement framework? When you think about behavioral data, there are many meaningful data points to consider. For example, a customer who writes a favorable review, refers a friend, or consistently engages with your brand on social media may be just as valuable as someone who places multiple orders in a year.

Yes, it's easy to get lost in the vast amount of data available, so you need to determine what behavioral data is important to your business as you measure loyalty.

Emotional data, on the other hand, is much harder to track, but it's extremely valuable. Timely customer surveys asking for feedback on a brand experience after activities like a purchase, a customer service interaction or a return are a great way to get emotional information from the consumer. Website exit surveys can provide information about their online experience. Both of these qualitative information types can be reviewed along with quantitative behavioral data to better understand customer satisfaction.

Customer Personas and Segments

Once you’ve settled on your measurement framework and start collecting the necessary data, you can build out different customer personas and user segments. Personalization is key because what motivates one customer may not work for another. You can then begin to tailor your messaging, offers and rewards within your loyalty program accordingly.

You can, for instance, unlock exclusive merchandise for customers who value exclusivity. The sky is the limit when it comes to creatively rewarding customers. Take Nuun, a popular hydration solution that's seeing outsized results in its loyalty program. The brand created a tiered loyalty program that rewards buyers with points and encourages referrals, social media activation, and more. The program not only rewards with points; free shipping, samples of new products, and early access to Nuun-branded merchandise are some other popular offers.

No two customers are the same, so you need to leverage data to send the right messages and rewards at the right times. Once you figure this out you'll gain traction in your loyalty metrics and, more importantly, turn customers into brand loyalists.

John Kalinoski is the digital analytics and insights practice lead at LiveArea. Since 2004, he has been helping clients grow their businesses by leveraging data to make informed decisions.

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Taking a Data-Driven Approach to Loyalty Programs - Total Retail
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1 Response to "Taking a Data-Driven Approach to Loyalty Programs - Total Retail"

  1. I read your blog it's very nice and very helpful, I learn something new every time from this website, Thanks for sharing this information with us. I am also a blogger i guide people on App and Software Development. You can visit my blog here Retail Loyalty Programs

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