What is customer loyalty?

Customer loyalty – every retailer wants it, but what does it mean? Are the customers who spent the most last year or the customers who bought something during the last three months going be the most loyal over the next year? What if they made 3 purchases last year, but only around the holidays? And, what does it mean to have “churned?”

As customer buying patterns shifted during the pandemic, customer retention became a hot topic, and rightly so. A deeper analysis of almost any retailer reveals that a small number of customers will deliver a disproportionately large percentage of revenue. Winning 5 “average” new customers often has less impact on the bottom line than losing just one of these “Loyalist” customers. Surprisingly, when most retailers think about retention, they think about winning back “lapsed” customers who have not bought in a very long time. They fail to identify, monitor, nurture, and protect the loyal core of their revenue base. Typically, it’s because they don’t have a way to measure future loyalty precisely and reliably.

Without precise, accurate measures for future loyalty, it’s hard to tell when a loyal customer who may have purchased recently is actually starting to slip closer to inactivity and churn than it appears. It’s also impossible to know how best to differentiate and allocate marketing resources among the masses of one-time buyers or dormant customers even though they are not all equally likely to buy again. If you did have a precise, accurate way to measure loyalty for each customer, not only could you invest and speak to customers in ways appropriate to their loyalty and lifecycle stage, but you could spot early warnings when a timely intervention could have reversed a negative trend before the churn risk got too high.

Loyalty Builders measures customer loyalty on two independent dimensions:

  • Predicted future value
  • Risk of churn

The first dimension is potential future value, a probability-weighted spend prediction over a time period in the future. Past spending is a factor in making this prediction, but if it were the only factor, the predictions would not be very accurate.

The second dimension is risk of churn, which is the predicted probability that the customer will make no further purchases since their last purchase. That probability may be low for many customers, but subtle differences matter in the long run. And when the risk creeps up above 50%, alarms should go off.

Investments in loyalty and retention marketing are essential to a healthy retail business and usually deliver higher returns than acquisition marketing. That does not mean stop investing in acquiring new customers. Rather, don’t forget to invest wisely in their loyalty once you get them.

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