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Additional Rules

If your loyalty rules engine is sufficiently flexible and comprehensive, the assignment of points in this way can be automated.

You also need the freedom to vary these values as needed. Across the list of examples above, few of the behaviors are equally profitable every time or all the time – so the amount offered should vary with the incremental value created. Each action might be worth more or less on Tuesdays compared to Saturdays.

In a points-based program, a base earning amount should be set so customers earn at least an expected amount of value, but you can then introduce bonus rewards to surprise or recognize customers when they take actions that help your business.

As suggested, a business may know that if a customer carries out ‘action A’, they are 80% more likely to carry out ‘action B’. Whereas, if customers don’t carry out ‘action A’, the likelihood they will carry out ‘action B’ is only 10%. Therefore, you might offer fewer points for ‘action B’ and allocate the value associated with ‘action B’ to ‘action A’ – because you want to get the customer on a specific path.

To summarize, the desire or priority to sell specific products or service changes over time, so points-based incentives can be used to create more urgency or motivation among customers if optimized for the specific context of a potential sale. ‘Context’, as described in the next section, is constantly changing, and incentives should change as well to optimize medium-term ROI.

In a program only incentivizing transactions, giving a constant amount of points is nothing more than cashback – and usually less rewarding than the value that disloyal customers can get via third-party cashback or affiliate schemes.

If a brand only offers 1% in points across all products, customers not only come to expect the modest benefit as routine; they also rarely change their behavior to earn more.