Lately, I’ve been writing about customer loyalty. Customer loyalty is when customers transact with your company again of their own free will. First I discussed how the growing trend of self-service automation affects customer loyalty. Then, I pointed out the fact a “loyalty program” shouldn’t be the lynchpin of a customer loyalty strategy.
Many businesses confuse loyalty programs with reward programs. A reward program is a customer retention strategy, not a loyalty strategy. You entice people to transact again with your company based on a reward or an incentive.
Loyalty programs trump reward programs. But if you use reward programs, you must understand how they work and how they can be most effective.
Today, we’ll cover some of the most common and effective retention strategies. Future columns will address more advanced ideas in loyalty programs (and how they intertwine with my other favorite topics: personalization, metadata, and mass customization).
The Skinny on Skinner
B. F. Skinner is probably the granddaddy of reward programs (a.k.a., reward schedules). His rewards were given to less-discerning creatures, of course (usually mice and pigeons). But his research on how animals react to positive and negative reinforcement is extremely important in understanding how incentives work and how effective they are.
In his most well-known experiments, Skinner placed a mouse in a box with a lever. When the mouse pressed the lever, food came down a chute into the box.
Skinner categorized his rewards into the following categories:
- Continuous reinforcement (CR)
- Fixed ratio and variable ratio (FR/VR)
- Fixed interval and variable interval (FI/VI)
Continuous reinforcement is a reward that always occurs. Every time the mouse presses the lever, food comes. In the business world, a reward like this is “free shipping with every order” or “everyday low prices.”
Fixed Ratio/Variable Ratio
Ratio rewards are based on repetition. With fixed ratio, the reward occurs precisely every X times. So every 10th time the mouse presses the lever, food comes down the chute. This is akin to SUBWAY’s “buy 12 feet, get one foot free” or similar punch cards.
The variable ratio version is similar, but X isn’t a constant number (though it averages to a constant number). A lottery might give winning odds of one in a million. It isn’t exactly one in a million every time, but it is on average. You may never win. But you keep playing because you have an equal chance of winning each time.
Fixed Interval/Variable Interval
Interval rewards are based on time. In the fixed version, no matter how many times the mouse presses the lever, food comes out only at a specific interval, such as once every 10 minutes. In the variable version of our example, food comes out approximately every 10 minutes, but not exactly. Sometimes it’s 9 minutes, sometimes 11, but it always averages to 10.
GNC has a special members’ discount the first week of every month. This is a fixed interval reward, as are a store’s annual sale and a daily lunch special from 11 a.m. to 2 p.m. The variable version includes radio contests that grant prizes “sometime this hour.” You don’t know exactly when, but basically it’s every hour.
A related reward schedule is the token economy, which is also commonly used for rewards or incentives. In a token economy, points (or something similar) are accrued, then traded for goods. Think arcades that give you tickets that can be exchanged for a number of prizes. Or airlines’ point programs. Token economies exhibit traits similar to fixed ratio rewards, though rewards can vary based on the number of points used. Because you can buy different rewards based on varying number of points, there’s always the potential of getting a reward.
Measuring Reward Effectiveness
To understand these reward schedules’ effectiveness, use these three key measures:
- Learning curve. How quickly does the user understand the reward, and how quickly does his behavior change because the reward is in effect? In the mouse experiments, this is the time it takes the mouse to realize food comes down the chute every 10 presses and how long it takes the mouse to alter its behavior to optimize its energy and get as much food as possible.
In the business world, the learning curve shows us how popular a particular reward schedule is based on how consumers’ behavior changes to optimize getting the reward. It’s a measure of how quickly the promotion takes effect.
- Frequency. Frequency shows how often the user interacts with the system when the reward is in place. If the food only comes down the chute once every 10 minutes (regardless of presses), frequency would detail how often the mouse presses the lever during that 10 minute interval.
Frequency is important because it shows people eat at SUBWAY more frequently when their punch cards are almost full. They don’t feel the need to go back so quickly when they must start a new punch card. Their frequency is a “scallop” when plotted on a graph: intensity increases as the reward gets close, then dips after the reward is given.
- Decay. Perhaps the most important metric, decay describes the subject’s behavior once the reward ends. It measures how many times the mouse presses the lever once food is entirely stopped. How many customers do we retain after the promotion or reward ends?
If you offer free shipping on every order during the Christmas shopping season, how many of those customers will still shop with you after the shipping promotion ends? Is that number more or less than had the promotion been something else? Decay is important because a good promotion works to retain customers, not just ramp up frequency when the promotion is on.
Next: how these reward schedules operate in the real world, which work better, and when they should (and shouldn’t) be used.
As always, I am curious to know if the topics I cover are interesting or useful to people. Let me know!
Until next time…
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