Increase customer lifetime value 29.5% with “Buy 10 get 1 free”
A simple loyalty reward program “Spend $100, get $5 free” increased customer lifetime value by 29.5%. 80% of the increase is due to less customers leaving.
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Surprisingly, research has repeatedly found that simple “Spend $100 and get $5 off next time” loyalty programs don’t actually make people spend more (the effect is minimal).
They do slightly increase how often people return to buy, but it’s much less than you’d think (e.g. only 2% revenue increase in one study).
Because of this, these simple loyalty programs have somewhat fallen out of fashion in favor of more complex tiered loyalty programs, where rewards increase as you reach higher thresholds (e.g. airline miles statuses, Booking.com’s Genius levels).
But today’s research finds that these simple “Buy 10, get 1 free” programs do indeed have a strong positive effect. Albeit one that’s often harder to measure for most many businesses.
They stop people from leaving you.
P.S.: What do you think of the emojis in each subsection (e.g. 🧠 Why it works). Emoji overkill or they help the sections stand out?
Use simple loyalty rewards to increase customer retention
Impacted metrics: Customer lifetime value | Purchase frequency
Channels: Loyalty rewards
For: Mostly B2C
Implement a simple loyalty reward program (e.g. “Get a $15 voucher for every $150 you spend) as an easy way to increase long-term customer retention and lifetime value.
An uncertain loyalty reward will likely make this even more powerful (e.g. there’s a 50% chance you’ll get either $5 or $15).
Previous research and this study found that simple reward loyalty programs (e.g. “Collect 10 stamps and get a free coffee”) aren’t very effective at increasing spending or purchase frequency.
More complex tiered reward programs (e.g. “Fly 150,000 miles and become a Platinum tier member”) are different from simple reward programs because they rely strongly on the psychology of belonging to a higher status.
This study discovered a strong undiscovered benefit of simple loyalty rewards. The introduction of a $5 coupon reward for every $100 spent in a chain of men’s hair salons (average sale: $21) led to a projected customer lifetime value increase of 29.5% over 5-years:
80% (23.6%) of this increase was caused by fewer regular customers leaving
20% is statistically unexplained but appears to be mostly due to a slight (4.1%) increase in the frequency of visits
Surprisingly, the effect is strongest for customers that are most and least loyal, and weakest for moderately loyal customers.
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🧠 Why it works
If we’re part of a loyalty program (no matter how small it is), we feel more connected to that company.
When we see that a company has a loyalty program, we may feel more positive towards it because we feel that they are investing in their customers.
An additional possibility is our quest for ‘completeness’. For example, if we have only 4 stamps left to reach 10 and complete the card, we want to reach that - and it could even be more satisfying than the reward itself.
The study focused on a chain of men hair’s salons, therefore:
The frequency of purchases is unlikely to change much due to incentives (people get a haircut when their hair grows back)
Likewise, there are limited upselling options at a barber. Customers mainly visit to get a haircut
However, previous research appears to back up the smaller than expected effect on both
The results are likely to generalize to other retail and service businesses. However, it may not extend to very different business models, such as those that rely on monthly/yearly subscriptions (e.g. SaaS).
The estimate of 29.5% increase in customer lifetime value over 5-years is a projection of the study’s model rather than actual measured results.
The study did not investigate in depth what drives this effect (e.g. through additional lab experiments). The Why it works section is what’s most likely based on previous research.
🏢 Companies using this
Simple, non-tiered, loyalty rewards are used primarily by grocery businesses (e.g. Carrefour) and local businesses like cafes (including big chains like Starbucks), where purchases are regular and frequent.
Companies that have less frequent sales (e.g. Fashion, B2B services), rarely use such rewards. This could be an underused opportunity.
The main users of tiered loyalty rewards tend to be in the travel industry, such as airlines (e.g. Delta Skymiles), car rentals, and hotel chains.
⚡ Steps to implement
Explore what kind of reward would make most sense for your business. For example:
Freelance designer: 2 hours free for every 20 hours hired
Clothing brand: Get $20 off after 3 purchases of $50 minimum
Gift shop: Spend $200 in a year and get a free mother’s, father’s or Valentine’s day special gift
Calculate what would be financially viable. You can build the cost into your prices.
Make it easy and free to join. For example, require only an email address, rather than an extensive signup form.
If you already have a customer database, automatically enroll customers into it, regulations allowing (e.g. GDPR).
Decide how rewards are redeemed:
Manually (e.g. insert a coupon code at checkout). Many customers will not redeem them, so you can save costs
Automatically (e.g. the system deducts a discount from the next purchase). Customers may feel better towards your brand if they get an unexpected reward
Remember that results will be hard to measure, as the effect is on losing less customers over several years (one fourth less, in this study), so don’t despair if you don't see an increase in sales because of the program - you shouldn’t expect one.
🔍 Study type
Market observation (of 5,544 customers of a chain of men’s hair salons). United States
Gopalakrishnan, A., Jiang, Z., Nevskaya, Y., & Thomadsen, R. (March 2021). Can Non-tiered Customer Loyalty Programs Be Profitable?. Marketing Science.
Jones Graduate School of Business, Rice University; Wharton School, University of Pennsylvania; and Olin Business School, Washington University in St. Louis. United States
Remember: Because of the groundbreaking nature of this paper, it could be disproven in the future (although this is rare). It also may not be generalizable to your situation. If it’s a risky change, always test it on a small scale before rolling it out widely.
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