Use ‘was 25% higher’ instead of ‘now 20% lower’
To make discounts appear larger and increase sales, use the discounted price ($2/$8 = 25%) instead of the original price ($2/$10 = 20%) to calculate the same $2 discount.
Today’s research gives us a powerful way to increase the attractiveness of promotions.
Warning: this can be easily misused to harm vulnerable consumers (e.g. overconsumption, unhealthy eating). Please use it ethically and responsibly.
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Calculate discounts using the discounted price to increase sales
Impacted metrics: Customer acquisition | Customer spending
Channels: Promotions | Pricing
Recommendation
You can make a promotion or discount more powerful by calculating the discount % based on the discounted price (e.g. $443.63/$755.37= 59%) rather than the original price ($443.63/$1,199.00= 37%), even when the discounted amount is the same ($443.63).
Phrase it as “was 59% higher” instead of “37% off”.
You can also use it in other situations, such as product features “was 25% smaller” rather than “now 20% bigger”
Effects
Calculating the discount based on the discounted (vs original) price makes it seem larger. Larger discounts lead to larger sales.
When discounts are small (e.g. $1), the effect is negligible because the difference between using the discounted price as a base (11%) and the original price (10%) is small.
The effect is weaker for people that have high numeracy skills (i.e. are good at math). It’s stronger for consumers that are typically less numerate (those who are older, less educated, and with lower income).
The effect can be applied beyond pricing. For example, instead of saying a new laptop is 30% lighter, you could say that the previous model was 42% heavier.
Based on previous research, there are also other ways to make a discount feel larger:
“Pay 80%” vs. “20% off”
Putting a sale price to the right of (vs. left of) original price
Stacked discounts (“25% off, then 20% off”) rather than single discounts (“40% off”)
Why it works
We are more likely to buy when a discount is, or seems, bigger.
Typically, we are attracted to numbers when judging an offer (e.g. 20%, $120), and pay less attention to the surrounding text.
We usually think with our so-called “System 1”, which makes fast, almost automatic decisions and is more prone to biases like this one. This is especially true when we’re buying small everyday items like groceries. To think through and calculate the true meaning of an offer means engaging our “System 2” deliberative thinking, which requires much more effort and energy, and might not be worth it. (see Daniel Kahneman’s Thinking, Fast and Slow).
Limitations
The experiments are robust and measured actual sales. However, they were run only on physical products. The effect should extend to services and digital products, but this was not directly tested.
The researchers did not test if the effect persists at very high discounts that go over 100% (e.g. “now 67% lower” vs. “was 200% higher”).
Some people could feel deceived by this discount framing and develop negative feelings towards a brand. This was not investigated.
If many companies start using this practice, the effect is likely to become reduced.
Companies using this
Very few or no companies seem to be using this promotion strategy.
Steps to implement
Reframe your offers to “was X% higher” instead of “now Y% lower”.
Think of whether you can apply this different framing to your product or service features as well (e.g. opening an account is 60% slower with our competitor).
Study type
Field and lab experiments, Sweden and United States
Source
Guha, A., Biswas, A., Grewal, D., Verma, S., Banerjee, S., & Nordfält, J. (June 2018). Reframing the discount as a comparison against the sale price: does it make the discount more attractive?. Journal of Marketing Research, 55(3), 339-351.
Affiliations
University of South Carolina, Wayne State University, Babson College, Lawrence Technological University, Wayne State University, and Stockholm School of Economics
Remember: This research 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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