$2,111 is better than $1,999 (+ Pricing Playbook 📘)
For prices with 4 figures or more, in any currency, repeat the last 3 digits and use a low number (e.g. $4,111, not $3,888). The price will feel more discounted.
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P.S.: Here are two key insights I just used above (which will of course be among those covered in the playbook):
When surveyed, 78.4% of managers thought it would be better to use a price of 1,999 Turkish Lira rather than 2,111 TL.
Their reasoning was that 999 makes the product seem more discounted and affordable.
They were wrong.
In 4 or more figure prices, use 3 repeated low digits as the final numbers to make them seem cheaper
Impacted metrics: Customer acquisition
Channels: Pricing | Promotions
For: B2C. Can be tested for B2B
Research date: January 2022
To make prices or discounts of 4 or more figure products seem cheaper (in any currency, $4,000, ¥2,000, ₹8,000), use 3 repeating digits as the final numbers.
Choose repeating digits that are as low as possible. Preferably 1 (e.g. $3,111), but other digits below 5 will also work (e.g. ₹8,222).
People process prices with 3 repeated final digits (e.g. $1,999, $2111, $25,222) in “chunks'' of the repeated digits (e.g. 9s, 1s, 2s).
The lower the value of the repeated digits (e.g. 1 vs 9), the more people perceive the price to be discounted. That means that $2,111 or $3,222 appear more discounted than $1,999 or $3,888.
The effect only applies to
Prices of at least 4 figures (in any currency) with the last 3 final digits repeated
Non-decimal prices. For decimal prices (e.g. $19.99 vs $21.11), the left-digit bias effect overrides this effect ($19.99 is perceived as more discounted)
For example, in one of a series of 5 lab and field experiments:
A Google Ad for a Philips Vacuum Cleaner received an 18.9% higher CTR (clickthrough rate) when its price was 2,111 TL (Turkish Lira) vs 1,999 TL
🧠 Why it works
When prices have 4 or more digits, we pay less attention to the first digit, which eliminates the left-digit bias of just-below pricing (e.g. using $19.99 instead of $20).
We also pay more attention to repeated digits compared to random numbers, because we find these repetitions unlikely.
So when our attention is on the 3 repeated final digits, a lower repeated digit makes us feel that the price is lower.
The study did not test repeated 0 digits in prices (e.g. $2,000). This round figure is likely to have important implications that go beyond looking cheaper. It may for example signal stability and completeness, or could work better for hedonic products (e.g. fashion).
If repeating digits attracts more attention, it might be beneficial to use repeated 3 digit chunks at the start of the price (e.g. $1,115 or $2,229). We don’t know if this is the case.
Chunks of more than 3 repeating digits (e.g. $21,111) do not show this effect. It’s unclear why.
🏢 Companies using this
This technique does not seem to be used in practice.
Nikon and Canon often list their top-of-the-line professional cameras for $5,999. Panasonic lists one of their mirrorless cameras at $1999.
Out of 200 random cars and motorcycles on eBay, about 20% of prices with 4 figures ended with repeating 9s. Media Markt, the electronics retailer, has a similar ratio for TV prices.
⚡ Steps to implement
When promoting a 4 or more figure product, use low (preferably 1) repeating 3 digits as the last digits.
Given that this technique increases perceptions of discounts, use it in line with your brand. If your brand is premium and does not offer discounts or only does so rarely, limit or avoid its use.
🔍 Study type
Lab and online experiments, and a field experiment (A/B test of a Google Ad from May 2020 to May 2021).
Are 1-endings the new 9-endings? An alternative for generating price discount perceptions (January 2022). Journal of Retailing and Consumer Services.
Kivilcim Dogerlioglu-Demir, Sabanci University
Ezgi Akpinar, Sabanci University
Zeynep Gurhan Canli, Koç University
Cenk Koçaş, Sabanci University
Remember: This is a new scientific discovery. In the future it will probably be better understood and could even be proven wrong (that’s how science works). It may also 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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