The Power of the Anchoring Effect on Pricing Models

Author: Charlotte Notaras       

The PeopleScience team performed an informal experiment at Experient’s 2018 e4 conference, Aug. 12–15 in Anaheim. We asked participants to write down the last two digits of their phone numbers, and then had them taste a red wine. They then wrote down how much they would pay for the wine for our first wine tasting. The group with phone numbers ending in digits between 76 and 100 were willing to pay three times as much for the wine as those in the 0-to-25 numbered group ($36 vs. $12).

We shared with the group the anchoring effect — the human tendency to rely too heavily on an initial (and often unrelated) piece of information when making a decision — and showed them the results. Then, we tried it again. This time we changed it up by using a white wine and asking for the last three digits of their phone number. We found exactly the same effect! The quartile with the higher digits in their phone number were willing to pay $38 versus $16 for the group with the lowest three digits.

The repercussions of the anchoring effect stretch far and wide, but an easy example to consider is retail pricing. When Apple released the iPhone X for $999, many people questioned who would pay that much for a phone. But it was Apple’s top-selling model each week in the second quarter of 2018. Between the release of the X and the subsequent releases of the XS, XS Max, and XR, Apple gave its consumers enough time to adjust their expectations around an iPhone’s cost. The newer phones were anchored around the iPhone X price point. Since people had gotten used to the idea of paying $999 for an iPhone, $749 for the iPhone XR seemed like a bargain, despite being twice the price of the average smartphone.

It’s not just prices people anchor to when assessing the value of an object or experience. With the iPhone, Apple created a unique experience that is difficult to compare to other phones. They’ve created a cult of devoted fans; some customers even justify spending up to 250 hours waiting in line to be the first to buy the newest Apple products. So, the next time you release a product related to your annual business event, look to Apple as a real-world example of how anchoring can not only boost profits but also create a loyal fanbase for your organization.


In 1974, Amos Tversky and Daniel Kahneman conducted an experiment in which participants were asked to spin a wheel that was labeled 0 to 100 — unaware that the wheel was rigged to land on either 10 or 65. Once the participants spun the wheel, they were asked whether the percentage of African countries that belong to the UN was higher or lower than the number on the wheel. Then, they were asked to estimate the actual percentage.

If people were not anchoring, we would expect to see an approximately uniform distribution of numbers between 0 and 100. Tversky and Kahneman found that participants who landed on 10 estimated the percentage to be around 25 percent, but those who landed on 60 guessed it was around 45 percent. Clearly, these participants did not know the answer (the correct answer is 100 percent). The important takeaway from this study is that the first number the participants saw biased how they answered the following questions, despite the number on the wheel being unrelated to the task.

Charlotte Notaras is a student at Princeton University who interned at PeopleScience.

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