Bias in the Spotlight: Anchoring

By Crawford Hollingworth and Liz Barker

People find it hard to make decisions without a reference point. It’s human nature to look for such reference points – or anchors, as they’re known – to help give us context or understanding. It is also known that we often tend to then rely too heavily on an anchor, or to anchor on one trait or piece of information, often in the immediate context, when making decisions.

But why do people do this?

Behavioural science research suggests that anchors affect our decision making in a whole variety of different contexts. This ranges from placing bids on Ebay or choosing an item on a menu to charitable donations and house valuations.

Furthermore, anchors themselves can vary. We might anchor to a variety of different reference points, including:

  • Prices
  • Similar products
  • Dissimilar products
  • Context e.g. the general feel or ambience of the environment
  • Extremes
  • Expectations
  • Rules of thumb
  • And even to completely random numbers, albeit subconsciously

Two primary ways of anchoring that impact decision making exist:

  • Conscious adjustment: The first is through deliberate, reasoned adjustment using our rational, conscious, logical ‘System 2’. For example, when choosing wine in a restaurant we might look at the most expensive & cheapest wine on the list and make our choice by adjusting from those prices. So, with the most expensive bottle priced at £30, and the cheapest at £10, we might choose a £25 bottle
  • Unconscious priming: The second cause is through priming effects. This is when we subconsciously anchor to an often-unrelated number. This phenomenon draws on our automatic, subconscious System 1. For example, when bidding in an auction we might subconsciously anchor to a number we recently read such as a bus number or phone number. If the number is high, it increases the bid. If it’s low, it subconsciously decreases the bid. If the number we’re exposed to is high – e.g. 92 – we might bid £50 in an auction. However, if the number we’re exposed to is low – e.g. 20 – it’s is more likely to generate a lower bid of £25

One experiment that showed how influential anchoring effects can be looked at credit card repayments. Researchers found that the amount we repay on our credit card bill can be influenced by the relatively low number of the minimum payment in comparison to the full amount owed. People who had seen the minimum payment, paid off only 23% of their balance owed. Comparatively, those who were only shown the total balance, paid off 40% of the balance owed.

Another well-known experiment illustrates the effect in a different way. Try to guess, within 5 seconds, the value of the following arithmetical expression. 5 seconds. Ready?

  • 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8

What did you get?

In the study, asking this exact same question, designed and tested by behavioural science pioneers Daniel Kahneman and Amos Tversky:

  • Students shown “1 x 2 x 3 x 4 x 5 x 6 x 7 x 8” made a median estimate of 512
  • Students shown “8 x 7 x 6 x 5 x 4 x 3 x 2 x 1” made a median estimate of 2,250

The motivating hypothesis was that students would anchor to the first few numbers then adjust upward. In case you were wondering the right answer is 40,320.

So what does this all mean?

In marketing, see if you can identify what the common anchors are for your category. What do your customers use as a reference point when choosing what to buy?

Next in the series…

Every three weeks The Behavioural Architects will put another cognitive bias or behavioural economics concept under the spotlight. Our next article features confirmation bias.

By Crawford Hollingworth and Liz Barker, The Behavioural Architects

Crawford Hollingworth is co-Founder of The Behavioural Architects – an award-winning global insight, research and consultancy business with behavioural science at its core, which he launched in 2011 with co-Founders Sian Davies and Sarah Davies.

Liz Barker is Global Head of BE Intelligence & Networks at The Behavioural Architects.



System 1 & 2


Optimism Bias

Availability Bias

Inattentional Bias

Change Blindness