Could Projecting Your Preferences onto Prospects Make Your Market Prediction Inaccurate?

You may have heard the phrase “If you build it, they will come.” This assumes that the marketeer knows best and the market will recognize this and come to buy. If you, the marketeer, are in love with a product, it’s natural to project that love onto your target audience. However, it may be the right product at the wrong time, or just a product that doesn’t meet customers’ needs.

Marketing managers are only human, and humans have their own personal preferences. These preferences can become a problem, however, when they project them onto a target market that may or may not share their preferences. As a result, they may miss out on capturing sales for a product that really resonates with their audience, while they focus on marketing something that is not as appealing to their prospects. This tendency is called the false consensus effect, or FCE. 

Why Your Knowledge Could Be Making the Problem Worse

How can you avoid FCE in your marketing? The way you intuitively have been dealing with it may actually be making it worse. Krueger and Clement came to the conclusion that FCE is an “ineradicable bias,” and that it persisted even when decision makers were educated about the bias, provided with feedback on the accuracy of their decisions and statistical information on the target group. However, new research from Walter Herzog and colleagues shows that the strength of preference certainty is a moderating influence that marketeers should take into account. 

The first part of Herzog’s study examined whether marketing managers were aware of FCE and if so, whether they thought it was an important bias to counter and how they tried to counteract its effects. It turned out that the participants were well aware of the FCE with 82% identifying it as something that impacted their predictions of consumer preferences. Of these, nearly all (92.7%) were aware of FCE taking place among other managers in their companies and 86.6% said that it was something they did themselves. Respondents considered FCE to be a major problem, ranking the ability to separate personal from consumer preferences as the most important skill for marketing managers.

The study then asked the respondents to indicate which of a list of anti-biasing techniques they use to avoid the unintended consequences of FCE. Three quarters of them said that they use the simple strategy of trying to ignore their own preferences when predicting consumer behavior. To test whether this is an effective strategy, the researchers designed a series of four experiments.

The Effectiveness of Suppression on FCE Depends on Preference Strength

The first experiment asked marketing managers to familiarize themselves with a new product, a virtual reality headset, and all of its benefits and features. Then, researchers asked them to rate how much they liked the product, how strong their preference was and how certain they were that their opinion of the product would be the same in three weeks. The participants were then told to assume the role of the product manager and predict how target consumers would evaluate the product. When these responses had been recorded, they were asked if they had tried to suppress their own personal preferences when making their prediction.

Herzog found that personal preferences had a strong correlation with the managers’ predictions of consumer preferences, indicating a high prevalence of FCE. On average, preference suppression did not reduce FCE, however, there was a significant difference between those with a strong preference certainty and those who were less sure about their preference. Managers who felt certain about their preference were much more effective at suppressing their personal preference and reducing FCE. On the other hand, those who were unsure about their own preference and tried to ignore their bias ended up having a much higher amount of FCE. 

Why Does Low Preference Certainty Increase Bias?

The third experiment focused on explaining why preference certainty has this effect on FCE. Managers were exposed to AI products and their preferences and certainty in them were recorded. Then they were told to imagine that they were responsible for advising a company’s board about whether to invest in launching specific AI-based apps and asked how they would advise the board and try to convince them. Finally, they were asked how much time, energy and thought went into trying to suppress their own preferences when making their recommendation.

When they had a low preference certainty, they reported that they had put significant effort into trying to suppress their own preferences, but this strategy backfired and produced more FCE, while the opposite was true for the high preference certainty group. The theory is that those unsure of their preference focused so much on their own preferences in order to control for them that they actually increased their bias. Those with a strong preference spent less time overthinking and were able to suppress their bias much more effectively.

A More Effective Strategy for Low Preference Certainty

When asked to actively suppress their preferences, those who had a strong preference were successful, while those on the fence ended up reinforcing their bias. Since we as marketeers intuitively try to suppress our own bias, we are unintentionally reinforcing it when we aren’t sure. A better strategy when this is the case is to go with our gut. Overthinking it makes it worse.

So the next time you are asked to predict consumer reaction to a campaign or product, consider how certain you feel about its success. If you are very certain, suppressing your personal preference can successfully control for your bias. But if you are uncertain, taking a more intuitive approach will give a more accurate prediction of market behavior. Still not sure? Try paying attention to market research and getting the opinions of colleagues to get a fuller picture.

Take-home points

• Marketeers tend to project their own preferences onto consumers.
• Preference certainty indicates whether preference suppression is the way to go.
• Intuitive approaches are recommended when preference certainty is low.
• Suppressing personal preferences is recommended when preference certainty is high.
• Suppressing personal preferences may backfire when preference certainty is low.