How to be an unbiased marketer
Marketers confuse their personal preferences with customer preferences (e.g. I like this feature, so will my customers). Actively fighting it can remove this bias, but not always.
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You’ve probably found yourself countless times discussing: “Would our customers like X?” (e.g. a new feature, a new product).
Assumptions about customers’ preferences are our daily life as marketers. Not everything can be constantly tested or researched.
But how far off are we when we make these assumptions?
The good news is that experienced marketers (i.e. you) are usually aware they risk being biased: our personal preferences are unlikely the same as our customers’, so we suppress them.
The bad news is that to avoid this bias, we often overcompensate to the other extreme. We assume customers’ preferences are completely different from our own, even when that’s not the case.
The result? Bad decisions and tons of wasted resources (e.g. off-target campaigns, wasted product development).
When surveyed, 83% of managers said they wanted to read a management summary of an academic article on how to avoid this bias effectively.
Well, here you go ;)
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Beware of confusing personal preferences with customer preferences
Impacted metrics: Decision-making
Channels: All channels
For: Both B2C and B2B
Tip type: New research (April 2021)
To more accurately predict your customers’ preferences about a new feature, product, or campaign:
Keep in mind that we tend to confuse personal preferences with our customers’ preferences, so we need to actively react to this bias
If you’re certain of your personal preferences (e.g. I really don’t like this), actively suppress them and force yourself to ‘think as the customer’
If you don’t have strong personal preferences (e.g. I’m not sure I like it, but it could grow on me) don’t try too hard to suppress them if you’re unsure you’re being biased - doing so would backfire. Instead, let them guide you
This method greatly improves the accuracy of ‘gut feeling’ decisions about customer preferences.
Still, whenever possible (and reasonable), you should make decisions based on hard data instead (e.g. market research, MVP testing).
Marketers have a tendency to project personal preferences onto target customers (e.g. of course my customers also love Clubhouse!).
To fight this bias, 3 out of 4 experienced marketers actively suppress their personal preferences, to more clearly focus on and predict the customer’s actual preferences (e.g. will they enjoy this new campaign?).
The effectiveness of this method varies strongly when predicting customers’ preferences:
When marketers had a strong personal preference, suppressing their preferences decreased prediction errors by 60%
When marketers had a weak personal preference (i.e. they weren’t sure if they would change their mind), trying to suppress their preferences backfired. It increased prediction errors by 54%
When marketers with weak preferences abandoned efforts to apply this method when they weren’t sure if they were being affected by this bias, their prediction errors disappeared
(The effect of marketers trying to suppress their personal preferences when they were uncertain or certain of their preferences - Click to zoom in)
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🧠 Why it works
Suppressing our personal preferences is the most commonly used method because it’s intuitive, easy, and doesn’t require additional resources (e.g. recruiting a focus group).
When we’re unsure of our personal preferences:
We instinctively still try to suppress them
But we’re unable to tell whether our personal preferences affect our customer predictions.
So we ‘blindly’ assume our intuition is wrong and overcorrect something that didn’t need correcting
When we’re sure of our personal preferences we’re mostly able to tell which are our personal preferences and which are those of the customer, so we can suppress them successfully.
Some marketers may be unaware that they are confusing their personal preferences with those of their customers. More likely, many forget about this bias in the rush of making a decision. These corrections only work when marketers are aware of this bias.
The study didn’t test the effectiveness of this method against others (e.g. studying market research, consulting other managers), so we don’t know if there are other more effective methods.
🏢 Companies using this
In a survey of experienced marketing managers:
The ability to separate personal preferences from those of target customers (i.e. knowing how to avoid bias) was rated as one of the top skills in marketing
93% said they witnessed other managers recently falling for this bias. 87% admitted recently falling for it themselves
79% said they try to avoid this bias when predicting customer preferences
Many companies and marketing courses train marketers to be aware of this bias, which triggers managers to suppress their personal preferences in order to fight it.
This technique of ‘letting go’ when managers are unsure if they’re suppressing correctly isn’t yet widely used in practice, since it has just been discovered.
⚡ Steps to implement
Regularly remind yourself (e.g. a post-it next to your desk) to constantly be aware of this bias (e.g. “My preferences ≠ ACME’s customer preferences). Teach your team to do the same.
Whenever you are making a decision to predict what your customers would like:
Suppress your personal preferences if you feel certain about them
Let your personal preferences influence you if you don’t have strong preferences and you’re unsure if they’re influencing you
Whenever possible, make decisions based on hard data rather than what you think. This is crucial when the decision is important and would be hard to reverse.
🔍 Study type
Lab experiments. Germany and United Kingdom.
Herzog, W., Hattula, J. D., & Dahl, D. W. (April 2021). Marketers Project Their Personal Preferences onto Consumers: Overcoming the Threat of Egocentric Decision Making. Journal of Marketing Research.
WHU – Otto Beisheim School of Management; Imperial College Business School, Imperial College London; and Sauder School of Business, University of British Columbia. Germany, United Kingdom, and Canada.
Remember: Because of the groundbreaking nature of this paper, it 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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