How Confirmation Bias Is Destroying Your Product

Essentially the most harmful phrases in product improvement are: “Our customers will love this.” I’ve heard this declaration in numerous product conferences, often adopted by months of engineering work and ending with the quiet disappointment of underwhelming consumer adoption. The perpetrator? Affirmation bias — our mind’s maddening tendency to hunt out data that helps what we already consider.

As product managers, we’re employed to make selections. We analyze markets, collect necessities and prioritize options. The issue is, as soon as we have developed a speculation about what customers need, we begin filtering all incoming data by means of that lens. Ambiguous suggestions will get interpreted as supportive. Damaging suggestions will get labeled as “edge circumstances.” And step by step, we assemble an alternate actuality the place our product selections are all the time sensible.

Associated: How Entrepreneurs Can Overcome Affirmation Bias

The consumer analysis theater

“Person analysis theater” refers to going by means of the motions of speaking to customers with out truly being open to having your assumptions challenged. You would possibly acknowledge these signs in your group:

• Cherry-picking optimistic quotes from consumer classes whereas ignoring adverse patterns

• Asking main questions designed to elicit particular solutions

• Limiting your analysis to customers who already love your product

• Deciphering silence or confusion as settlement

• Dismissing adverse suggestions as “they only do not get it but”

Look, I get it. You’ve got already advised your leaders and buyers in regards to the wonderful characteristic roadmap. You’ve got employed engineers based mostly on sure technical assumptions. Your whole firm narrative is perhaps constructed round a specific imaginative and prescient of what customers need. Altering course feels unattainable.

However staying on the doomed course is worse.

Associated: Do You Know What Your Prospects Need? Are You Positive?

Breaking the bias cycle

So, how can we truly repair this? How can we create processes that problem our cherished assumptions as an alternative of reinforcing them? Listed below are some sensible approaches I’ve seen work:

1. Separate information assortment from interpretation

One staff I labored with adopted a follow the place the folks conducting consumer interviews weren’t allowed to interpret the outcomes. They might solely doc precisely what was stated. A separate staff — one with out emotional funding in particular outcomes — would then analyze the transcripts. This decreased the tendency to listen to what they needed to listen to throughout interviews.

This separation creates a wholesome rigidity. The interview staff focuses on asking good questions moderately than main customers towards predetermined conclusions. The evaluation staff spots patterns with out being influenced by customers’ tone or the interpersonal dynamics of the interview.

2. Actively search disconfirming proof

Make it somebody’s particular job to play satan’s advocate throughout analysis planning. This particular person needs to be asking: “How would possibly we disprove our speculation?” moderately than “How can we validate our concept?”

For instance, as an alternative of asking “Would you utilize this characteristic?” attempt “What would forestall you from utilizing this characteristic?” The primary query nearly all the time will get a well mannered “sure.” The second provides you precise obstacles you may want to beat.

3. Take note of conduct, not simply opinions

Customers are notoriously dangerous at predicting their very own future conduct. They will enthusiastically inform you they’d positively use your new characteristic, however when it launches, they stick to their outdated habits.

I’ve discovered it rather more beneficial to look at what customers truly do moderately than what they are saying they’re going to do. This implies analyzing utilization information from current options, creating prototype experiences the place customers can reveal preferences by means of actions, and conducting area research the place you watch customers of their pure surroundings.

4. Create a tradition that rewards altering course

In case your staff will get punished for admitting they have been fallacious, guess what? They will double down on dangerous concepts moderately than acknowledge the necessity to pivot.

Sensible firms construct ceremonies that commemorate studying and adjustment. Some startups have achieved “Pivot Events” — precise celebrations when the staff made a significant course correction based mostly on consumer insights. They actually popped champagne once they killed options that analysis confirmed would not succeed. This despatched a strong message: Studying is valued over cussed persistence.

5. Diversify your analysis contributors

In case you solely discuss to your most enthusiastic customers, you are creating an echo chamber. Ensure that your analysis consists of:

• Potential customers who selected competitor merchandise

• Former customers who deserted your product

• Present customers who hardly ever have interaction along with your product

• Customers from completely different demographics and use circumstances

This range helps expose blind spots in your understanding.

Associated: 3 Cognitive Pitfalls That Are Ruining Your Enterprise — Methods to Unravel the Biases in Resolution-Making

The paradox of experience

This is the painful fact: The extra skilled you might be in your area, the extra vulnerable you turn into to affirmation bias. You’ve got seen patterns earlier than. You’ve got developed instinct. Typically that is extremely beneficial. Different instances, it makes you dangerously overconfident.

The answer is not to disregard your expertise. It is to pair your hard-earned instinct with rigorous processes that check your assumptions. The most effective product leaders I do know have sturdy convictions loosely held. They make daring bets based mostly on their experience, however they’re fast to regulate when proof contradicts their preliminary hypotheses.

In the long run, the market does not care about your sensible imaginative and prescient or your elegant resolution. It solely cares should you’ve solved an actual downside in a means that matches into customers’ lives. And the one method to know that for positive is to continually problem what you suppose you recognize about your customers.