What Is Confirmation Bias in Data Storytelling?

What does confirmation bias mean?

Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs, values, or decisions. Per Wikipedia, people readily accept new information consistent with their beliefs while remaining skeptical of information that contradicts them, and the effect is strongest for desired outcomes and deeply held beliefs. In data work specifically, this means someone can look at the exact same dataset as a colleague and walk away with a different, self-serving conclusion, not because either one is being dishonest, but because both are unconsciously weighting the evidence differently.

This makes confirmation bias harder to catch than an outright factual error, since the person affected by it genuinely believes their read of the data is objective.

Why confirmation bias matters for product managers

Turning Data Into Storytelling names confirmation bias directly in its certification quiz as a specific psychological principle relevant to data storytelling: users tend to favor data that aligns with their beliefs, framed as one of several cognitive traps a data storyteller has to actively guard against, not a rare edge case.

The bootcamp teaches this alongside a broader warning against misrepresentation in data storytelling generally, presenting data in a misleading way through inappropriate scales or cherry-picked data, since confirmation bias is often the psychological root cause behind exactly that kind of selective, if unintentional, misrepresentation.

Confirmation bias example

In Turning Data Into Storytelling's practical challenge, a PM has to build a narrative from Netflix's quarterly data that convinces four different audiences, management, investors, markets, and employees, that the stock has real potential. Each of those audiences almost certainly walks in with a different prior belief about Netflix, which creates a live risk: reaching for whichever chart best confirms what a specific audience already wants to hear, rather than building the narrative around what the full dataset actually shows.

The exercise's own structure guards against this by requiring the PM to first observe the data broadly, quantitative, qualitative, facts, insights, and visuals, before choosing a central angle, a sequencing that forces a fuller look at the evidence before committing to the story confirmation bias would otherwise steer toward first.

How Builders Camp teaches confirmation bias

Builders Camp teaches confirmation bias inside the Turning Data Into Storytelling bootcamp, directed by Andre Albuquerque, as part of its module on handling objections and communicating uncertainty honestly in a data narrative.

Builders Camp runs live and self-paced bootcamps in product management and AI product building. See the Turning Data Into Storytelling bootcamp for the next cohort dates.