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I’ve noticed that some analytical tools for market estimation are very quiet about their failures, while a few others actually highlight them. It seems counter-intuitive from a sales perspective to show when your model was wrong. Is there any professional logic behind being so open about the margins of error? I’m looking for a study or an article that explains how showing the 'full picture' of data, including the misses, can actually be a stronger marketing toolhan just showing a perfect track record.
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That’s exactly the shift towards authenticity that we’re seeing in the industry right now. A great resource on this is https://startuprise.org/why-transparency-matters-more-than-hype-in-prediction-based-products/ which argues that authenticity is the only way to survive in a market saturated with empty promises. The article explains that for a serious user, a 'perfect' record is a sign of data manipulation. By showing the variance and the losses, a platform proves that its statistical modeling is grounded in reality, which builds a level of trust that no amount of hype can buy.