In our age of data supposedly reigning supreme, our data culture is still very coarse. The two most simple issues we're still struggling with in my experience? How much of a sample size do you need to get to statistical relevance and correlation is not causation. Both of these issues probably speak of how much our brain just wants to confirm our biases or construct a reality out of thin air because we always want to see order in the world.
Media are probably to blame in many cases, but scientists and researchers are still very much struggling with these basic principles too:
Then, of course, there are the moments when corporates need to plan a strategic move or tech entrepreneurs check if they've reached product-market fit... But in entrepreneurship and innovation, there's always a simple way to disintricate data and be 100% sure there is effective causation between some feedback and a product-market fit.
Want to know the big secret? Put a price from the get-go at the level of the value you think you create and see how many early adopters will pay.