There has been a lot of talk lately about what makes a successful online sale, and much like the recent noise around AI-driven forecasting, it is easy to draw the wrong conclusions from surface-level data.

Having worked within one platform and then gone on to help build another, I have seen how tempting it is to focus on indicators that seem to correlate with price but often do not tell the full story. It is like comparing online prices to the saleyards. Online will almost always look stronger because unsold or passed-in stock is simply not reflected in the averages.

As an example when people analyse a single data point, like photo count, as though it is the only contributing factor to higher prices. Of course, description quality and images can play a role, but what is often overlooked is the most important piece of the puzzle, which is why something did not sell.

Understanding the no-sales is just as valuable, if not more, than analysing the successful ones. Real insights come from looking at the full picture, not just the results that make the website (even ours) look good.