Indie Dev Finds 42% of His 'Real Demand Data' Was Mislabeled for Months

The creator of Idea Miner, a tool that surfaces paid outsourcing tasks to help indie developers decide what to build, discovered that 1,446 of 3,401 published listings — about 42.5% — carried incorrect category labels. The flaw traced back to an old fallback classifier that defaulted unrecognized tasks to 'Web Development' when the primary model was unavailable; the code was later replaced but never retroactively corrected existing database rows. Because the pages continued to render normally and showed real data, the silent error went undetected through routine use for an extended period. The developer fixed 1,383 of the mislabeled entries using deterministic, rule-based reclassification, moving the remainder to an honest 'Other' category rather than guessing. The incident highlights a distinction often overlooked when evaluating data tools: whether a source is genuine is a separate question from whether the processing pipeline between that source and the final output is error-free.