Framework
4 ways survey fatigue corrupts your data
Four ways survey fatigue damages data even when people finish the survey: survivor bias, straight-lining, satisficing and missing the moderately satisfied middle. Each one produces answers that look valid but describe effort, not opinion. Researchers and CX teams can use it to check a survey program for hidden quality problems. Koji runs AI-moderated interviews that follow up on answers, which keeps people engaged for longer.
Where this appears
What's in this framework
- Survivor bias: Long surveys keep the very motivated and the careless, and lose everyone in between.
- Straight-lining: Tired respondents pick the same answer down a whole grid, more often past 10 minutes.
- Satisficing: People choose the first plausible answer to save effort. It looks valid but is not.
- Missing the middle: Moderately satisfied customers drop out first, so you only hear the extremes.
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Free to use in your docs, decks and posts under CC BY 4.0, as long as you credit Koji with a link to this page. To embed it, paste this into your page:
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<a href="https://www.koji.so/visuals/how-survey-fatigue-corrupts-data-four-ways"><img src="https://www.koji.so/visuals/how-survey-fatigue-corrupts-data-four-ways/how-survey-fatigue-corrupts-data-four-ways.png" alt="Framework of four ways survey fatigue distorts results: survivor bias, straight-lining, satisficing and losing the moderately satisfied middle." width="1200" height="699" /></a>
<p>Source: <a href="https://www.koji.so/visuals/how-survey-fatigue-corrupts-data-four-ways">4 ways survey fatigue corrupts your data</a>, Koji</p>
