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Data Quality - How do we ensure high quality data?
Data Quality - How do we ensure high quality data?
Cameron Gavin avatar
Written by Cameron Gavin
Updated over a week ago

In this article:

High quality data by design.

We stay one step ahead of poor quality data on Upsiide, with proprietary checks built in before, during, and post study and a brand new approach to mobile surveys.

We get it - quality is kind of crucial.

Quality of response data is a common concern for the researchers and marketers we work with. And while most research platforms implement quality checks to filter out profanity, speeding, and professional respondents, we take our commitment to high quality data one step further.

We offer 9 discrete quality checks that occur before, during, and after responses come in. If at any point a respondent’s answers do not meet our quality threshold, they’re removed from the study, along with their prior responses, and automatically replaced with someone else.

How our quality checks work


When a respondent enters into an Upsiide study, some fancy stuff happens in the background. Our proprietary algorithms check for bots, professional respondents, and more.


While a respondent swipes and answers questions, we're able to understand if they're offering up quality feedback with in-app gibberish and language detection.


Once a respondent has completed an Upsiide study, our back-end is hard at work checking for speeding and similarity across open-end responses

A keen focus on bot-detection and speeding

The time and effort put into creating studies could be worth little if the ones responding are not your target audience. Or worse, are bots.

Our 9 discrete quality checks help identify and exclude notorious bots, giving you a pool of respondents that are trustworthy, and human.

Professional respondents often just type away answers to your open-ended questions without taking the time to think them through. This makes them a not-so-reliable source of responses which skew your results and potentially your business decisions.

Our quality checks identify and exclude them from your results, leaving only the most genuine respondents behind. You're welcome.

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