Rep Data's In-Survey Data Cleaning Helps (r)evolution Get to Better Data Faster

(r)evolution is one of the leading full-service market research institutes in the German-speaking region. Independent studies regularly confirm the company as a top performer, and it has received multiple awards for its consulting expertise and quality.

Ensuring the quality of collected panel data has always been a top priority at (r)evolution. Before implementing Rep Data's in-survey data cleaning tool, ReDem, the company used methods such as oversampling, trap questions, and filtering out speeders and flatliners to identify "lazy respondents" and systematic fraud. However, these approaches were time-consuming and inconsistent, as they varied from project to project.

A major challenge was assessing open-ended responses, which was especially labor-intensive as fraudulent answers became harder to spot. Over the past one to two years, (r)evolution saw a significant rise in fraud cases within online samples, particularly in heavily researched markets like the U.S., where large incentives are offered.

Traditional methods for data validation and cleaning began to reach their limits. Detecting fraud became increasingly difficult, and oversampling alone was no longer enough to guarantee data quality.

To tackle these challenges, (r)evolution began using Rep Data's in-survey data cleaning tool, ReDem, for data cleaning and quality assurance. The process is now applied to the majority of the company's studies.

Through a live integration with their survey tool, keyingress, each interview is evaluated in real time against predefined quality criteria. Low-quality data is flagged as a "Quality Fail" and reported back to the panel, ensuring it does not affect quotas.

A key part of this process is the automated review of open-ended responses, which is used across all studies. Additional checks include content analysis, duplicate detection within and across interviews, and monitoring of response times and patterns in grid questions.

With Rep Data's in-survey data cleaning tool in place, (r)evolution has seen a clear improvement in data quality, especially in the review of open-ended responses.

One example came from an analysis of product usage intent. A comparison between raw and cleaned data showed that the seemingly high usage intent in the raw data was largely driven by fraudulent responses. These cases would have been nearly impossible to detect through manual review alone.

Without technology-based data quality checks, the skewed data could have led to inaccurate insights and misguided business decisions, such as launching products based on inflated customer demand.

Beyond improving data quality, the tool has also helped (r)evolution gain efficiency through automated data checking, cleaning, and quota management. As a result, the time needed for project management, quality assurance, and data analysis has been significantly reduced.

"Using ReDem has led to a significant improvement in data quality, especially when it comes to reviewing open-ended responses. We now achieve a level of data quality that would no longer be possible to guarantee manually, given the increasingly professional and automated fraud. Beyond improving quality, we have also gained efficiency through automated data checking, cleaning, and quota management. The time required for project management, quality assurance, and data analysis has been reduced considerably. With ReDem, we now get to better data faster."