Marco Vriens is CEO of Kwantum. He can be reached at marco.vriens@teamkwantum.com. Andrew Elder is chief research officer at Illuminas. He can be reached at andrew.elder@us.illuminas.com. Scott Holland is director marketing sciences at Illuminas. He can be reached at scott.holland@us.illuminas.com.

Every marketing researcher knows that survey data quality has become a major issue, even more so when surveying hard-to-reach audiences. There are many factors that determine data quality: survey design, question format, survey length, sample sourcing and modality. In this article, we assume that the researcher has made every attempt to a design a quality multimode survey, keep the length reasonable and select quality sample partners.

Despite all these efforts we can seldom (if ever) assume that the data we get back is completely valid or has all-around good quality. Any study can be susceptible to fake data, professional respondents or inattentive respondents who warrant being flagged as suspicious or of questionable quality. Though “inattentive” sounds benign in comparison to other, more actively problematic respondents, inattentiveness can be a serious issue for data quality. The extent to which we have respondents that were inattentive has been found to be in the 5%-50% range, as Maniaci and Rogge (2014) state: “Meaningful findings among attentive respondents were not present among inattentive respondents.”

It is this positive perspective towards the data quality issue – finding the respondents who did do their best to conscientiously read the questions and provide thoughtful answers – that often gets overlooked during the quality-review process. We argue that by identifying these respondents we not only gain meaningful insights from the data but also gain insight into quality.

Illuminas has developed a data quality process ranging from eliminating fake data to identifying the most valuable resp...