What I think we lack in data quality in market research is pure transparency.
So not generic terms and phrases, your own scores, or other fancy names.
It’s not even a problem if you share those, that’s fine. The problem is nobody is explaining what that exactly means.
It’s presented as a black box which we really don’t need in market research, as we need to be able to defend our sources of data.
That’s the reason why at Peekator we share with our clients and prospects the exact 13 data quality steps we take before, during, and after data collection.
If we don’t respect those, we give money back on the survey project.
In my opinion, as a first step to fix data quality, we need transparency!
This was part of Insights Future Live 03 with the amazing Karine Pepin on Data Quality. We covered a lot, and Karine shared some interesting stories and perspectives on data quality.
To hear why the panel industry is all one big pool, check the link bellow. 🚶🏼
