Recently, I’ve heard, “Clients don’t even care where the data comes from.”
And this one is double-sword of market research industry.
First of all, I don’t agree that clients don’t care where the data comes from.
However, they also want most of your attention on outputs. Sometimes, the outputs can suffer because of data quality measures.
Here’s the trick. At this point, usually the following happens:
- The supplier stands firm and maintains its data quality, explaining it to the client.
- The supplier lowers their data quality practices to accommodate the client.
At the end of the day, a good client will understand that data quality comes first and your outputs can only be as good as the data is.
But there are also a lot of clients who don’t understand and don’t ask anything about data quality. They just assume you are going to take care of it. Which is, of course, perfect for those wanting to earn a quick buck.
If you decide to gamble on your data quality, trust me, there is no faster and better way to ruin your reputation.
When the client sees bad data, they start to question everything you’ve ever said. It’s hard to recover from that.
Then again, we have a question; What is bad data? But that’s a topic for another post.
All in all, suppliers need to educate clients more on the importance of data quality and what is essential in our work.
Now, with AI synthetic sample, this all becomes far more complicated and interesting, but even more dangerous for clients. Fun times! 🚶🏼