Now that I'm on the other side of the table, one of the most common complaints I
By Jack · October 6, 2026 · Curated by George's Blog
Now that I'm on the other side of the table, one of the most common complaints I hear from ecom teams at brands/agencies about their digital shelf data is that its inaccurate. And then they pick their next digital shelf vendor based on the coolness of the dashboard and the AI demo.
This doesn't really surprise me. Accuracy problems only really show up once you live with the data and have to start actioning off it. The out-of-stock alert doesn't match the retailers inventory replenishment report. The Paid SOV numbers jump a ton when you know you were cutting budget.
None of the accuracy validation I'd want is commonplace during an evaluation. A real check means doing a lot of analysis & leg work reconciling across multiple providers and your own data.
So buyers instead frequently judge on what they can see. "If the AI demo is cool, the design looks clean, and the slide says they cover all the retailers I need..... well that must be good enough!" A few months later, the accuracy complaints start again, this time with a new vendor.
For vendors that truly do have differentiated quality data, this is a big opening. You need to build the evaluation system for the prospect. How can they easily see that your data is better? And why does this data quality even matter to them? Turn their complaint into a test you can teach them how to run.