Product-data quality checker: how it works
The checker looks for mechanical problems in a catalogue: missing attributes, inconsistent units and sizing, duplicated or near-identical descriptions, unassigned categories, and fields that contradict each other between the title, the summary and the detailed specification.
( The Detail )
What this tool tells you
Findings tell you where the catalogue will behave badly in search, filtering and feeds. They do not tell you whether the copy is persuasive, whether the range is right, or which products deserve commercial attention. It also cannot verify that a stated specification is true, only that it is present.
Using it well
The mechanics matter less than the reasoning behind them. Each question is chosen because the answer changes the recommendation, not because it pads out a score. Where an answer is uncertain, the tool is designed to say so rather than average the uncertainty away into a confident-looking number.
Nothing here replaces a conversation about your specific operation. The value is that it puts the same structured questions to every business, which makes the gaps visible quickly and gives a shared starting point for a more detailed discussion.
How to approach it
Begin with the decision rather than the tool. Name the recurring judgement this affects, the information it depends on, and the person accountable for acting on the result. That framing keeps the first build small enough to inspect and useful enough to matter.
Keep a human review point in the loop until the quality and the failure modes are understood. A system that shows its working - what it drew on, where it is uncertain, and what it deliberately left alone - is one a business can keep running after the initial build.
( Next Step )
Start small enough to review, but on a workflow important enough to show whether a better system is worth building.