A weekly AI visibility review should tell your team what changed, why it matters to buyers and what to inspect next. Start with the answers behind the result, then decide whether the evidence calls for a correction, a closer look or continued observation.
Check that the periods are comparable
Review the same buyer questions, assistants and relevant settings across both periods. Note newly added prompts, products, markets or assistant experiences. Check whether the available answers cover both periods well enough to make a useful comparison.
A gap in available answers needs investigation before it can support a conclusion about your brand. Keep launches, stock changes, promotions and significant site edits alongside the review.
Read the changes that affect a buyer decision
Observed change | What to inspect | Possible next action |
|---|---|---|
Your brand appears less often | The affected questions and the alternatives now recommended | Check whether your product still meets the request and has clear supporting information |
A competitor becomes more prominent | The reasons given and the cited evidence | Look for an unanswered buyer need or a meaningful difference in the offer |
An answer introduces an inaccurate claim | The exact passage, product variant and source | Correct information you control or request a factual correction from the publisher |
A new source is cited | The page and the claim it supports | Assess whether it supplies useful evidence or repeats an error |
An answer improves after a page change | The corrected information and other changes during the period | Verify the improvement across further comparable answers |
Use the context to interpret a change
Suppose an assistant stops recommending a product after the relevant size goes out of stock. The immediate question is whether the stock information and available alternatives are accurate. Rewriting the product description would not resolve the missing size.
Alternatively, an answer may recommend the item while misstating a compatibility requirement. That specific error can deserve attention even when the overall visibility result barely changes.
These examples illustrate how to choose the next check. Read representative answers from both periods before attributing a change to a particular cause.
Separate urgent corrections from trends to watch
Prioritize inaccurate information that could lead a buyer to the wrong product or terms. Verify the source, fix the facts where you can, and check the public result.
For broader changes, look for a pattern across relevant questions and dates. A single unusual answer may warrant another check before a substantial content project. Consider the importance of the affected buyer need as well as how consistently the change appears.
Write a weekly note the team can use
What changed: identify the buyer question, assistant and comparison periods.
Evidence: include representative answer passages and source links.
Context: note changes in products, availability, questions or coverage.
Next action: name the specific check or correction and the person responsible.
Follow-up: set a review date and describe what a useful improvement would look like.
Keep completed work separate from its later effects. Confirm that a corrected page or listing is live, then examine whether subsequent answers use the information accurately.
The guide to interpreting AI visibility explains how to read mentions, position and citations together. Use the revenue guide when assessing visits and purchases alongside discovery.