Ask how the score is constructed.
A visibility score is a summary produced by a particular method. It may combine rank observations with selected queries, weights or demand estimates. Its meaning depends on those choices; the score is not a universal store measurement.
Request the provider’s methodology and known limitations. If the calculation is not disclosed, report that constraint rather than inventing an explanation for a precise-looking number.
Keep the comparison universe stable.
Adding more queries, changing markets or revising weights can change the score even if the app’s observations do not change. Save the configuration used for each reporting period.
The visual shows two fictional weighting schemes applied to the same inputs. Their different totals illustrate sensitivity to methodology, not a comparison of real tools. A score needs its version and scope attached.
Inspect which terms drive the movement.
Break down the change where the tool permits. Check whether the terms are relevant to the product and whether the source data is complete. A headline gain dominated by low-fit queries may deserve a different interpretation than a broad improvement in core tasks.
Use query-level rank tracking and relevance review. Do not let aggregation remove the evidence needed to challenge the conclusion.
Avoid comparing incompatible score scales.
A score of 60 from one method is not necessarily better than 40 from another. Different baskets, normalisation and weights can make the numbers incomparable. Even the same provider can introduce a methodological break.
Document changes in the reporting timeline. Show separate series or explain the discontinuity rather than presenting a seamless performance trend.
Connect the score to a decision.
Use the summary to identify where further inspection is useful. It cannot establish revenue, customer value or the number of downloads caused by ASO. Report those outcomes using appropriate sources and definitions.
The KPI guide helps separate diagnostic signals from outcomes. A summary is useful when it helps the team ask better questions, not when it replaces them.
