How claims are extracted from reviews
Vyera groups repeated claims across reviews rather than reporting on any single review alone.
Vyera groups repeated claims across reviews rather than reporting on any single review alone.
Why repeated claims matter more than one review
A single review is an anecdote. The same claim showing up across many reviews is a pattern worth acting on. Similar claims are grouped together, and each group shows how often it appears, how it is trending, and links back to the original reviews it was drawn from.
This is also why claims are more useful than a star-rating average alone: an average can stay flat while the specific reasons behind it shift underneath it.
What it does not do
Claim extraction does not read private feedback such as support tickets or surveys you have not made public, only reviews published on the sources Vyera reads.
It does not verify whether a claim is actually true, only that reviewers are making it.
It never posts anything back to a review platform. This is a reading tool, not a way to respond to reviews on your or a competitor's behalf.
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Related articles
- Which review sources Vyera reads
Vyera reads review platforms matched to your industry, where a competitor has a listing on them.
- Reading the sentiment view
Sentiment by theme tells you more than an overall average, because an average can hide which specific thing is driving it.
- How loss reasons are identified
Loss reasons are extracted from reviews that mention switching away from or comparing against a competitor.
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