The Reviews That Actually Move Buyers.
Social Proof generation is curatorial, not generative. It scores reviews from your scan data against Voice Map entities and presents the most impactful highlights with placement guidance. The system finds the reviews that address your buyers' top concerns, you place them where they matter most.
3 Entity Types. Curated, Not Generated.
Social Proof scores existing reviews against three entity dimensions. The result is a ranked list of the reviews most likely to move a buyer who shares your category's top concerns.
Identifies reviews that describe real results
Reviews mentioning outcomes buyers care about get scored highest.
Surfaces trust-building reviews
Reviews that address brand credibility concerns from the Voice Map get prioritized.
Matches buyer vocabulary
Reviews using the same language patterns buyers use across networks are more relatable and credible.
Social Proof is different from the other 4 generation types. It does not write new content. It curates existing reviews from your scan data, scores them against your Voice Map, and tells you which reviews to highlight and where to place them.
Ranked Reviews. With Placement Guidance.
Each with the review text, rating, and relevance score against your Voice Map.
Where to place each review. For example, "Near the price section to counter durability objection."
Which buyer concerns each review addresses, mapped back to entity confidence.
From a Real Voice Map Scan.
Social Proof Highlights surfaces the most impactful reviews from your scan data with placement guidance aligned to your Voice Map's top buyer concerns.
Want to see the other generation types in action?
See examplesWhat Changes When Social Proof Is Curated by Voice Map.
Seller reads through reviews and picks favorites.
Selection biased toward reviews that praise the product.
Cherry-picked positive reviews that may not address buyer concerns.
Sellers pick reviews that make them feel good. Buyers need reviews that address their specific concerns.
All reviews from scan data scored against Voice Map entities.
Algorithmic curation based on entity match, not sentiment.
Reviews selected for their relevance to top buyer concerns, with placement guidance.
A 4-star review that addresses the #1 buyer objection is more valuable than a 5-star review that says "great product." DecodeIQ finds the reviews that move buyers, not just the ones that flatter sellers.
Curatorial (scoring), not generative (LLM)
Reviews from scan data
Algorithmic scoring against Voice Map entities
1 credit per generation
Surface the ReviewsThat Actually Sell.
Run a Category Scan. Build your Voice Map. Curate your first proof set.
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