AI Review Summaries on Product Pages

Review summaries help shoppers notice repeated themes without reading every comment. AI can group semantically similar statements, distinguish topics such as fit, durability or shipping, and draft a short overview. The source set should be defined: which product variant, time range, language, rating range and review types are included? If those boundaries are unclear, a polished summary can sound like a complete consensus even when it reflects only a subset. A sound workflow cleans duplicates and spam signals, retains the original review records, groups statements by topic and drafts a summary with traceable examples. Check that the model preserves the difference between a factual defect report and an opinion. If reviews disagree, state that experience varies rather than selecting one side. A rare but consequential issue can matter even when it is not the most common theme; frequency and severity are different dimensions. Do not claim “most included reviews agree” without a supporting count and denominator; reviewers may not represent all buyers. Quality review should look for omitted complaints, unsupported product claims, misattributed comments and variant mixing. Summaries should not convert a reviewer’s words into a retailer’s product guarantee. The FTC’s Consumer Reviews and Testimonials Rule took effect October 21, 2024 and addresses specified deceptive practices, including fake or false reviews and incentives tied to sentiment. It does not prescribe a summary algorithm. FTC guidance says mere review hosting does not create a general duty to investigate every review; application depends on conduct and context. Monitor summary corrections, complaints, clicks to source reviews and differences between the generated text and the underlying distribution. Rebuild summaries when the review set changes materially. For consequential products, use an editor who can evaluate the product category and source quality. AI is a way to organize customer language; the retailer remains accountable for the message shown on its product page.