---
title: "#reviews — seo-mcp"
description: "SEO tips tagged Reviews."
url: "https://seo-mcp.io/tag/reviews"
---

# #reviews

7 published tips tagged “Reviews”.

- [Collect product reviews on Google or Trustpilot](https://seo-mcp.io/t/collect-product-reviews-on-google-or-trustpilot) — Product reviews add first-hand evidence that product pages rarely contain and that review systems reward. Ask every buyer after delivery through the order confirmation or a follow-up email, make the request one click, and never filter out unhappy customers. Answer negative reviews in public, keep review markup on the page, and track rating counts per product rather than one sitewide number.
- [Add review snippet structured data](https://seo-mcp.io/t/add-review-snippet-structured-data) — Review snippets require a Review or AggregateRating attached to a specific item such as Product, Recipe or LocalBusiness. Provide ratingValue and reviewCount or ratingCount, keep the visible rating identical, and never mark up self-serving reviews on your own Organization.
- [Get steady Google reviews and reply within two days](https://seo-mcp.io/t/get-steady-google-reviews-and-reply-within-two-days) — Ask customers for a review at checkout while the visit is fresh, text the direct Google review link the same day, and invite them to mention the treatment in their own words. Reply to every review within one to two days. A steady flow of recent, specific reviews keeps the local profile active and relevant.
- [Add review-sourced customer results to pages for AI quotes](https://seo-mcp.io/t/add-review-sourced-customer-results-to-pages-for-ai-quotes) — Pull the last 12 months of reviews from G2 or Capterra, extract every concrete customer result with an LLM, then add two or three verified quotes with the reviewer's role and company size to the pages that match their industry and segment. Specific, attributable results give answer engines something exact to quote.
- [Audit the six sources AI assistants read for local queries](https://seo-mcp.io/t/audit-the-six-sources-ai-assistants-read-for-local-queries) — The post argues AI assistants answer local recommendation questions by running search-style queries and reading a fixed set of sources. Audit and align those sources: Google Business Profile fields, customer reviews, service and city pages, third-party listings, profile posts, and consistent name, address and phone data. The benefit is a better chance of being included when an assistant recommends a local business.
- [Create a dedicated reviews domain to earn AI review citations](https://seo-mcp.io/t/create-a-dedicated-reviews-domain-to-earn-ai-review) — One practitioner reports that ChatGPT cites a dedicated brand-reviews domain (brandname + reviews) for review queries. If you hold genuine customer reviews, publish them there in crawlable HTML and link the site from your main product page, then check whether an assistant retrieves it for review questions.
- [Tune Google Business Profile for AI local recommendations](https://seo-mcp.io/t/tune-google-business-profile-for-ai-local-recommendations) — Work the surfaces AI assistants read for local queries: keep name, hours and phone identical everywhere, copy the primary category from the top local pack results, request reviews that name the service, city and result, answer real questions on the profile and site, and earn mentions on other people's pages.