RightResponse AI is an AI reputation and review management software for brick-and-mortar businesses, with the core goal of turning Google reviews into a growth engine. According to the official description, it helps businesses manage the entire Google review lifecycle, including acquiring reviews, replying to reviews, understanding customer and competitor feedback, and tracking local visibility on Google Maps. Businesses can use the software directly or hand day-to-day review management over to the official Done For You team.
Traditional AI review tools usually only generate a polite reply that restates the review itself. RightResponse AI's differentiation lies in "Message-Informed Review Responses": it can select relevant and approved business information and incorporate it into replies, so that public replies both respond to the reviewer and provide useful business information to potential customers.
The platform offers five product directions around the review lifecycle:
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Message-informed AI review responses (Review Responder): generate highly personalized replies that can incorporate relevant information about the business, brand, and location. Its multi-stage agent workflow plans, writes, and checks the quality and safety of each reply, including specialized agents for safety and risk, review understanding, topic analysis, information selection, reply planning, writing, and final quality assurance. Businesses can control rules such as greetings, closings, contact information, and whether to include the business name, and customize them by company, brand, or location. Users can choose which star ratings are automatically published, which require manual approval, editing, or scheduling. A dedicated safety agent identifies protected health information (PHI) and personally identifiable information (PII) to avoid sensitive details appearing in public replies. The system can also detect when reviews are edited and when written feedback is inconsistent with the star rating, and supports more than 60 languages and over 100 review platforms.
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AI review requests (Review Generation): combine campaign controls with AI personalization to generate more authentic customer reviews. You can start with standard request templates and gradually introduce more channels and advanced AI personalization. Use customer, transaction, appointment, and other data to create highly personalized requests, ask customized questions to guide informative reviews, and invite customers to include photos. It provides a WYSIWYG campaign builder where you can define fields, writing instructions, and request methods, and preview the results. Request channels include email, SMS, and QR codes, and can be triggered through Zapier, in-app workflows, Google Sheets Direct integrations such as direct connection and others initiate activities. It supports custom blackout periods to prevent repeated requests to customers within a specified time; you can also set send delays and specific allowed sending time windows.
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AI Voice of Customer and Review Sentiment Analysis (Review Analysis): Turn reviews into detailed, evidence-backed intelligence, analyzing the specific topics within each review rather than reducing the entire review to a single sentiment score. The system drafts a topic framework based on the company's service, product, department, and operational priorities, and teams can review, modify, or add to it. Sentiment is analyzed separately by topic, because a single review may simultaneously praise and criticize different aspects. Phrases unrelated to the customer experience are excluded to avoid distorting the results. Every insight can be opened to reveal the underlying customer verbatim and source review. It supports comparisons by brand, location, star rating, and time period, and also supports applying the same topic framework to both your own and competitors' reviews to obtain directly comparable Voice of Customer intelligence.
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Competitor Analysis: It not only shows which competitors have stronger ratings or review momentum, but also reveals the reasons given by their customers. Features include side-by-side reputation benchmark comparisons (average rating, total review volume, review frequency, recent performance), review velocity and momentum (average monthly review volume and recent changes), competitor Voice of Customer, topic-by-topic competitive gaps, and evidence-backed competitive findings. Comparisons can be made against meaningful competitors for each location or market.
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Local Visibility: Shows each store's Google Maps ranking within the geographic area where customers actually search, for each important search term. Because businesses do not have a uniform Maps ranking, the system measures visibility from multiple search points and tracks changes. It supports selecting search terms, geographic coverage, grid configuration, and scan schedules; measuring rankings point by point; retaining historical scans and using Rewind to replay how visibility changed across the grid; discovering local competitors; viewing map visibility alongside competitor ratings, review volume, recency, and response behavior; and tracking search grids separately for each location.
It is suitable for: enterprise and local teams, multi-location businesses (typically 25–200 locations), enterprises and franchisors (200+ locations, multi-brand), as well as agencies and white-label partners. Agencies can offer review requests, information-driven replies, review intelligence, and local visibility support services to clients under their own brand, delivered in the background by RightResponse AI.
In terms of pricing, the official description offers usage-based PAYGO access, monthly plans for scaling teams, Done For You services for enterprise and agency clients, and month-to-month flexibility with no long-term contract; specific prices and included capacity need to be viewed on its pricing page.
