As of November 3, 2025, the Q&A API has been discontinued, and the familiar Q&A section of the GBP listing is vanishing from business listings across Google Search and Maps. This isn't just another feature deprecation, it's a sign of a how Google plans to handles local business information going forward.
For businesses using LocalClarity, historical Q&A data will remain accessible for the next six months, providing time to preserve and repurpose this valuable content. But understanding what this change means for local search strategy is what matters most.
The traditional Q&A section allowed anyone to post questions about a business, with anyone (including the business owner) able to provide answers. It was crowdsourced, sometimes messy, and occasionally valuable. Potential business customers asked about parking, pet policies, service areas, and appointment availability, real questions that could influenced purchasing decisions.
LocalClarity clients have historically leveraged the Google Business Profile Q&A dataset in two ways. First, by downloading and analyzing questions across locations, client could identify recurring themes that revealed what customers truly wanted to know about the brand, its products, and its services, effectively treating Q&A as a direct line to customer intent and curiosity. Second, they used this insight to identify common questions that could be answered on each listing via a bulk upload. Pre-answering custom questions helped to ensure consistent, accurate information across listings while limiting the chance that public answers provided the wrong details.
Now, in the mobile view of Google Maps, the option to “Ask about this place” is visible, where the Q&A section used to be. This section now presents common and suggested topics based on review data and business type. When a user clicks on a pre-generated question or submits their own query, the feature processes the question, searches available location and business data, and generates a corresponding answer. If insufficient information is available, the response will indicate, “It looks like there isn’t much information about [your query],” and provide an explanation of their data sources.
Google pulls information from Google Business Profiles, website content, customer reviews, uploaded photos, structured data, and other public sources. If the information available is clear and consistent, users get accurate answers. If it's missing or contradictory, the AI might make assumptions – or pull incorrect information from outdated sources.
With Google's AI now speaking on behalf of businesses, local landing pages have transformed from a nice-to-have into an absolute necessity. This isn't just about having a page for each location’s address, phone number and hours anymore – it's about creating comprehensive, authoritative content that feeds the Beast (aka, Google's information requirements).
Local landing pages need to serve as the single source of truth for everything about a business location. They should answer common questions, presented in clear, structured formats that both humans and AI models can easily parse. This means going beyond basic NAP (Name, Address, Phone) information to include detailed service descriptions, policies, FAQs, and nuanced, location-specific content.
The most effective local landing pages now include operational details like parking availability, accessibility features, accepted payment methods, and service areas. They document policies around appointments, cancellations, and special accommodations. Every piece of information that once lived in Q&A sections should now have a prominent, structured place on these pages.
With Q&A gone, Google Business Profile categories, attributes, and services have become exponentially more important. These structured data points are now primary sources for AI-generated answers, making their proper configuration critical for accurate representation in search results.
Categories define what a business is at the most fundamental level. Primary and secondary categories don't just affect where businesses appear in searches – they now influence how AI interprets and presents them. Google frequently adds new category options, making regular reviews essential to ensure optimal classification.
Attributes are the differentiating details that help customers make decisions. Does a restaurant offer outdoor seating? Is a medical practice wheelchair accessible? Is there free Wi-Fi? These attributes directly feed into AI responses when customers ask specific questions. The more attributes a business claims and verifies, the more comprehensive and accurate the AI's answers become.
Services deserve special attention in this new landscape. Rather than simple lists, services should include detailed descriptions. Including pricing where appropriate, explaining what's included, and clarifying any limitations or requirements helps the AI provide specific, helpful answers rather than generic responses that might send customers elsewhere for clarity.
Customer reviews have always influenced purchasing decisions and local search rankings (review count, recency, and rankings are all algorithm factors), but they've now become a primary data source for AI-generated answers. A review mentioning "amazing gluten-free options" might become the source for answering dietary questions. A complaint about limited parking could influence how the AI responds to accessibility queries.
This shift requires a more strategic approach to review generation and management. Detailed reviews that mention specific aspects of a business – services used, staff members who helped, unique features appreciated – become valuable data points. These detailed reviews function as an informal FAQ, providing the context and specifics that AI systems need.
Review responses can even contribute to this new ecosystem, even if indirectly. When businesses respond to reviews with detailed information, especially when correcting misconceptions or announcing updates, these responses become part of the data set that AI systems will eventually analyze.
The transition away from Q&A requires systematic action. Here's what needs to happen:
Immediately preserve existing Q&A content. Before it disappears completely, download all questions and answers associated with your business profiles from the LocalClarity platform. This content represents real customer concerns and proven answers.
Audit digital presence for gaps. Identify where missing information might lead to AI assumptions or errors. Look for inconsistencies across platforms that might confuse AI systems.
Build comprehensive local pages. Create detailed, structured content that addresses every aspect of business operations. Include FAQs, policies, service details, and location-specific information.
Optimize Google Business Profile completely. Fill every available field, claim all relevant attributes, and detail all services. These structured elements are now primary information sources.
Develop a review strategy. Encourage detailed reviews and respond comprehensively. Both reviews and responses feed the AI's understanding of the business.
Implement proper schema markup. Use FAQ, local business, and service schema to make content easily digestible for AI systems.
Maintain content freshness. Regular updates signal reliability and provide current information for traditional search, local map search and expanding AI systems to reference.
The removal of Q&A represents an evolution in how Google handles local business information. While direct control over one specific feature has been lost, the opportunity to influence search results and AI responses across the entire Google ecosystem remains. Success requires shifting from reactive management to proactive content creation.
