Optimizing for 'Ask A Question': Strategies After the Death of Google Q&A

Google has quietly retired the manual Questions and Answers feature that has been a staple of Google Business Profiles (GBP) since 2017. Current observations indicate that the secondary 'Ask A Question' (AAQ) interface—powered by Large Language Models (LLMs)—is becoming the primary method for user inquiries within the Google Maps app. Last updated by Miriam Ellis on January 26, 2026, this shift represents a move away from human-curated FAQs toward automated, synthesized responses derived from a business's entire digital footprint.

For nearly a decade, local search was defined by a predictable exchange: a user asked a question, and either the business owner or a Local Guide provided a static answer. We are now seeing the deprecation of that manual interaction in favor of an AI that generates answers instantly by scraping menus, reviews, and website metadata.

How does the Google Maps Ask A Question feature work?

Unlike its predecessor, the new interface does not necessarily display a list of previous queries. Instead, when a user engages with the 'Ask A Question' prompt on the Google Maps app, they are greeted with AI-suggested topics based on the business category. If a user enters a custom query—for example, a dental practice in Leeds being asked if they offer specific orthodontic brands—the system scans available data to formulate a response.

According to research by Whitespark, these answers are often accompanied by citations. If an AI tells a customer that a bakery has 'jelly doughnuts,' it might link directly to a specific mention in a customer review or an item in the digital menu on the profile. This is a significant departure from the old system where answers were isolated text blocks; now, the answer is a synthesis of the business's total online presence.

Why Google transitioned to an automated model

The traditional Q&A section was frequently plagued by neglect. Many business owners failed to monitor the section, leading to unanswered questions or, worse, incorrect answers provided by unverified third parties. By shifting to an AI-driven model, Google can provide immediate gratification to the searcher while reducing the burden of manual moderation for the business.

However, this automation introduces a new challenge for local SEO. Compared to the previous workflow of simply 'upvoting' a helpful answer, operators must now ensure that the underlying data sources—their reviews, attributes, and on-site content—contain the specific keywords the AI needs to respond accurately.

Long-tail strategies for Google Maps Ask A Question optimization

To influence these automated responses, businesses must treat every field in the New Merchant Experience (NMX) as a data feed for the LLM. Consider a 12-location HVAC operator: previously, they might have posted a single FAQ about emergency 24/7 furnace repair. Under the new model, they need that information to appear consistently across their website, their service attributes, and within the text of their customer reviews.

Review cultivation has become arguably the most critical component of this strategy. Because Google cites reviews in its AI answers, prompting customers to mention specific services or products provides the 'social proof' the LLM requires to verify a fact. A review that mentions 'the best emergency furnace repair in the city' serves as a credible data point for an AI answering a late-night query.

Restrictions and category exclusions

Not every business currently has access to this AI-synthesized feature. Data suggests that Google is intentionally excluding categories that require high levels of sensitivity or are prone to spam. Current exclusions include:

• Medical categories dealing with sensitive issues like addiction or therapy (though general dentistry is often included).
• Regulated industries such as legal services or dispensaries.
• High-spam categories like locksmiths or garage door repair services.

For businesses in these niches, the absence of the 'Ask A Question' feature may leave a temporary void in how users interact with the profile, as the legacy Q&A section has also been removed from many desktop views.

What this means for local businesses

The transition to an AI-first inquiry system requires a shift from 'managing a profile' to 'feeding a database.' We recommend the following actions to ensure your business provides accurate answers:

1. Optimize the Digital Menu and Product Catalog: If your business category allows for a menu or product list, treat it as a primary FAQ. Ensure every variant of your offering is listed with clear descriptions.
2. Guide Review Content: Use post-service follow-ups to ask customers specific questions. Instead of 'leave us a review,' try 'mention which technician helped you and what service they performed.' This creates the descriptive text Google’s AI needs.
3. Sync Social Media Signals: Connect your social profiles via the NMX. There is evidence that Google scans linked social signatures to identify business attributes and community engagement.
4. Strengthen On-Page FAQ Markup: Ensure your website has a dedicated FAQ page with Schema.org markup. This remains a foundational source for Google's broader understanding of your business capabilities.

Sources

• Whitespark: With Google Q&A Gone, You Need a Maps Ask A Question Strategy
• Google Blog: New ways to use AI in Google Maps
• Search Engine Journal: Ask Maps - What it Means for Marketers