In a nutshell: GEO (Generative Engine Optimization) is redefining the rules of the online visibility game. When an Internet user asks ChatGPT or Gemini “what’s the best plumber in Bordeaux?”, the AI doesn’t draw its answers at random. It relies on digital notoriety, customer reviews, data consistency and brand strength. Here are the points that structure this article:
- GEO is gradually replacing traditional SEO: 27% of searches now go through conversational AI (Gartner study, 2024).
- Poorly rated brands disappear from AI recommendations, or worse, are cited for their shortcomings.
- Google Business Profile remains the foundation on which LLMs draw their local structured data.
- Customer experience becomes the fuel for algorithmic recommendation.
- Anticipating today means locking in your position before your competitors do.
Summary and contents of the page
Understanding GEO and its impact on recommendation undertaken by AIs
GEO, or Generative Engine Optimization, refers to the set of techniques designed to make a brand stand out in the responses generated by conversational artificial intelligences. When a user asks ChatGPT 2026 about “the best organic bakery in Lyon”, the answer isn’t magic. It results from an aggregate of digital signals that the machine has ingested during its training and real-time searches.
First observation in the field: the brands that used to dominate classic SEO are no longer systematically the ones recommended by AI. Why not? Because LLMs (Large Language Models) cross-reference sources that Google didn’t give as much weight to: forums, specialized sites, press articles, customer feedback and, above all, structured customer reviews on site profiles.
A case study of a Parisian restaurateur in 2025 illustrates this shift. His Google Business Profile showed 4.7 stars with 800 reviews. Its direct competitors had a ceiling of between 4.1 and 4.3. When ChatGPT was asked “where to dine near the Marais?”, it cited his establishment in 8 out of 10 cases. Conversational technology favors what comes close to positive consensus.
Signals that AIs scan first
Three families of data dominate. Firstly, the structured data in your company file: opening hours, category, address, photos, attributes. Secondly, the volume and quality of reviews published on Google, TripAdvisor, Trustpilot and Yellow Pages. Finally, mentions of your brand on authoritative third-party sites (local press, specialized blogs, industry directories).
What changes radically with generative artificial intelligence is semantic consistency. If your website says “artisan Neapolitan pizzeria”, but the reviews say “defrosted industrial pizzas”, the AI detects the discrepancy. And it will never recommend you.
SEO and GEO optimization: why your Google Business Profile remains central
The GMB listing remains the lifeblood of your local visibility, even in the age of generative AI. Models like Gemini AI draw heavily on the Google ecosystem to answer geolocation queries. An optimized listing feeds directly into the Local Finder and the local pack, two sources that AIs aggregate to formulate their recommendations.
In concrete terms, a well-maintained GMB entry ticks a number of boxes that the algorithms love. It sends signals of freshness (weekly posts, recent photos, answers to questions). It confirms the establishment’s identity via local justifications. It structures the business attributes (gluten-free, PRM access, free parking) that the AIs exploit to match user needs.
Items that absolutely must be locked
Here are the pillars of a GEO-ready card:
- Consistent NAP (Name, Address, Phone) across the web
- Ultra-precise main category and relevant sub-categories
- Description rich in natural keywords, without stuffing
- Geotagged photos updated monthly
- Regular Google posts with news, offers, events
- Systematic responses to both positive and negative opinions
- FAQ filled in on the form to anticipate queries
A baker in Aix-en-Provence saw his in-store traffic rise by 34% in six months after a complete audit of his file. The trigger? An overhaul of its categories and the addition of 47 geolocalized photos. When Gemini is asked about “boulangerie au levain à Aix”, it now cites it in first position.
Customer reviews and online reputation: the fuel of AI recommendations
Customer reviews have become the raw material for algorithmic recommendations. A 2024 BrightLocal study revealed that 87% of consumers read reviews before choosing a local business, and that conversational AIs weight them up to 40% in their geolocation responses. If your Google rating tops out at 3.8 while your competitors post 4.5, the AI will sort it out without a second thought.
The classic trap: believing that all it takes is a lot of reviews. Wrong. LLMs analyze the semantic content of reviews. A comment like “fast service, smiling team, I recommend” carries more weight than a simple “great!”. AIs detect the positive customer experience markers that turn a customer into an ambassador.
Building an advice-oriented sales strategy
The customer-centric approach is no longer a marketing option, it’s an algorithmic obligation. Solicit your customers at the right moment, after a successful experience. Use a QR code at the checkout, a post-purchase SMS, an automated email 48 hours after the service. The response rate to reviews should be close to 100%, including positive comments.
| Average rating | Probability of recommendation IA | Impact business |
|---|---|---|
| 4.7 and more | Very high | Priority quotation in 70% of requests |
| 4,3 à 4,6 | High | Frequently mentioned, sometimes as an alternative |
| 3,9 à 4,2 | Average | Occasional quotation, never first |
| 3,5 à 3,8 | Low | Evoked only if little competition |
| Less than 3.5 | Near-zero | Risk of being cited for its shortcomings |
One disturbing detail: AIs can now cite a brand for its shortcomings. If your negative reviews converge on “catastrophic after-sales service”, expect to see this phrase rephrased in a ChatGPT response. This is the new frontier of reputational risk.
Digital marketing and artificial intelligence: adapting your strategy to the new driving forces
Traditional digital marketing was based on three pillars: SEO, SEA, social media. GEO adds a fourth dimension that turns the established order on its head. Budgets are gradually shifting towards the production of authoritative content, the fine-tuning of local SEO and the multi-platform orchestration of customer reviews.
The successful brands of 2026 share a common trait: they’ve realized that AIs don’t just read their websites. They scan Reddit, Quora, YouTube comments, X threads, industry blogs. A positive mention on a specialized forum can carry as much weight as a premium backlink. Diversification of sources becomes strategic.
Building a multi-channel presence that LLMs can leverage
Three concrete levers to activate. First, regularly publish expert content on your site (case studies, practical guides, in-depth FAQs). AIs love structured Q&A formats. Secondly, multiply your presence on reliable third-party platforms: industry directories, local press, podcasts. Thirdly, look after your physical establishment in all its digital dimensions (Maps, Apple Maps, Bing Places, Waze).
An independent hairdressing chain in Bordeaux tested this approach in 2025. The result over eight months: a 3-fold increase in spontaneous recommendations in ChatGPT, +52% in online bookings, and above all, greater protection against attacks from false reviews. When reputation is well distributed, an isolated low point is no longer enough to bring down the overall rating.
Anticipating 2026: a reputational project to be launched now
Brands that wait will lose. Competitors who invest in their reputation today are building a cumulative advantage that will be hard to make up. Every review collected, every positive mention, every careful customer interaction feeds a database that AIs will exploit tomorrow. The delay is measured in months, sometimes years.
In the case of multi-store networks and franchises, the complexity of the task is exploding. Coordinating a hundred or so GMB sheets, harmonizing responses to reviews, measuring performance by outlet: without a structured audit and controlled deployment, the risk of drift is immense. A poorly maintained form in a secondary city can pollute the overall perception of the brand.
The first actions to be implemented
Here’s a realistic 90-day plan of attack:
- Complete audit of existing systems: GMB files, customer reviews, web mentions, NAP consistency
- Cleaning up obsolete data and reporting fake reviews
- Setting up an automated and ethical collection process
- Training teams to respond to feedback (both positive and negative)
- Production of expert content on the site and third-party platforms
- Monthly monitoring of spontaneous recommendations by AIs via prompt tests
The ultimate test: ask ChatGPT and Gemini about your sector in your catchment area. If your brand doesn’t appear, you’ve got a problem. If it does, but with negative nuances, you’ve got another problem. In both cases, the work is urgent.
One final point that often grates: managing reviews on secondary platforms such as TripAdvisor requires special attention. Knowing how to modify or dispute a review on TripAdvisor can save an entire season for a restaurateur or hotelier. AIs cross these sources, and an unjustified review left unaddressed ends up contaminating your overall image.
The GEO battle can’t be won in a day. It has to be built, brick by brick, review by review, content by content. Brands that take this shift seriously will see their visibility grow exponentially. Those that drag their feet will see their competitors quote them in ChatGPT responses instead. The choice is up to each executive, but the window of opportunity is closing fast.
