The 5 Secrets to Exist in ChatGPT When Google Forgets You
How to Get Referenced in LLMs: The New Challenge for Retailers
Remember when having a website was optional? Then the era when being absent from Google meant you didn’t exist. Today, we’re experiencing a comparable but faster shift: Large Language Models (LLMs) like ChatGPT, Claude, or Gemini are redefining online visibility—and most retail brands are unprepared for this tsunami.
I observe this shift daily at WISHIBAM. The question is no longer “how to rank on Google’s first page,” but rather “how to be THE answer that AI recommends directly to consumers.” Because when a customer asks ChatGPT “which store offers the best running shoes in Paris?”, either your brand appears, or you’re invisible. No intermediary, no page 2, no second chance.
Below I share concrete strategies we’ve developed to help retailers thrive in this new paradigm. Discover why LLMs disrupt your visibility, which levers to activate immediately, and how to turn this revolution into a strategic opportunity for your business.
Why LLMs Are Changing the Game for Your Online Visibility
Answer Engines Are Replacing Search Engines: Are You Ready?
Just yesterday, SEO, keywords, and backlinks were the priorities. They still matter but are now insufficient. LLMs don’t just improve search—they radically change the rules.
Google showed you 10 links. ChatGPT gives you ONE answer.
The numbers speak for themselves: Google has lost 8% of its traffic since ChatGPT launched. Microsoft has integrated AI into Bing. Google is countering with Gemini. The trend is clear and accelerating.
For retailers, stakes are enormous. With Google, a store searching for “evening dress Lyon” had probable visibility among many results. With an LLM, either you appear in THE answer provided, or you don’t exist, period.
My own tests on various AIs revealed only retailers with:
- Structured digital presence
- Precise, up-to-date local data
- Plenty of customer reviews
…were cited. All others, even local leaders, were absent.
The most alarming part? Most retailers don’t even realize the problem and are still optimizing for a world that’s already vanishing.
72% of Consumers Trust AI-Generated Responses: Is Your Brand in the Loop?
According to a Salesforce study, nearly three out of four consumers trust AI-generated responses. This trust is transforming the purchase journey.
What does it mean concretely? LLM recommendations have a prescriptive effect. When ChatGPT lists stores for a designer sofa, users take it as truth—not just a suggestion.
The effect on store traffic is palpable. One of our partners saw a 23% jump in store visits after optimizing for LLM visibility. Another, segment leader yet absent from AI, saw footfall decrease correspondingly.
This trust stems from:
- Perception of AI objectivity (rightly or wrongly)
- A conversational format that personalizes the relationship
- The convenience of getting an instant, synthetic answer
But beware: this trust can turn against you if LLMs use outdated, incomplete, or totally wrong info about your brand. Incorrect hours or product listings, for example, have caused retailers massive revenue loss.
The real question now is: how do you ensure your brand is correctly positioned in this new channel of influence?
Concrete Levers to Appear in AI Responses
Create Useful, Structured, and Human Content: LLMs Love Expert, Authentic Voices
Forget generic keyword-stuffed content. LLMs are designed to recognize and reward true expertise and authenticity. What works, based on our testing with 30+ retailers:
- Demonstrable expertise: Showcase your real knowledge, know-how, innovations. A cosmetics brand we worked with saw visibility surge after publishing behind-the-scenes articles on their artisanal manufacturing.
- Clear semantic structure: LLMs parse hierarchized HTML (titles, lists, tables) more easily. One fashion site reorganized product sheets and saw mentions in AI answers jump by 2.7x.
- Human, authentic tone: Paradoxically, AI prefers content sounding human. Use anecdotes, real case studies, speak plainly. An appliance retailer replaced technical compostion sheets with user story scenarios and increased AI mentions by 40%.
- Freshness and regular updates: LLMs value up-to-date info. Date articles, provide market commentary, and keep your site alive. A home decor client publishing monthly trends is now a go-to LLM citation for new decorating searches.
The common mistake? Investing in mass-produced, generic articles and superficial optimizations. LLMs reward genuine value, not tricks.
Brands sincere and modest in digital communication often become indispensable references in AI answers—while big budget, generic content goes unseen.
Optimize Your Local and Product Data: Without Reliable Data, No LLM Visibility
If content is king, then structured data is queen in the LLM universe. Here’s how to optimize:
- LLMs need data: If a user asks for “Nike Air Max in Lyon, same-day delivery”, AI can only recommend stores with this information online—and in a usable format.
- Our analysis shows 78% of retailers have major data inconsistencies. Wrong hours, out-of-date stock, poorly listed services. These make you invisible, even if ranked well on Google.
Prioritize:
- Local data: Precise addresses, current hours, in-store services—update in Google Business Profile, Yelp, TripAdvisor, directories.
- Product data: Detailed descriptions, tech specs, stock, delivery options—consistent everywhere: site, marketplaces, socials.
- Relational data: Customer reviews, FAQs, post-sales support—LLMs elevate trustworthy signals.
Case study: A sports store chain harmonized data across all POS and saw a 34% boost in LLM appearances in two months. Conversely, a competitor with outdated hours during Covid was blacklisted as unreliable.
Good news: while SEO takes months, LLM data optimization shows results in weeks—a quick ROI.
Retailers: How Wishibam Helps You Exist in the Post-Google Era
Sovereign Data Centralization: Feed AIs With Your Data, Not Your Competitors’
In the face of LLM revolutions, controlling your data equals survival. At WISHIBAM, we offer a unique, sovereign data centralization solution tailored for retail in the AI era.
The key issue? Fragmented data—spread between ERP, CRM, PIM, PoS systems, marketplaces—which LLMs interpret as unreliability.
- Our platform centralizes all local and product data in real time,
- Normalizes the format for LLMs,
- Distributes updated info to all digital channels.
And sovereignty is critical: unlike US solutions that can reuse or resell your data, our European approach keeps you in control—you own your data.
Success story: For a major ready-to-wear chain: 120 stores and 15,000 products centralized. When a user asks ChatGPT for a specific Sandro dress in size 38, our client appears first thanks to structured, reliable data.
Centralization also means:
- Automatically enriching data with what LLMs need (attributes, services, options)
- Agile reaction: update once and it’s instantly live everywhere—a true competitive edge.
An Omnichannel Strategy for Humans—Understood By AIs
The usual error? Treating LLM optimization as purely technical. In fact, AIs seek to copy and augment human behavior. A successful strategy must speak to both customers and algorithms.
- Unified customer experience: Seamless digital/physical journey—what LLMs love to recommend.
- Leverage physical assets: Try-ons, expert advice, instant pick-up—our platform packages these for LLM understanding.
- Smart use of client data: We turn interactions into LLM-friendly trust signals—with privacy preserved.
Example: Appliance store chain, QR codes in-store linking to expert content, perfectly structured for both human and AI reading. Result? 68% LLM response rate in their segment.
Our holistic vision means LLM optimization is integrated in overall strategy—leading to gains across online, offline, and now in AI answers.
Conclusion: Prepare Now for the Post-Google Era
The LLM revolution isn’t coming—it’s here, transforming how consumers discover and pick brands. For retailers, future visibility relies on being in direct AI answers, not just Google search.
Brands that quickly structure their data, prove their expertise, and unify their omnichannel voice will win. The rest will struggle to catch up later—when the game is already set.
At WISHIBAM, we guide retailers through this change daily. Our core belief: technology should serve humans, not rule them. Our approach blends technical mastery with a deep knowledge of retail realities.
The only real question: not if LLMs will change your business, but how you will stay relevant in the new paradigm. Are you ready for the post-Google era?
FAQ: How to Be Referenced in LLMs
Which major LLMs are already influencing consumer purchasing decisions?
Currently, ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), and Copilot (Microsoft) are most used by consumers for buying decisions. Each has its specifics, but all provide direct recommendations, often bypassing traditional search.
How long does it take to improve visibility in LLM responses?
Unlike classic SEO (6-12 months), LLM optimization can show results in 4-8 weeks. Centralizing and structuring data yields rapid impacts, while building content authority takes longer.
Can small independent businesses be visible in LLMs alongside big retailers?
Absolutely! LLMs favor local expertise and authenticity. A small specialized store with well-structured data and expert content can outperform a national chain in its niche.
Should specific content be created for each LLM or is a unified strategy enough?
A unified, high-quality strategy works across all major LLMs: they all value expertise, structured and consistent data, and authenticity. Fine differences are secondary to these essential principles.
How do you measure the effectiveness of an LLM optimization strategy?
At WISHIBAM, we combine metrics: systematic query tests in various LLMs, analyzing AI-originated traffic (via UTM), and correlation with in-store visits. We also use our unique “LLM Readiness” score to gauge preparedness.
Does paid advertising already exist in LLMs and how should we prepare?
Some LLMs (e.g. Claude AI) are starting to test sponsored answers, but for now the most sustainable tactic remains organic optimization. Brands building trust now will be best positioned for future LLM ad formats.
Charlotte Journo-Baur, Founder of WISHIBAM
Recognized among the top 0.1% most influential retail experts in Europe