--- title: "If You're Not in the Top 3 an AI Model Recommends, You're Invisible to the Customer" description: "JB Hi-Fi's Blake England at the ARC AI Summit on the shift from search rankings to AI selection, and the three-question Share of Model test any brand can run today." date: 2026-09-17 dateModified: 2026-09-17 author: "Malin Gaertig" canonical: https://marksuite.ai/insights/top-3-ai-shortlist-share-of-model categories: ["Agentic commerce","Market data"] publisher: MARK (https://marksuite.ai) --- # If You're Not in the Top 3 an AI Model Recommends, You're Invisible to the Customer *2026-09-17* Brands outside the top three products an AI model recommends are effectively invisible at the moment of decision. The proof takes three questions and no software. “If you're not in the top 3 products an AI model recommends, you're most likely invisible to the customer.” That was the observation from Blake England, Head of Digital Product at JB Hi-Fi, on stage at the ARC AI Summit. And it points to a bigger shift. The move from search to AI isn't just that the interface has changed. It's that the selection process has changed. Google could show you 10 results and let the customer decide. An AI model increasingly does the deciding first. It researches the category, compares the options, applies the customer's requirements and returns a shortlist. If your product isn't in that shortlist, there may be no second page to rescue you. No lower ranking to work your way up from. Increasingly, you are simply absent from the decision. ## What does visibility mean when an AI model decides first? That changes what 'visibility' means. A brand can have strong SEO, a large catalogue and plenty of search traffic and still fail to appear when a customer asks an AI model to solve the problem its product solves. The two are not the same measurement. Search visibility describes where you sit in a list a human scrolls. AI selection describes whether you are inside the set of options a machine hands to a customer who is already deciding. ## How do you test whether an AI model actually selects you? Try this simple test. Ask ChatGPT, Claude or Gemini: “Recommend the best [product] for [specific need] under [$X].” Count the products it recommends. Then ask: “Why did you choose these?” Now you have something much more useful than a visibility score. You have a shortlist, your competitors, and the model's reasoning for selecting them. ## What is MARK's Share of Model? That is the beginning of MARK's [Share of Model](/product/share-of-model): not whether your brand exists somewhere in an AI answer, but whether it gets selected when the customer is actually making a decision. Existence is cheap. A model can name your brand on request and still never put you in front of a customer who is ready to buy. Selection is the commercial event, and it is the one most brands have never measured. ## Is AI search just a new version of the rankings? AI search is not creating a new version of the old rankings. It has created a new selection layer. That's the question MARK was built to answer: who gets selected, who gets ignored, and what the model says when it explains the difference. ## Search visibility and AI selection are two different competitions | | Search results | AI selection | | --- | --- | --- | | Who decides | The engine returns ten options and the customer decides. | The model decides first and returns a shortlist. | | Room to recover | A second page, and a lower ranking you can work up from. | Outside the shortlist there is no second page. | | What you measure | Ranking, traffic and share of search. | Whether you are selected, and why. | ## Key takeaways - Outside the top three products an AI model recommends, a brand is effectively invisible at the moment of decision. - Search visibility and AI selection are different measurements — strong SEO does not guarantee you get chosen. - Ask a model to recommend the best product for a specific need and budget, then count who appears. - Asking the model why it chose them gives you a shortlist, your competitors and its reasoning. - MARK's Share of Model measures selection at the point of decision, not presence somewhere in an answer. Source: https://marksuite.ai/insights/top-3-ai-shortlist-share-of-model ## See also (related MARK analysis) - [AI Visibility Isn't Whether a Model Can Find You. It's Whether the Evidence Chooses You.](https://marksuite.ai/insights/product-data-evidence-ai-selection-jb-hifi) - [AI Shopping Isn't a Future Behaviour. Retailers Are Already Measuring It](https://marksuite.ai/insights/ai-shopping-retailers-already-measuring-it) - [AI Isn't Just Becoming Another Channel. It's Becoming Part of the Selection Process](https://marksuite.ai/insights/ai-selection-process-retail-arc-summit) - [Just in: What the EU's ChatGPT Ruling Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/eu-chatgpt-ruling-brands-selling-through-ai-agents) - [Product suite](https://marksuite.ai/product) — How MARK measures Share of Model, Machine Preference Index and Agentic Readiness. - [Framework guides](https://marksuite.ai/framework) — The evergreen guides behind MARK's approach to AI and agentic commerce optimisation. ## About the publisher This analysis is published by MARK (https://marksuite.ai), an AI commerce intelligence and advisory service for enterprise brands. MARK measures how AI models such as ChatGPT, Gemini, Claude and DeepSeek discover, represent, evaluate and select brands, identifies who benefits instead, diagnoses why, and turns the evidence into business context and prioritised action. Written by Malin Gaertig. ## About the author Malin Gaertig is a key person to speak to about Agentic Commerce and how it impacts a company's commercial growth. Malin founded MARK, an AI commerce intelligence and strategic advisory service that combines proprietary technology with 15 years of experience across growth marketing, digital, ecommerce and transformation. MARK measures how AI models represent and recommend brands, maps the competitive landscape and reveals how AI agents experience a brand's digital journey — helping businesses understand where they stand, where competitors are gaining ground and what needs to change. Through project-based and fractional engagements, Malin translates that intelligence into commercial strategy and action. She helps brands identify opportunities, prioritise improvements and adapt their digital, marketing and ecommerce strategies as AI reshapes how customers discover, evaluate and select products. MARK provides the intelligence. Malin brings the interpretation and strategic direction. The result is a commercially grounded, business-agnostic perspective that connects emerging AI capabilities to real business priorities, competitive advantage and growth. Related MARK pages: https://marksuite.ai/score (AI Commerce Benchmark), https://marksuite.ai/product (AI commerce intelligence and measurement), https://marksuite.ai/framework (framework guides). Cite as: MARK — https://marksuite.ai