Most brands treat AI search as one thing and try to be everywhere at once. That is the wrong instinct. Here is a practical way to rank ChatGPT, Gemini, Amazon Rufus, Perplexity and Claude by user base, citation behaviour and how close each one sits to a purchase, so you spend where it actually moves sales.
Which AI Platforms Actually Matter for Consumer Brands (and How to Prioritise Them)
By Stephen Honight, Founder of Lmo7
The question I get asked more than any other right now is some version of “which AI platforms should we actually care about”. It came up in seven separate client and prospect conversations in the last two weeks alone. Everyone can feel that AI is changing how people find and choose products. Very few people have a clear way to decide where to put finite time and budget.
The unhelpful answer is “all of them, AI search is the future”. The useful answer is a ranking, because you cannot resource all of them properly and you should not try.
My sense is the reason brands get stuck here is that the market keeps talking about “AI search” as if it were a single surface. It is not. ChatGPT, Gemini, Amazon Rufus, Perplexity and Claude behave differently, pull from different sources, and sit at different distances from an actual purchase. Treat them as one thing and you spread effort evenly across surfaces that deserve very different levels of attention.
So before the ranking, the mechanism. Once you see what actually separates these platforms, the priority order falls out on its own.
Three things that separate the platforms
There are three variables that matter when you decide whether a surface is worth your effort.
The first is the user base. How many people use it, and are they your buyers or someone else’s. A platform with huge reach among the general public is worth more to a consumer brand than a platform with a smaller, more specialist audience, even if the specialist platform is technically excellent.
The second is citation behaviour. Each model builds its answers from different sources. Some lean heavily on Reddit and YouTube, some lean on classic web content and news, some pull from the retailer’s own catalogue. This matters because it tells you what work actually moves your visibility on that surface. The content play for one platform is not the content play for another.
The third, and the one most people skip, is commercial proximity. How close is the surface to the moment of buying. Someone asking an assistant to compare running gels while planning a long ride is closer to a purchase than someone reading a general explainer. A surface that sits right next to the checkout is worth more per unit of effort than one that sits at the top of the funnel, because the path from mention to sale is shorter.
Rank a platform on those three and you get a clear read on whether it deserves a lot of your attention, some of it, or very little for now. Let me walk the surfaces in the order I would actually prioritise them for a mainstream consumer brand.
ChatGPT and Gemini are the primary consumer surfaces
For most consumer brands these are the two to focus on first, and by a distance.
The reason is reach. ChatGPT is where the general public has gone to ask questions, including product questions. When a shopper asks “what is a good magnesium supplement for sleep” or “which functional drink actually helps with focus”, ChatGPT is increasingly the surface answering. That is your buyer, in your category, at a moment of genuine consideration. The commercial proximity is high because the recommendation and the shortlist happen right there in the conversation.
Gemini matters for a related but slightly different reason. It sits inside the Google ecosystem, which means it is woven into the surfaces people already use, and it pulls heavily on sources like YouTube. In our own Share-of-Model work across client categories we see Gemini and ChatGPT behave quite differently on the same question. A brand can hold a strong position in one and be nearly absent in the other, which is exactly why you have to report on them separately rather than as a blended “AI visibility” score.
The practical implication is that your first block of effort, the content, the tracking and the paid testing, should go here. ChatGPT now has an ads product live in the UK, which means these surfaces are not only where you earn organic mentions but also where you can start buying presence in the conversations that matter. That combination, high reach and high commercial proximity with both an organic and a paid lever, is what puts them at the top.
Amazon Rufus and Alexa for Shopping are the on-platform buying surface
If ChatGPT and Gemini are where the shopper researches, Amazon’s assistant is where a lot of them buy.
Rufus, now folded into Alexa for Shopping, is a different kind of surface. It does not sit at the top of the funnel. It sits on the retail platform itself, next to the Buy Box, at the point where someone has already decided to spend. The commercial proximity here is as high as it gets. When Rufus answers “which of these is better for sensitive skin” on a product page, the next click can be a purchase.
The citation behaviour is different too. Rufus is not pulling from Reddit or YouTube in the same way the open assistants do. It reads your PDP, your A+ content, your reviews and your Q&A. That is good news, because it means the work is largely within your control. The listing content you already own is the substrate the assistant draws on. This is why PDP rewrites for AI recall have become close to a default deliverable across almost every Amazon engagement we run now.
The catch is that Rufus only matters if Amazon is a meaningful channel for you. For a brand doing serious volume on Amazon it belongs right behind ChatGPT and Gemini, sometimes level with them, because the distance from an answer to a sale is so short. For a pure D2C brand with no real Amazon presence it drops down the list. This is the first place the ranking becomes category and channel dependent rather than universal.
Perplexity and Claude are lower priority for mass consumer, for now
This is the part that surprises people, because both are excellent products.
Perplexity and Claude are genuinely good at what they do. But for a mainstream consumer brand they are lower priority right now, and the reason is the user base. Both skew toward business, professional and technical users rather than the general shopping public. If you sell a supplement, a spirit, a snack or a skincare product to ordinary consumers, a smaller share of your actual buyers are making purchase decisions inside Perplexity or Claude today than inside ChatGPT, Gemini or Rufus.
That is not a permanent judgment. Audiences shift, and if your category genuinely skews professional then the calculus changes. A B2B tool, a developer product or a specialist professional brand should weight these two far higher, because that is where their buyers actually are. The point is not that these platforms do not matter. It is that for a mass consumer brand with finite budget they are not where the first or second block of effort should go.
I would still track them. Watching where you stand costs little through the data layer and it tells you early if the audience is moving. I just would not build a content and optimisation programme around them ahead of the three surfaces that sit closer to your buyer and closer to the sale.
Why this is a ranking, not a league table
The one thing I would push back on is the idea that there is a single correct order that applies to every brand. There is not.
The framework is the three variables. The order is what you get when you run your own category through them. A spirits brand and a sports nutrition brand and a consumer health brand will not land in exactly the same place, because their buyers behave differently and their channels weigh differently. When we did the GEO and AI visibility work for Brown-Forman on Jack Daniel’s, the citation pattern across engines looked different from what we see in supplements, because the sources people trust when they talk about whisky are not the sources they trust when they talk about vitamins.
So the honest version of this is: ChatGPT and Gemini first for almost everyone, Rufus and Alexa for Shopping right up there if Amazon is a real channel for you, Perplexity and Claude lower unless your audience is genuinely professional. Then adjust for your own category using real data rather than assumption. The framework holds. The exact order is yours to work out.
There is a limit worth being straight about. Knowing which platforms matter is the easy half. Actually moving your position on them runs into the same constraint everything in AI search runs into, which is authority. On the open assistants, the models weight third-party sources they already trust, so a clean piece of content on your own site only goes so far without the citations and mentions behind it. That is the long game, and it sits alongside the quicker content and structure work rather than replacing it. Do not let a neat platform ranking convince you the visibility problem is solved once you know where to look.
What to do next
If you take one thing from this, let it be that “be everywhere in AI search” is not a strategy. Pick the surfaces that match your buyers and your channels, and resource those properly.
Here is where I would start, in order.
Get a baseline first. Before you commit budget to any platform, find out where you actually stand on the ones that matter for your category. Track mention rate and average position on ChatGPT and Gemini as your two primary surfaces, add Amazon Rufus if Amazon is a real channel, and keep a light watch on the rest. This is the DaaS layer, direct access to the tracking data so your team can see the picture and read it themselves. It is the cheapest way to replace assumption with fact.
Then fix the surface closest to your sales. If Amazon matters to you, the PDP and A+ content that Rufus reads is the highest-impact, most controllable work you can do, because you own the substrate and the answer sits next to the Buy Box. This is Challenger work, the Amazon Content Optimisation module, and it is where effort maps most directly to a sale.
Then build presence on the two primary consumer surfaces. Content and tracking for ChatGPT and Gemini, and where it fits, testing the ChatGPT ads product that is now live in the UK. This is the Agentic Stack, tracking and content optimisation together, run as a loop rather than a one-off because the models and your competitors keep moving.
If you are a multi-brand business, the prioritisation itself becomes the deliverable. Working out the right platform order across a portfolio, where the categories differ brand by brand, is an Enterprise conversation. It is the kind of structured, stakeholder-facing decision a workshop and a multi-brand Share-of-Model programme are built for, and it stops different teams each guessing at their own answer.
My recommendation for most brands reading this would be to start with the baseline. Once you can see where you stand on the surfaces that matter, the order you should work in stops being a debate and becomes obvious.
Lmo7 helps consumer brands win in AI-powered discovery and agentic commerce, across Amazon, ChatGPT, Gemini, Google AI and Amazon Rufus. We work with brands including Trip Drinks, Veloforte, Brown-Forman, Haleon, Pelotan and Symprove. If you want to know which AI platforms actually matter for your category, and where you stand on them today, get in touch at lmo7.com.