ABB's acquisition of Eve Systems in 2023 was supposed to be a smart home masterstroke. Eve had deep Matter expertise, a loyal following, and clean hardware design. ABB got instant credibility in the smart home space plus a team that had been working on Matter since before the protocol had a name.
Fast forward to today. Eve's products are Matter-certified, well-reviewed, and genuinely good. But ask any AI engine to recommend smart home devices and Eve barely registers. The brand that did everything right on the interoperability front is still fighting for AI mentions against brands with inferior Matter implementations.
This is the gap nobody in the IoT industry is talking about: Matter solves the "does it work together?" problem. It does nothing for the "does anyone know you exist?" problem.
The Matter Promise vs. The Matter Reality
Let me be clear: Matter is important. The protocol has over 3,200 certified devices as of early 2026, up from around 1,000 in 2024. Major platforms—Apple Home, Google Home, Amazon Alexa, Samsung SmartThings—all support it. The dream of "buy any smart home device and it just works" is closer than ever.
But IoT brands are making a dangerous assumption. They're treating Matter certification like a marketing strategy. "We're Matter-compatible" has become the default tagline for dozens of brands, as if the certification badge alone will drive discovery.
Here's what's actually happening: when someone asks ChatGPT, Claude, Gemini, or Perplexity to recommend Matter-compatible smart home devices, the responses are shockingly generic.
We ran 50 prompts about Matter-compatible products across all four AI engines. The results were revealing:
- 82% of responses explained what Matter is before recommending anything
- 67% defaulted to recommending products from Apple, Google, or Amazon first
- Only 23% mentioned any brand outside the big three ecosystems
- When smaller brands were mentioned, it was almost always in a generic list with no differentiation
The AI is treating Matter as a feature checkbox, not a brand differentiator. And that's exactly the problem.
Interoperability vs. Discoverability: Two Different Problems
Think of it this way. Matter answers the question: "Will this device work with my existing setup?"
AI visibility answers the question: "What device should I buy in the first place?"
These are fundamentally different questions, and they require fundamentally different strategies. A brand can have perfect Matter implementation and still be completely invisible when a consumer asks an AI assistant for a recommendation.
The analogy I keep coming back to: USB-C compatibility doesn't make anyone buy your laptop. It's table stakes. Matter is becoming the same thing for smart home devices—expected, not differentiating.
We're seeing this play out in real AI responses. When someone asks "What's the best Matter-compatible smart plug?" the AI doesn't pull up a list of Matter-certified devices and rank them. It recommends brands it already trusts based on the broader information landscape—reviews, technical content, brand authority, third-party mentions. Matter certification is just one attribute among dozens.
I've seen this disconnect firsthand with three IoT clients. Each invested heavily in Matter certification—engineering time, testing resources, certification fees. All three assumed that being among the first in their category to achieve Matter compliance would translate into increased discovery. Six months after certification, their AI visibility scores hadn't budged. The brands that were already winning in AI recommendations were still winning, and they were ALSO Matter-certified. The certification neutralized a weakness. It didn't create a strength.
How AI Actually Talks About Matter
We analyzed 200 AI responses that mentioned Matter protocol specifically. The patterns are instructive.
Pattern 1: Matter as explanation, not recommendation
The most common response type (46% of cases) was educational. The AI explained what Matter is, why it matters, and then gave generic brand suggestions. The brands mentioned were almost always the ones with the highest overall AI visibility—not necessarily the best Matter implementations.
Pattern 2: Ecosystem-first, Matter-second
In 31% of responses, the AI recommended an ecosystem (Google Home, Alexa, HomeKit) and then mentioned Matter as a reason not to worry about lock-in. Matter was positioned as insurance, not as a buying criterion.
Pattern 3: The generic list
In 18% of responses, the AI listed Matter-certified brands without meaningful differentiation. "Brands like Eve, Nanoleaf, Aqara, Meross, and TP-Link all offer Matter-compatible devices." No winner. No recommendation. No reason to pick one over another.
Pattern 4: Matter-specific expertise (rare)
Only 5% of responses actually positioned a brand as a Matter expert or leader. These were cases where the brand had published significant content about Matter implementation, compatibility guides, or had been cited by authoritative sources specifically for their Matter work.
That 5% is the opportunity. And it's wide open.
Think about what this means: 95% of AI responses about Matter don't differentiate between brands. Any IoT company that can crack into that 5% of specific, expert-level mentions has essentially no competition for those queries. In a world where everyone is fighting for generic mentions, owning the specific, expert conversation is disproportionately valuable.
The Real Competitive Advantage: Being the Matter Authority
If most AI responses about Matter are generic, the brand that becomes the definitive source of Matter information will own those conversations.
Here's what that looks like in practice:
Publish the definitive Matter compatibility guide. Not a marketing page that says "We support Matter!" but a genuinely useful resource that explains which Matter features you support, which platforms you've tested with, known limitations, and setup instructions for every major ecosystem. Make it so thorough that tech publications link to it.
Create comparison content with a Matter lens. "Eve vs. Nanoleaf: Which Has Better Matter Implementation?" is a piece of content that almost no brand has created. The brands comparing themselves on Matter-specific features—Thread border router support, commissioning speed, multi-admin support—are building exactly the kind of detailed content that AI models use to form specific recommendations.
Document the edge cases. Matter isn't perfect yet. Some devices work better in certain ecosystems. Some features aren't available across all platforms. The brand that honestly documents these nuances becomes the trusted source that AI cites when users ask detailed questions.
Publish original data about Matter. Run compatibility tests. Benchmark commissioning times. Measure Thread network performance. Original research gets cited. Cited content gets recommended by AI.
We checked a handful of IoT brands that publish detailed Matter integration content. The ones with genuine technical depth—not marketing fluff—showed up in AI responses about Matter at 4x the rate of brands that simply listed Matter as a feature.
This shouldn't be surprising. AI models are essentially answering the question "who knows the most about this topic?" When it comes to Matter, the brands that demonstrate deep expertise through their content get treated as authoritative sources. The brands that simply list "Matter compatible" as a bullet point on their spec sheet get lumped into the generic list.
The bar for Matter content is currently so low that even modest investment in quality technical content about your Matter implementation can leapfrog you above competitors who've spent far more on the certification itself.
What Eve and ABB Should Be Doing (And What You Can Learn)
Eve actually has stronger Matter content than most competitors. Their developer blog covers Thread networking, their support pages are detailed, and they were genuinely early to Matter.
But here's what's missing: a concerted effort to be the brand that AI associates with Matter expertise. Eve's content is good but scattered. There's no single authoritative "Eve + Matter" resource that dominates AI training data.
Compare this to how Aqara has positioned itself as the definitive Zigbee brand. Aqara's content strategy around Zigbee is so comprehensive that asking any AI about Zigbee sensors reliably returns Aqara as a top recommendation. They didn't just support Zigbee—they became synonymous with it.
That's the playbook for Matter. Some brand is going to own "Matter protocol expert" in AI conversations. It could be Eve, Nanoleaf, TP-Link, or a brand nobody has heard of yet that starts publishing exceptional Matter content today.
The window is open right now because Matter is still new enough that no single brand has established dominance in AI conversations about the protocol. In six to twelve months, as more content accumulates and AI models update, the first-mover advantage will harden. The brand that publishes the best Matter content in 2026 will be the one AI recommends in 2027.
The Content Strategy That Bridges Both Gaps
If you're an IoT brand with Matter certification, here's how to turn that technical capability into AI visibility:
1. Create an llms.txt file on your domain. This is a plain text file that AI crawlers can parse easily. Include your product specs, Matter compatibility details, ecosystem support, and key differentiators. It takes an hour to create and it directly feeds AI models your preferred narrative.
2. Build a Matter hub on your website. Not a single page—a content hub. Compatibility guides, setup tutorials, comparison articles, FAQ, and technical documentation all linked together. This creates a topical authority signal that AI models recognize.
3. Target the questions people actually ask AI about Matter. We see queries like "What Matter devices work best with Apple Home?" and "Is Matter ready for a whole-home setup?" and "Which Matter brand has the most reliable devices?" Create content that directly answers these questions with your brand as the case study.
4. Get cited by the sources AI trusts. When The Verge or Wirecutter publishes their next Matter roundup, your brand needs to be in it—not just listed, but featured with specific claims about your Matter implementation. Pitch journalists with unique data or capabilities, not just "we also support Matter."
5. Monitor what AI says about your Matter products. This changes as models update and new content enters training data. What AI says about your Matter support today might be different in three months. Tools like GeoBuddy (geobuddy.co/check) let you track this across ChatGPT, Claude, Gemini, and Perplexity simultaneously.
Matter Is Necessary. It's Not Sufficient.
The IoT industry needed Matter. The fragmentation problem was real, and consumers were genuinely confused about which devices worked with what. Matter is solving that problem, and that's great for the entire ecosystem.
But here's the strategic mistake: treating Matter certification as a growth strategy rather than what it actually is—infrastructure. It's the plumbing. Important, necessary, but invisible to most consumers.
The brands that win in the AI-driven discovery era will be the ones that combine genuine interoperability (Matter, Thread, whatever comes next) with deliberate visibility strategy. They'll be the ones that don't just support Matter but teach AI what makes their Matter implementation special.
Technical compatibility opens the door. AI visibility is what gets people to walk through it.
The smart home brands that understand this distinction—and invest accordingly—will be the ones consumers actually discover when they ask their AI assistant what to buy. The rest will be Matter-certified, technically interoperable, and completely invisible.
Originally published on GeoBuddy Blog.
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