From Keywords to Context: Why Generative AI Optimisation Depends on Relevance, Not Rankings

From Keywords to Context: Why Generative AI Optimisation Depends on Relevance, Not Rankings

Back in the day, you could rank on Google by stuffing keywords everywhere. Title tags, meta descriptions, blog posts, just cram in the focus keyword and hope for the best. It wasn't pretty, but it worked. Fast forward to now, and AI systems like ChatGPT are rewriting the rulebook on visibility.

Here’s the thing: these generative engines don’t behave like traditional search engines. They don’t think in keywords; they interpret context. And if your brand isn’t showing up in their answers, it doesn’t matter how good your site SEO is. You're invisible in the conversations people are having, where decisions are made and recommendations are acted on. Visibility in AI prompts isn’t about ranking; it’s about relevance.

The shift from rankings to relevance

In my experience, the penny dropped on this when we started running experiments across generative AI systems in our Contxt network. Across 2881 prompts (a hefty dataset), the results were crystal clear: AI visibility isn’t as simple as being “optimised” for search queries anymore. In fact, 39% of the time, ChatGPT and Google’s AI Overview gave conflicting recommendations. So, if you’re visible on one, you’re far from guaranteed a mention on the other.

Here’s an example of what I mean. Say you’re a manufacturing company (like Iconsys 2, one of the brands we track). In traditional SEO, you’d target keywords like “industrial automation solutions” and try to rank for that phrase. But in our AI data, Iconsys 2 had an abysmal mention rate, just 6.7% overall, despite fitting the criteria perfectly. Related reading: this piece about top 25 llm visibility tools compared: features, pricing &.... For a deeper look, have a read of this piece about content, links, technical: the seo trinity took 25 years .... Why? Because the AI systems are responding to the broader context of the prompts, not just plucking out keyword matches.

Why context matters more than keywords

When someone asks an AI system about industrial automation, they’re not typing in exact-match phrases the way they might in Google. Instead, they’re asking broader or conceptually deeper questions: “What’s the best option for factory robotics?” or “Who supplies automation tech that integrates with existing workflows?” That brings nuance into play. The AI interprets intent, not syntax.

This is why brands with strong contextual relevance outperform those clinging to keyword optimisation. Take Viking Pumps, a brand with 100% AI visibility across the network. They’re not just hanging their hat on a single phrase like “industrial pumps.” Instead, their visibility comes from aligning content with a range of contexts predicted in relevant AI prompts. Related reading: our article on prompt engineering for visibility: how brands can influen.... Related reading: this piece about trust metrics decoded: how enterprises can evaluate the c.... That’s proper context-driven AI optimisation.

Our data backs this up too. Of the 1016 unique prompt variations tested, brands like Viking Pumps and Red Fern consistently surfaced because their digital presence connected dots beyond basic phrases. On the flip side, low visibility brands like TOCA Social (sports tech) hovered at just 10% mention rate because, frankly, the AI couldn’t find enough context to recommend them.

How brands can pivot to context-driven strategies

So, what actually works? Historically, optimising for Google was a bit prescriptive, find keywords, build content around them, repeat. AI visibility is more like turning up at a party with the right conversation starters. You need to understand the dialogue your audience is having, not just the topic.

Here’s how to make that shift:

1. Analyse prompts systematically. Start by mapping the kinds of questions your audience might ask generative AI. In our experiments, buying-intent prompts were particularly revealing. For instance, brands recommended in “best options for” scenarios had far higher mention rates than under generic “tell me about Y” prompts. If you’re not tracking prompt sensitivity, you’re missing critical visibility insights.
2. Expand your semantic footprint. Think about contextual depth. If you’re only targeting a specific niche phrase, you’ll struggle when the AI interprets broader related concepts. One test we ran on feature-attribution prompts showed that brands connecting multiple elements (e.g., reliability, scalability, and compatibility) were picked far more often than one-trick ponies.
3. Create content for intent-driven queries. Forget the days of “10 ways to optimise X”; AI visibility thrives on answering multi-layered questions. For instance, a prompt like “Which industrial automation tools integrate well with PLCs?” needs content that positions you as a clear fit. If it’s not already on your site, you’re invisible in the AI’s answer set.
4. Test across platforms. Don’t assume visibility on one generative system guarantees success across the board. Our data showed Claude had an impressive 78.5% mention rate in prompts tested, while Google AI Overview was way down at 45.5%. You need to optimise for each system, not just generative engines as a concept.

Two common mistakes to avoid

Now, a quick word of warning: AI visibility is a bit of a minefield and not without its pitfalls. Here are two missteps I’ve seen time and again:

1. Over-focusing on one provider
A mate of mine runs an agency for e-commerce brands, and they obsess over ChatGPT. They’ve built loads of optimised prompts for it, which is great, except they’ve completely ignored Google’s AI Overview. Bad move, because ChatGPT and Google disagree 39% of the time in recommending brands. Related reading: this piece about how b2b enterprises can dominate llm visibility in ai sys.... You can AI visibility tracking features to see for yourself. If you’re only betting on one horse, you’re leaving visibility on the table.

2. Ignoring prompt sensitivity
If you think creating static optimised content will work across all queries, think again. In our buying-intent tests on 12 businesses, brand mention rates swung wildly depending on the query type. One case had a brand recommended in “top options” prompts but completely absent under “reliable choices for X”. You can how AI visibility monitoring works to see for yourself. If you’re not running prompt-specific tests, you might be invisible in half the contexts that matter.

Actionable steps for brands in the AI era

Look, I get it. Shifting from keyword-heavy strategies to context-driven AI optimisation sounds overwhelming. But it’s not rocket science if you break it into manageable steps. Here’s what I’d suggest:

1. Start small with intent analysis. Pick three core audience intents relevant to your business. For example, if you’re in B2B SaaS, look at queries like “tools for scaling teams” or “software for remote collaboration.”
2. Run experiments on generative engines. Test prompts across multiple systems (ChatGPT, Claude, Google AI Overview, etc.) to understand where your visibility gaps are. If a specific platform is underperforming, it’s likely a contextual alignment issue.
3. Build semantic depth. Expand your content library to answer multi-layered queries. If all you’ve got is surface-level articles, the AI won’t see you as contextually relevant. FAQs, case studies, and detailed guides work wonders here.
4. Monitor brand recall regularly. From our data, brands with consistent tracker runs (85 completed across the network) saw steady improvements in their visibility. It’s not a one-and-done effort; you need continuous optimisation.
5. Optimise for cross-provider divergence. Use the 39% disagreement rate between providers as a reminder that different systems interpret prompts differently. Target each one with tailored strategies and measure regularly.

Final thoughts

At the end of the day, AI visibility is about connecting with your audience’s intent, not guessing at keywords. The era of generative engines forces us to rethink optimisation as a dialogue, not a ranking game. And let’s be honest, it’s better this way. Who wants to wade through keyword-stuffed fluff when you can build meaningful, context-rich visibility instead?

If you’re ready to stop being invisible, check out Contxt’s platform. We specialise in context-driven AI optimisation and have all the data you need to see where your brand stands, and how to improve it.

Right, time for a pint. But before I go, here’s your next step:

Grab three recent pieces of content from your site, run them through prompts on ChatGPT, Claude, and Google AI Overview, and see if your brand shows up. If not, you’ve got work to do.