David Haas has spent close to 30 years in marketing. He’ll tell you the last year has been unlike any of the ones before.
David’s niche is growth-stage tech and healthcare companies. They’re organizations with a budget to invest but no in-house SEO team or dedicated content function. His job is to make them achieve as much success as companies with more resources.
“A solution like Semrush One is an incredible advantage for these companies—typically, they won’t have enough resources and expertise in-house.”
AI answer engines have opened a new opportunity for smaller brands to be discovered through. And David has built a repeatable framework that those brands can use to excel.
Here’s how he did it for Frenos, an operational technology cybersecurity company—going from near-zero search presence to growing market visibility in under six months.
The ‘Foundation Up’ Framework
When David Haas sits down with a new client, the conversation about strategy almost always ends up in the same place: You have to build the base before you build the rest of the tower.
Growth-stage teams are often tempted to jump straight to AI visibility—it feels faster, newer, more exciting. But David knows that without a solid SEO foundation, any AI visibility gains are fragile. Build both layers deliberately, in sequence, and they start to reinforce each other.
“I tend to sit down and talk strategy, and it always seems to gravitate toward building a solid SEO foundation first, and then building the AI plan on top of that. Once you’ve gotten that and built out your content and backlink strategies, it all just builds on itself.”
The result?
Frenos went from near-zero search visibility on Google in July 2025 to a score of 18.32% in January 2026—outpacing multiple competitors in a niche, highly technical market.
This is also reflected in how the brand appears in Google’s AI Overviews, with overall visibility steadily increasing over time.
Let’s go over the exact workflow David built to help Frenos grow their search presence.
Step 1: Establish an SEO Baseline First
David’s first move was to measure performance and identify opportunities based on real search data.
He started with the Keyword Magic Tool and the Keyword Overview Tool to find buyer-intent queries that decision-makers were actually searching.
Chasing high-volume terms sounds appealing, but it rarely pays off for a company without much existing authority. For Frenos, David ruled out broad terms like “ot cybersecurity.” Because it’s too competitive and offers too little upside.
Instead, David focuses on buyer-intent queries, low-to-moderate difficulty terms, and technical searches relevant to OT cybersecurity decision-makers
Then, he sets up Position Tracking to establish where the brand stands against its direct competitors across key search terms.
Step 2: Measure the AI Visibility Baseline
While establishing an SEO baseline, David also opens the AI Visibility Toolkit to understand where the brand stands in AI-generated answers.
It’s a separate picture from isolated search rankings and, increasingly, the one that matters to buyers. In fact, our recent survey of over 1,000 U.S. consumers found that 50% have made a purchase after using AI during research, across categories and price points.
David checks the AI Visibility score first. For Frenos—as with almost every small brand he works with—it came back around 14.
“It’s a great place to start. It kind of gives people a sense of: Am I showing up a lot? Am I showing up a little?”
Then, he uses the Competitor Research tool to see how rivals’ AI visibility scores and prompt mentions compare. It tells him exactly where the client stands and where there are gaps worth going after.
David also cross-references AI opportunities uncovered via the AI Visibility Toolkit with manual community research—reading forums where real buyers ask real questions—to get a fuller picture.
“Semrush is giving you a very specific set of prompts, which are good, but community research is an augmentative way to look at a bigger picture and create content that is really going to resonate.”
Each page that comes out of this process is built to do two things at once:
- Rank in traditional search
- Be retrievable by AI answer engines
That means clear structure, direct answers, and content that’s genuinely useful—written for a person who just asked a question in ChatGPT.
“You’ll see them move from not being mentioned to being mentioned in a week or two weeks. Which is wild.”
Step 3: Build Topical Authority with Pillar Pages and Cluster Content
Once the search-optimized pages are live, David builds out a pillar-and-cluster structure around the topics that matter most to the client.
For Frenos, that meant comprehensive pillar pages on topics like OT penetration testing and industrial cybersecurity testing. Content aimed at buyers who are researching a problem but aren’t yet ready to buy.
Cluster content then went deeper on each theme: specific use cases, technical FAQs, and subject-matter expertise that gradually introduced Frenos as a credible voice.
All content in a cluster links together deliberately—cluster pieces back to pillars. And the pillar pages also reference credible external sources.
The effect over time was that Frenos started ranking not just for individual keywords but across whole topic areas. Because the site had built authority around those topics.
Step 4: Treat Keyword and Prompt Research as an Ongoing Loop
The final ingredient in David’s framework is iteration. As content goes live and performance data starts coming in, the strategy gets smarter.
He watches for content climbing toward page one on Google, gaining traction on long-tail queries, and spotting gaps where competitors are vulnerable.
David returns to the Keyword Magic Tool and Visibility Overview regularly, using live performance signals to decide what to write next and what to cut.
“SEO accelerates when data informs strategy—and strategy guides content.”
Why the Framework Works
Modern buyers don’t just type keywords into Google. They ask full questions in ChatGPT. They read Reddit threads before they ever visit a vendor website. They get answers from AI Overviews before clicking anything.
According to our recent research, most buyers use AI and search together. About 33% start with search engines, then switch to AI to summarize or compare. Another 26% do the opposite. Only 8% don’t use them together at all.
David’s framework reflects that reality, bringing SEO and AEO together as part of the same search visibility picture across the channels where decisions happen.
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