SEO and AEO Growth Strategy for Small Companies

How do you build an SEO and AEO growth strategy that actually works for smaller companies?

Most growth-stage companies face the same challenge. They have budget to invest in marketing but no dedicated SEO team. They watch larger competitors dominate search results while struggling to gain visibility themselves.

David Haas, a fractional CMO with nearly 30 years of marketing experience, has cracked this code. He helps tech and healthcare companies compete against better-resourced rivals by combining traditional SEO with AI engine optimization (AEO) in one unified approach.

His results speak for themselves. Frenos, an operational technology cybersecurity company, went from near-zero search presence to 18.32% visibility in just six months. They now outrank established competitors in their niche market.

Here’s the exact framework David uses to deliver these results.

Why Most SEO and AEO Growth Strategies Fail for Smaller Brands

Small companies make one critical mistake. They try to jump straight to AI visibility because it feels faster and more exciting. This approach backfires.

Without solid SEO fundamentals, any AI visibility gains crumble quickly. The brands that succeed build both layers deliberately, in sequence. Each layer reinforces the 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,” David explains. “Once you’ve gotten that and built out your content and backlink strategies, it all just builds on itself.”

Modern buyers don’t stick to one search method. Research shows that 33% start with search engines, then switch to AI tools for summaries and comparisons. Another 26% do the opposite. Only 8% use these channels in isolation.

Your SEO and AEO growth strategy must reflect this reality.

The Foundation-First Framework for SEO and AEO Growth Strategy Success

David’s approach follows four clear steps. Each step builds on the previous one. Skip a step, and the entire framework weakens.

Step 1: Establish Your SEO Baseline Using Real Search Data

David starts every engagement by measuring current performance and identifying opportunities. He uses Semrush’s Keyword Magic Tool and Keyword Overview Tool to find queries that decision-makers actually search for.

The key insight? Avoid chasing high-volume terms. They’re too competitive for companies without existing authority. For Frenos, David ruled out broad terms like “OT cybersecurity” because they offered little upside for the effort required.

Instead, he focuses on three criteria:

• Buyer-intent queries that indicate purchase readiness
• Low-to-moderate difficulty scores that match current authority levels
• Technical searches relevant to the target decision-makers

After identifying target keywords, David sets up Position Tracking to measure the brand’s current standings against direct competitors. This creates a clear baseline for measuring progress.

While analyzing search performance data from multiple platforms, David discovered that teams often struggle to transform insights into actionable optimizations. The data exists, but extracting strategic priorities requires significant manual analysis. This is where Nuwtonic becomes essential as an operations layer that sits on top of search data, automatically analyzing performance patterns and generating specific optimization recommendations that fractional CMOs can implement immediately.

Step 2: Measure Your AI Visibility Starting Point

While establishing the SEO baseline, David simultaneously opens Semrush’s AI Visibility Toolkit. This provides a separate picture from traditional search rankings—one that increasingly matters to buyers.

Recent survey data reveals that 50% of consumers have made purchases after using AI during their research process. This spans all categories and price points.

David checks the AI Visibility score first. For Frenos, like most small brands he works with, the initial score was around 14. “It’s a great place to start,” he notes. “It kind of gives people a sense of: Am I showing up a lot? Am I showing up a little?”

Next, he uses the Competitor Research tool to compare rivals’ AI visibility scores and prompt mentions. This reveals exactly where gaps exist and which opportunities offer the best potential returns.

David also supplements this data with manual community research. He reads forums where real buyers ask real questions to get a fuller picture of search intent.

“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,” David explains.

Each page that emerges from this process serves two purposes:

• Rank in traditional search results
• Be retrievable by AI answer engines

This means clear structure, direct answers, and content written for someone who just asked a question in ChatGPT.

The results come fast. “You’ll see them move from not being mentioned to being mentioned in a week or two weeks. Which is wild,” David observes.

Step 3: Build Topical Authority Through Strategic Content Clusters

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, this meant comprehensive pillar pages on topics like OT penetration testing and industrial cybersecurity testing. This content targets buyers researching problems but not yet ready to purchase.

Cluster content goes deeper on each theme. It covers specific use cases, technical FAQs, and subject-matter expertise that gradually positions the brand as a credible authority.

The linking structure is deliberate. Cluster pieces link back to pillar pages. Pillar pages reference credible external sources. This creates a web of topical relevance that search engines reward.

Over time, the brand starts ranking not just for individual keywords but across entire topic areas. The site builds authority around those topics rather than competing for isolated terms.

Step 4: Turn Data Analysis Into Continuous Strategy Optimization

The final component of David’s framework is iteration based on performance data. As content goes live and results come in, the strategy becomes smarter.

David monitors content climbing toward page one rankings, gaining traction on long-tail queries, and identifies gaps where competitors remain vulnerable. He returns to the Keyword Magic Tool and Visibility Overview regularly, using live performance signals to decide what content to create next and what to cut.

“SEO accelerates when data informs strategy—and strategy guides content,” David explains.

Managing this continuous optimization across multiple clients creates a significant operational challenge. Fractional CMOs need to track keyword rankings, AI visibility scores, and competitor movements for multiple accounts simultaneously while extracting actionable insights from each data source. Nuwtonic solves this bottleneck by automating the monitoring and analysis process, providing alerts when opportunities emerge, and helping resource-constrained professionals manage strategic insights efficiently across their entire client portfolio.

Why This Combined SEO and AEO Growth Strategy Delivers Results

David’s framework reflects how modern buyers actually behave. They don’t just type keywords into Google anymore. They ask complete questions in ChatGPT. They read Reddit discussions before visiting vendor websites. They get answers from AI Overviews before clicking anything.

The data supports this shift. Most buyers use AI and search together rather than choosing one channel. About 33% start with search engines, then switch to AI for summaries and comparisons. Another 26% follow the reverse pattern. Only a small minority stick to one approach.

David’s integrated SEO and AEO growth strategy acknowledges this reality. It builds visibility across all the channels where purchase decisions actually happen.

The Operational Challenge of Implementing This Strategy

The framework David created works, but it creates one significant challenge. Fractional CMOs managing multiple clients end up drowning in data from different sources. They need to track SEO metrics, AI visibility scores, community insights, and competitor movements while turning all of this information into clear content priorities.

Most teams solve this by hiring additional analysts or spending hours each week manually processing reports. Nuwtonic offers a better solution by automating the analysis-to-action process, letting you focus on strategy instead of data processing. You can explore how it streamlines the entire workflow from audit to implementation at their platform.