How I Read a Market Before I Make a Move
Michel Fortin
Author

Article Summary
Competitive intelligence isn’t a research task to file away. Done well, it’s one of the most direct inputs into positioning decisions. This post covers a framework for reading a market before making any strategic move: starting with buyer search behavior to map the conversational territory, identifying who actually earns relevant attention (not just industry competitors), scanning for content gaps and trust infrastructure, and checking which sources AI tools cite when buyers ask questions in your category.
Most growth leaders think of competitive analysis as a research task. Something you do at the start of a strategy project, hand off to a junior team member, or outsource to an agency that delivers a 40-page PDF you skim once and file away.
That’s not how I think about it.
Competitive intelligence, done well, is one of the most direct inputs into positioning decisions. It tells you what your market already believes, what buyers are actively looking for, and where your competitors are earning attention that you’re not. Those three things have a direct line to revenue.
What follows is the framework I use when I need to understand a competitive landscape before making positioning or content decisions. It starts with the search environment, because that’s where market conversations become visible at scale. But the output is not an SEO report. It’s a market map.
Start With What the Market Is Actually Saying
Before I look at competitors, I look at buyers. The search bar is one of the most honest data sources available to any marketer. When someone types a query into Google, they’re not performing for an audience. They’re asking a question they actually have.
At scale, search data tells you what problems buyers are trying to solve, what language they’re using to describe those problems, and how far along they are in the awareness journey. I use five areas within Google’s search interface to surface this: the search results themselves, autocomplete suggestions, “People also asked” questions, “People also search for” listings, and related searches at the bottom of the page.
Together, these give you a dimensional view of how your market thinks about a problem. Each reflects a different angle on the same underlying question: what are buyers trying to figure out, and how are they trying to figure it out?
The Autocomplete Technique
Here’s a specific technique I find valuable, and most people don’t use it this way.
Start typing a query and let Google surface its autocomplete suggestions. Take one of those suggestions, click it, and once the results load, place your cursor back in the search bar at the end of the query and press the spacebar. You’ll get a new set of suggestions layered on top of the first. Repeat the process. Each iteration reveals a different dimension of the same topic.
What you’re doing is mapping the full conversational territory around a topic, not just the top-level terms. You’re finding out what questions lead to other questions, which tells you how buyers are actually thinking through their problems.
This is the kind of intelligence that tools alone can’t replicate. Keyword planners and browser extensions can accelerate the data gathering, but the pattern recognition that turns raw queries into positioning insight requires a strategic lens.
Why Specificity Beats Volume
A generic keyword with high search volume looks attractive on paper. In practice, it’s usually a trap. The traffic is unqualified, the competition is fierce, and ranking for it rarely moves a business forward.
The strategically valuable terms are specific. In B2B, generic category terms attract researchers. Specific, intent-loaded phrases attract buyers. And the buyers who search with specificity are easier to convert, less price-sensitive, and more likely to be the right fit.
I’d rather a client generate 5% of 100 long-tail terms averaging 20 monthly searches each than generate 0.1% of a single term with 5,000 searches. The first produces 100 qualified visitors. The second produces five.
Specificity compounds.
Mapping Your True Competitors
Once you understand what your market is searching for, the next question is: who is winning that attention, and why?
The first thing to establish is what “competitor” actually means in this context. A competitor in your industry is not necessarily a competitor for the attention of your buyers. A large agency with a national brand may compete with you in the market but not rank for the same queries your ideal buyers are searching. A smaller niche player with strong content might be earning far more relevant organic attention than a better-known name.
True competitors, for this analysis, are the sites earning the most relevant organic traffic for the queries that matter to your buyers. Those are the competitors worth studying.
What the Scan Reveals
For each competitor I identify, I look at three dimensions.
First, content gaps. Which topics and keywords are competitors ranking for that my client isn’t? These represent untapped attention that competitors have already validated. If a competitor consistently earns traffic on a topic your site doesn’t cover, that’s a positioning gap as much as a content gap.
Second, trust infrastructure. Where are competitors earning credibility that my client hasn’t? Industry associations, authoritative directories, publications, and communities where competitors have established presence. This tells you where your category’s trust architecture lives.
Third, brand conversations. What comes up when you search a competitor’s name directly? What are buyers saying about them? Brand mentions, reviews, forum discussions, and media coverage are all part of the competitive picture that backlink and ranking data don’t capture.
What the Data Is Really Telling You
Here’s what most competitive analyses miss. The data isn’t fundamentally about search rankings. It’s about market perception.
When a competitor consistently ranks for a category of queries, it means the market has assessed that their content best answers buyer questions in that space. That’s a signal about authority and relevance, not just optimization.
When buyers repeatedly phrase questions a certain way, that’s a signal about how they understand their own problems. That has direct implications for messaging and positioning.
When you look at a competitive landscape through this lens, the questions change. Instead of “how do we rank for these keywords,” the question becomes “what does it take to own this territory in the minds of our buyers?” Instead of “how do we get more backlinks,” the question becomes “where is the trust infrastructure of this category, and are we part of it?”
Those are positioning questions. And they lead to positioning decisions about content strategy, messaging architecture, where to invest in authority, and which buyer segments to prioritize.
This is exactly the kind of diagnostic work I do in fractional CSO engagements, where reading the competitive landscape is the first step before any strategic recommendation.
Competitive Intelligence in the Age of AI Search
AI-powered search tools, including Perplexity, ChatGPT, and Google’s AI Overviews, are functioning as a new layer of competitive positioning. When a buyer asks an AI tool about a problem in your category, the sources the AI cites are the effective competitors for that buyer’s attention at that moment.
The criteria for appearing in AI-generated answers are roughly the same criteria that determine strong organic search performance: authoritative content, clear structure, specific and well-sourced claims, and demonstrated expertise. But the presentation layer is different. AI tools summarize and synthesize rather than rank. The content that gets cited tends to be content that’s easy to reference accurately.
Competitive intelligence now needs to include a new question: which sources are AI tools drawing on when buyers ask about our category? Running the same queries you’d use for traditional competitive research through AI tools gives you a fast read on which players have established enough authority to be recommended by AI systems. In some categories, the AI-era competitive set is quite different from the traditional organic search set. Knowing the difference is a strategic advantage.
Applying the Intelligence
Competitive intelligence is only useful if it changes something. The output of this process should give you a clear view of three things: where your buyers are in the awareness journey based on what they’re searching for, which competitors currently own the attention you want, and where the gaps represent untapped positioning opportunity.
From there, the decisions become relatively clear. Where do you need to build content to fill gaps your buyers are actively looking to fill? Where are competitors earning authority that you should be earning instead? What does your messaging need to say to differentiate your position from the competitors your buyers are most likely comparing you against?
These are not SEO questions. They’re market positioning questions. The search environment just happens to be one of the clearest places to find the answers.
Frequently Asked Questions
What is competitive intelligence and how is it different from a competitive analysis?
Most competitive analyses are research deliverables — a document produced at the start of a project and filed away. Competitive intelligence is an ongoing input into positioning decisions. It tells you what your market already believes, what buyers are actively searching for, and where competitors are earning attention you’re not. The output isn’t a report. It’s a market map that drives content, messaging, and positioning decisions.
Why start competitive research with buyer search behavior rather than competitor analysis?
The search bar is one of the most honest data sources available. When someone types a query, they’re expressing a real need, not performing for an audience. At scale, search data reveals what problems buyers are trying to solve, the language they use to describe those problems, and how far along they are in their awareness journey. Looking at buyers before looking at competitors means your intelligence is grounded in actual demand rather than industry assumptions.
What is the autocomplete technique for competitive research?
Type a query into Google and let autocomplete surface suggestions. Click one, then place the cursor back in the search bar and press the spacebar — you’ll get a new layer of suggestions on top of the first. Each iteration reveals a different dimension of the same topic. What you’re mapping is the full conversational territory around a subject: which questions lead to other questions, and how buyers are actually thinking through their problems.
Who are your “true” competitors for the purpose of this analysis?
True competitors are the sites earning the most relevant organic traffic for the queries your buyers actually search — not necessarily the firms you’d name as industry rivals. A large agency with a strong brand may compete with you in the market but not for your buyers’ search attention. A smaller niche player with deep content might be winning far more relevant visibility. The competitor worth studying is whoever earns the attention you want.
How does competitive intelligence work in the context of AI search?
AI tools like Perplexity, ChatGPT, and Google’s AI Overviews create a new competitive layer. When a buyer asks an AI about a problem in your category, the sources cited are the effective competitors for that buyer’s attention at that moment. Running your standard competitive queries through AI tools reveals which players have earned enough authority to be recommended by AI systems — and in some categories, that set looks quite different from the traditional organic search competitive landscape.
Michel Fortin
Michel Fortin is a revenue architect, strategic advisor, and fractional CGO/CMO/CRO/CSO who helps growth-stage companies, expert-led firms, and SaaS brands diagnose what's stalling their growth and build the systems to fix it. Over 30+ years in strategic marketing, he has generated over $1 billion in revenue across 200+ industries by combining deep positioning expertise with AI-powered marketing strategy. He's the author of "Power Positioning" and a recognized thought leader on organic visibility, revenue architecture, and authority-driven growth. Michel writes the Fortin File™ Newsletter, where he shares strategic insights on positioning, AI, and sustainable growth for leaders and consultants.

Most people use ‘branding’ and ‘brandifying’ as if they were the same word. They are not. Branding decorates what already exists. Brandifying names the thing into existence first, so it can be owned. I have been doing the second one for 35 years without a word for it. Here is the line, the move, and why expert-led firms that want to claim a category have to learn to brandify rather than brand.

Most “revenue architecture” sold today is plumbing, such as pipeline mechanics, attribution, dashboards. But the real architecture is upstream, where positioning lives.

A fractional CGO (Chief Growth Officer) owns the unified growth engine across marketing, sales, and retention. Here’s how the role differs from a CMO, CRO, or CSO.
