Competitive Analysis Graphs That Tell You Something

A competitive analysis graph is a visual representation of how competing businesses compare across a defined set of dimensions, typically plotted on a two-axis matrix, a radar chart, or a positioning map. Done well, it collapses weeks of market research into a single frame of reference that a leadership team can act on. Done badly, it produces a slide that looks rigorous but says nothing useful.

The difference between the two usually comes down to what you choose to measure, and whether those dimensions are genuinely strategic or just the ones that were easy to find data for.

Why Most Competitive Graphs Fail Before They’re Built

I’ve sat in more strategy sessions than I can count where someone has pulled up a competitive positioning map and the entire room has nodded along without questioning a single axis. The chart looked credible. It had competitor logos on it. It had a grid. And it told us almost nothing we didn’t already assume.

The problem usually starts at the design stage. The person building the graph picks axes that are easy to populate rather than axes that reflect genuine strategic tension. “Price” versus “Quality” is the classic example. Every market has a premium end and a budget end. Plotting your competitors on that matrix almost always produces a diagonal line from bottom-left to top-right, with everyone clustered in the middle. You’ve confirmed that expensive things tend to be higher quality. Congratulations.

What you actually want are axes that reveal a real choice your business faces, or a gap the market hasn’t filled. That requires knowing your market well enough to identify the dimensions that genuinely differentiate competitive positions, not just the ones that show up in a Google search for “competitive analysis framework.”

If you’re building out a broader market research programme alongside your competitive work, the Market Research and Competitive Intel hub covers the full landscape, from intelligence tools to positioning methodology.

Which Graph Types Work for Which Strategic Questions

There’s no single correct format for a competitive analysis graph. The right choice depends on what question you’re trying to answer. Using the wrong format for the question is one of the more common ways that competitive analysis produces beautiful outputs and useless insights.

The two-axis positioning map is the most widely used format. You pick two dimensions that represent genuine strategic trade-offs in your market, plot each competitor at the intersection of their position on both axes, and look for clusters and gaps. It works best when you’re trying to identify white space or understand where you sit relative to a small number of direct competitors. It breaks down when you have more than eight or ten competitors on the same map, because it becomes visually unreadable, and when the two axes don’t capture the real dynamics of your market.

The radar chart (sometimes called a spider chart) is better suited to multi-dimensional comparisons across a defined set of capabilities or attributes. If you’re comparing yourself against three or four competitors across five to seven dimensions simultaneously, a radar chart shows the shape of each competitor’s strengths and weaknesses in a way a two-axis map can’t. The limitation is that radar charts require you to score each competitor on each dimension, which introduces subjectivity unless you have clear, defensible criteria for each score. And once you push past seven dimensions, the chart becomes hard to read and the insights blur together.

The bar or column chart is underused in competitive analysis but often the clearest format when you’re comparing competitors on a single quantifiable dimension: share of voice, estimated organic traffic, review volume, pricing tiers, or similar. It doesn’t have the strategic elegance of a positioning map, but it’s honest. It shows one thing clearly rather than suggesting a strategic narrative that the data may not fully support.

The bubble chart adds a third variable to a two-axis map by varying the size of each competitor’s bubble. This is genuinely useful when the third variable is meaningful, for instance plotting competitors by price versus customer satisfaction, with bubble size representing market share. It adds a dimension of context without requiring a separate chart. The risk is overcomplication: if the bubble sizes are hard to compare visually, you lose the clarity that makes a positioning map useful in the first place.

How to Choose Axes That Actually Mean Something

Early in my career, I was helping put together a competitive review for a client in financial services. The brief was to show where they sat in the market. The team had built a positioning map with “innovation” on one axis and “customer focus” on the other. Every competitor was in the top-right quadrant. Our client was also in the top-right quadrant. The map was perfectly useless.

The axes had been chosen because they sounded good, not because they reflected a real strategic tension. No business in financial services is going to position itself as low-innovation and customer-hostile. Of course everyone clusters in the same corner.

Good axis selection starts with a different question: what are the genuine trade-offs in this market? What do customers actually have to choose between when they’re deciding between competitors? Those trade-offs are your axes.

In some markets, the real tension is between breadth and depth of service. In others, it’s between speed and accuracy, or between self-serve and high-touch, or between specialist expertise and generalist coverage. These are the axes that produce differentiated positioning maps, because not every competitor can sit in the same corner when the axes reflect real choices.

A practical test: if every competitor on your map ends up in the same quadrant, your axes are wrong. Either they’re not capturing a real trade-off, or they’re measuring something that all competitors in your category have optimised for equally.

The other common mistake is choosing axes based purely on what data is available. Traffic volume is easy to find. Ad spend estimates are available from tools. Review scores are public. But easy-to-find data doesn’t automatically translate into strategically relevant axes. Sometimes the most important dimension in a market is the hardest to measure, and the right response is to find a proxy for it rather than defaulting to whatever’s in the tool dashboard.

Building the Graph: Data Sources and Scoring

The quality of a competitive analysis graph is a direct function of the quality of the underlying data. This sounds obvious, but it’s regularly ignored. Teams spend hours perfecting the visual presentation of a graph built on estimates, assumptions, and data that’s six months out of date.

For quantitative dimensions, the sources you use matter. Organic traffic estimates from tools like Semrush or Ahrefs are useful directional signals but are not precise measurements. Similarweb’s traffic data is a modelled approximation. Ad spend estimates from intelligence platforms are educated guesses based on observed ad activity. None of this is a reason not to use these tools, but it is a reason to treat the numbers as ranges rather than precise figures, and to be honest about that when presenting the graph to stakeholders.

For qualitative dimensions, you need a scoring methodology that is consistent and defensible. If you’re scoring competitors on “customer experience quality,” you need to define what that means in measurable terms before you assign scores. Review sentiment analysis, mystery shopping, NPS data where available, and customer interview findings are all legitimate inputs. Gut feel from the marketing team is not, at least not without triangulation against something more objective.

When I was running agencies and we were pitching for new business, we’d sometimes build competitive maps for prospective clients as part of the pitch. The ones that landed were always the ones where we could explain exactly how each position had been determined. Not just “we scored your competitors on these dimensions,” but “here’s the specific data that informed each score, here’s where we had to make judgement calls, and consider this we’d want to validate further.” That kind of transparency builds more credibility than a polished chart that doesn’t show its working.

Behavioural data can add a useful layer to competitive analysis, particularly when you’re assessing user experience dimensions. Tools that track on-site behaviour, like Hotjar’s click tracking, can give you a sense of how competitors’ sites are structured to guide user behaviour, even if you can’t access their internal analytics directly.

Reading the Graph: What to Look for Beyond the Obvious

Once you have a well-constructed competitive analysis graph, the instinct is to look at where you sit relative to competitors. That’s a reasonable starting point, but it’s not where the most useful insight usually lives.

White space is the primary strategic signal. If your positioning map has a quadrant with no competitors in it, that’s either an opportunity or a warning sign. It’s an opportunity if the empty quadrant represents a customer need that isn’t being served. It’s a warning sign if the empty quadrant is empty because customers don’t actually want what that position offers. The graph can show you the gap; it can’t tell you whether the gap is worth filling. That requires customer research.

Clustering tells you where competition is most intense. If five of your eight competitors are clustered in the same quadrant, that’s where the market is most crowded. Being in that cluster means competing on marginal differentiation. Being outside it means you’re either genuinely differentiated or you’ve drifted to a position where customers aren’t looking.

Movement over time is more valuable than a single snapshot. A competitive analysis graph built once and never revisited is a historical document, not a strategic tool. The most useful version of this analysis is one you run on a regular cadence, so you can see how competitive positions are shifting. A competitor moving from the mid-market quadrant into the premium quadrant is a strategic signal worth tracking. A new entrant appearing in white space you’d identified is a signal worth acting on.

I’ve seen brands lose meaningful market share because their competitive positioning maps were built annually and treated as definitive. By the time the next review came around, a competitor had already moved into the gap they’d identified and were planning to fill. The graph was accurate when it was built. It just wasn’t being watched.

Presenting Competitive Graphs to Stakeholders Without Losing the Nuance

A competitive analysis graph is a communication tool as much as an analytical one. How you present it shapes how it’s used, and how it’s used determines whether the analysis drives decisions or just decorates a strategy deck.

The most common presentation mistake is presenting the graph as a conclusion rather than a starting point. “Here’s where we sit in the market” is a statement. “Here’s where we sit, consider this that means for our positioning options, and here are the assumptions we’d need to validate before committing to one of them” is a strategic conversation. The latter is harder to present, but it’s the one that actually moves things forward.

Be explicit about what the graph can and can’t tell you. A positioning map built on estimated traffic data and publicly available pricing tells you something about the visible competitive landscape. It doesn’t tell you about competitors’ internal strategic priorities, their unit economics, or what moves they’re planning to make. Acknowledging those limits doesn’t undermine the analysis. It makes you more credible as the person presenting it.

When I was judging the Effie Awards, one of the things that separated strong entries from weak ones was the quality of the strategic framing. The teams that could show a clear line from market analysis to strategic insight to creative decision were consistently more compelling than the ones that had done a lot of research and produced a lot of slides. Competitive graphs are the same. The graph is not the insight. The insight is what you do with it.

For a broader view of how competitive analysis fits into a full market intelligence programme, the Market Research and Competitive Intel hub covers the methodologies, tools, and frameworks worth building into your process.

When Competitive Graphs Are Not the Right Tool

There are situations where a competitive analysis graph is the wrong format entirely, and it’s worth being clear about them rather than defaulting to a positioning map because it’s the expected deliverable.

If your market has fewer than three meaningful competitors, a positioning map doesn’t have enough data points to be informative. You’re better served by a detailed qualitative comparison of specific capabilities, customer perceptions, and strategic priorities. A graph with two competitors on it is not an analysis; it’s a diagram.

If your market is changing fast enough that any snapshot is outdated before it’s presented, the effort is better spent on a monitoring system that tracks competitive signals in near-real-time rather than a static graph built on a quarterly cycle. The graph format assumes a degree of stability in competitive positions that fast-moving markets don’t always provide.

And if the strategic question you’re trying to answer is about customer behaviour rather than competitor positioning, customer research is the right tool, not competitive analysis. A positioning map tells you how competitors are positioned. It doesn’t tell you how customers actually perceive those positions, which is a different and often more important question.

There’s a tendency in marketing to reach for the familiar framework rather than the right one. Competitive analysis graphs are useful, but they’re not universally applicable. Knowing when not to build one is as important as knowing how to build one well.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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