Impression Share by Funnel Position: A Better SEO Funnel Reporting Framework

For years, the first page of many SEO reports included sessions from organic search — a nice line going up and to the right. That line is going down in a lot of accounts now, and leadership wants to know what SEO is actually doing for the business. On top of that, the impression numbers themselves have been wrong for nearly a year, which makes a mix-based reporting framing more important, not less. Noah Learner’s approach to bucketing Google Search Console impressions by funnel intent is a much better way of thinking about this, and the way I report it back to clients is a translation of his methodology into a leadership-friendly framing. I started building on it because the old way of reporting wasn’t telling the right story, and as I’ve written before about reporting honesty, if the numbers don’t help anyone make a decision, they’re not really a report. Let’s walk through the framework and how to apply it to your own reporting.

SEO funnel reporting is a way of looking at your Google Search Console impression data through the lens of buyer intent, (top of funnel, middle, and bottom) instead of as a single traffic line. Instead of reporting “we got 50,000 sessions last month,” you report “your search visibility is roughly 70% top of funnel, 10% middle, 20% bottom — here’s where you’re showing up at the moments that close deals, and here’s where you’re invisible.” It’s a small shift in framing that lands very differently with leadership and account teams.

In many B2B accounts, I’ll typically see around 70% top-of-funnel impressions, 10% middle, 20% bottom. Your numbers might look different, especially if you’ve invested heavily in product-led content or bottom-of-funnel SEO for a while. But for most accounts I look at, the shape is recognisable: a big slice of awareness-stage visibility and a much smaller slice of anything closer to a buying decision.

That mix isn’t a reflection of how buyers behave. It’s a reflection of what SEO teams have been rewarded for producing. We’ve been incentivised to chase traffic as the main metric for so long that of course top of funnel is where the volume sits because that’s where the biggest numbers are! And then if you think about lower-funnel queries, it’s fewer people, but they’re really engaged people. However, that wasn’t what we got measured on. We partly did this to ourselves, and now we have to dig ourselves out of the hole.

A quick aside on the funnel framing itself: real customer journeys aren’t strictly linear. People loop back, jump stages, get pulled in by something that catches their eye on a podcast and skip three steps. The funnel is a simplification. But if you’ve never broken your impressions out by stage at all, this is a great starting point for finding the gaps in how you’re showing up, and that’s the value here. You’re not modelling a perfect customer journey. You’re diagnosing where your search surface is heaviest and where it’s thin.

Before you can report on the mix, you have to decide what counts as top, middle, and bottom of funnel for your business. That sounds simpler than it is. Here’s what I’ve found works, and this is based on Noah’s starting points.

Top-of-funnel queries are the educational ones: “what is X,” “how to X,” broad topic terms, problem-statement language where the searcher hasn’t decided what kind of solution they need. Middle of funnel is where comparison and evaluation language shows up: “X vs Y,” category-defining terms, queries that include words like “compare,” “alternative,” “best.” Bottom of funnel is action and intent: now we bring in branded queries, “buy X,” “X pricing,” “X demo,” geographic modifiers when location matters, anything that screams “I’m ready to give you my money”.

The lines are fuzzy, and your buckets might look different for your industry. A “comparison” query in B2B SaaS is middle funnel. The same comparison query for a local service business might effectively be bottom funnel because the comparison is the buying decision. If you aren’t sure how to bucket your queries, use this to start, but start building a taxonomy that fits your business best.

Implementation-wise, a spreadsheet of your most important keywords with a funnel stage column is a fine start. Export your queries from Search Console, add a column called “funnel stage,” and start tagging. If you have a lot of keywords (and you probably do) and you’ve never done this before, ask an LLM to help you out. Develop some rule-based pattern matching (e.g. any keyword with “vs” is middle), feed that to the LLM along with your CSV of keywords, and that will get you most of the way there. Then go back and hand-correct the misses.

Once you’ve got your impressions bucketed, now you can compare the mix against what you know about your actual sales funnel. The mismatch is the diagnostic.

Keep in mind that your impression mix isn’t your audience. Impressions are an imprecise measure of how visible you are across the different intents Google has decided your content speaks to. They’re a measure of search-surface composition, not buyer composition. Most of those top-of-funnel impressions are people loosely matched to broad terms; many of them were never going to be in your funnel at all. Strictly speaking, you’re not comparing audience to audience.

But the diagnostic still works, and it works because if (for example) your impression mix is 70% top of funnel, you’re showing up almost exclusively at awareness-stage moments and barely showing up when buyers are actively comparing or deciding. That’s the problem that’s worth solving. The outcome isn’t “your audience is wrong”, instead it’s “your search surface is wrong”.

The counterargument is that top-of-funnel and bottom-of-funnel queries aren’t comparable on volume. A query like “how does a heat pump work” might get 100,000 impressions a month because it’s a generic query, and could be asked by anyone. A query like “heat pump installer Victoria” might get 50 impressions because it’s a narrow buying-stage query with low search volume. Of course your impression mix skews toward the top — that’s just keyword volume math.

I’d argue that the volume difference isn’t the problem. Instead, the problem is when your share within each stage is also lopsided. If the bottom-of-funnel queries that exist for your business are 50 impressions a month and you’re capturing 5 of them, you have a visibility problem at the moments that actually close deals. The 70/10/20 isn’t “too much top-of-funnel volume.” It’s “you’re invisible when it counts.”

What I often see is a sad little slice of middle funnel, and that’s because middle funnel can feel difficult to speak to, but that’s exactly why there’s opportunity there. April Dunford writes in Sales Pitch that the most difficult competitor for any considered purchase is the prospect doing nothing. Those companies stick with the status quo because the alternative feels too hard to evaluate. Middle funnel is where you teach buyers how to evaluate the choice. If you’re invisible there, you’re losing to inertia, not to your direct competitors.

Here is a classic example, from one of our client accounts. We use a 100% area chart to illustrate how top-heavy the impressions are, without getting distracted by looking at the actual volumes.

Once you’ve done the bucketing and run the diagnostic, your report can lead with funnel position, not with traffic totals. Here’s the shape I’ve found works.

Page one of the report is your impression share by funnel position, side by side with a target state. The target state is based on your actual sales funnel math, which answers the question “what would the mix look like if your search visibility roughly mirrored where buyers spend the most consequential time?”. These aren’t fixed, precise numbers; it’s a directional comparison. You’re answering “are we showing up at the right moments?” rather than “did we hit the impression goal?”

Page two is movement over time. Are we shifting impression share toward middle and bottom, or holding steady? Is the work we’ve been doing this quarter actually changing where we show up? This is the page that makes the previous quarter’s investment legible. If you’ve been writing comparison content for six months, this is where you see whether it’s accumulating into measurable middle-funnel surface.

The third page you may not want to include to leadership, depending on how engaged they are with your work (or how engaged you want them to be!). This page is the content map, where you line up which pieces of content are doing which funnel jobs. This is where the work starts getting actionable, because you can see which bottom-funnel pages are doing the heavy lifting and which middle-funnel pages still need to exist.

That being said, I don’t recommend dropping traffic entirely from your reports! It’s still useful as a secondary graph, especially for explaining month-over-month variance. Just move it off the front page so it’s not the headline metric anymore.

A quick language tip — when you talk to leadership about this, “awareness” and “consideration” land better than “top of funnel” and “middle of funnel.” Use the language your audience uses, and in your case, your audience is your leadership or your clients. The exact terminology doesn’t matter. Instead, they care about whether the marketing investment is showing up in the moments that matter for revenue.

You might have noticed I keep saying “the mix” rather than “the impressions” and that’s because of what’s happened with the past year of Google Search Console data.

Two things have happened to GSC impression data since mid-2025. First, Google had an internal logging bug that over-reported impressions from May 2025 through April 2026 — about 11 months of inflated counts before Google acknowledged the bug publicly. Per Google’s disclosure, only impressions were affected, not clicks or position. But CTR is calculated from impressions, so any CTR figure during that window is also wrong. Second, a chunk of the “rising impressions” everyone attributed to AI Overviews and zero-click expansion turned out to be bot inflation from rank trackers and SERP scrapers using the &num=100 URL parameter. Google killed that parameter in September 2025, and impressions dropped sharply in many accounts immediately after, showing how much of data was non-human. Most accounts we worked with saw a drop of around 25%. We always knew that there was rank tracker traffic in GSC, we just didn’t realize the sheer scale of it.

These kind of issues highlight why the mix-based framing is more durable. Even if absolute impression counts are inflated, the relative shape across funnel positions is more stable — unless scrapers tend to hit one funnel stage over another (more on that below), the proportion of TOFU vs MOFU vs BOFU impressions will show differences in how Google surfaces your content. Google Search Console data is never 100% accurate, and this is a more honest way of presenting imprecise data.

Something else to consider is that scrapers probably didn’t hit every query type evenly. Broad TOFU queries see more rank-tracker activity than narrow branded BOFU queries, in my experience. So your 70/10/20 might be slightly inflated toward TOFU because of who was scraping what. I’d recommend noting this in your reports during this period by annotating any unusual spikes and displaying rolling averages instead of daily totals. If you want to dig deeper into how GSC reports impressions in different views, the difference between site impression and URL impression is worth understanding before you build dashboards on either.

The data will always be noisy, but this mix is still a stable signal, and it has the advantage of being directly connected to the story leadership needs to hear.

SEO reporting has needed a better story for a long time. Zero-click search and the GSC reliability mess forced the issue, but this is the reporting we should have been doing all along. The mix tells leadership where the SEO investment is actually showing up; the change in mix over time tells them whether the work is moving the right way; and the content map tells the strategy team where to invest next quarter.

To start, pick a relatively short time frame (a month, a quarter), and do the bucketing exercise. See what the mix looks like. Compare it to what you know about your sales process. Build the three-page report and walk your team members through it, before you show it to leadership. If it lands well, show it to leadership, then replicate the framework across a longer time frame. If you’re already thinking in terms of quality traffic metrics rather than raw counts, this is the natural next move.