Problem Map
How Visibility Flux scores every page against the click-through rate its ranking position should earn, and what each view of the map means.
Problem Map
The Problem Map answers one question: which page should I open first?
Most SEO tools grade the page you are already editing. The Problem Map instead scores your entire site from real Search Console data and sorts it by how many clicks each page is leaving on the table.
How lost clicks are calculated
A page at position 1 earns a very different click-through rate than a page at position 9. Judging every page against one flat CTR benchmark misreads both: a position-1 page at 5% CTR looks fine but is badly underperforming, while a position-9 page at 3% is doing well.
Visibility Flux compares each page's actual CTR against the CTR expected for its actual position, using a curve based on aggregate published organic CTR studies:
| Position | Expected CTR |
|---|---|
| 1 | 28% |
| 2 | 15% |
| 3 | 11% |
| 4 | 8% |
| 5 | 6% |
| 6 | 5% |
| 7 | 4% |
| 8 | 3% |
| 9 | 3% |
| 10 | 2% |
| 11 | 1.5% |
| 15 | 0.9% |
| 20 | 0.5% |
| 20+ | keeps decaying, with a floor |
Positions in between are interpolated, and positions past 20 keep decaying rather than flattening out.
That tail matters more than it looks. When everything past position 10 was credited the same 1% expected CTR, a page ranked 88th scored more lost clicks than one ranked 11th — purely because deep pages accumulate impressions. Since the whole map sorts by lost clicks, effectively unreachable pages pushed the genuinely fixable ones off the top of the list.
The estimate is then:
lost clicks = (expected CTR − actual CTR) × impressions
Negative results are floored at zero — a page beating its expected CTR is not "losing" anything.
This is an estimate for prioritisation, not a promise. Its job is to rank your pages against each other, and it does that reliably. Treat the absolute number as directional.
The header metrics
Across the top of the Problem Map:
- Impressions and Clicks — totals from your import
- Site CTR — overall click-through rate
- Avg Position — average ranking position across all pages
- Lost/mo (est) — the sum of estimated lost clicks across every page
The views
Low CTR
Pages Google shows often and few people click, sorted by the clicks that gap is costing you. It merges two lists that used to be separate — very high impressions with almost no clicks, and page-one rankings under 1% CTR — because they are the same complaint split by an arbitrary cutoff, and one worklist is easier to work through than two overlapping ones. Duplicates are removed.
This is where to start. It is nearly always a title and meta description problem rather than a content problem, the fix is fast, and the impressions are already there.
Almost there
Two lists that share a fix: a small push.
- Page 2 pages — position 11 to 20 with real impressions. They have already proven they are relevant enough to rank; page two just gets almost no traffic
- Quick win queries — searches at position 4 to 20 with meaningful volume, where the CTR curve steepens sharply just above them. Adding a section that answers the query directly often moves them
Each paginates independently.
Cannibalisation
Groups of your own pages competing for the same searches, with a KEEP (winner) and MERGE + 301 recommendation per group.
Two detection methods:
- Exact — used when your Queries export includes the Page dimension. Visibility Flux groups pages that literally rank for the same query. Ground truth, no guessing. A group forms when pages share two or more overlapping queries
- Heuristic — the fallback when page mapping is absent. Compares URL slug keywords, language-agnostically, and adapts to scripts that do not space their words
The exact method is much better. Re-export your Queries report with Page added as a second dimension to enable it.
Losing ground
Pages sliding down between your two most recent imports — caught before they become a crisis. Needs two imports to exist. See Measuring results.
Indexing (Pro)
Google's own verdict on each page, joined to your performance data, including pages Google canonicalised to a different URL. See Indexing.
Results
Every page you have fixed, before and after, plus site totals import by import. This is the tab that tells you whether any of the work paid off — see Measuring results.
Content calendar
The gaps worth writing next.
Working through the list
Each row has a Fix → link that opens that page in the AI Editor with its Search Console metrics already loaded.
Once you have applied a change, that row shows Fixed with the date instead, so the list visibly shrinks as you work — and the page's before-numbers are stored for the comparison in Results.
Every list here paginates at ten rows.
A sensible order of attack:
- Low CTR — biggest volume, cheapest fix, already sorted by what it is costing you
- Almost there → quick win queries — small content additions, high upside
- Cannibalisation — structural, do it once and it stays fixed
- Losing ground — cheaper to rescue a page still falling than one already at the bottom
- Almost there → page 2 pages — the most work per page, do these when the fast wins are done
Then wait for the next import and open Results.
Caching
The analysis is cached so large sites don't recompute on every page load. Re-importing your CSVs clears every Visibility Flux cache automatically, so the map always reflects your latest export.