Keyword Clustering Template and Page Plan
Clusters sized on real demand rather than the sum of the rows, then turned into a page count, a page type and a build order.
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Cluster Rationale · Marrowfield Payroll · cluster 7 of 214
Running payroll for the first time
| Keywords in cluster | 27 |
|---|---|
| Sum of the rows | 29,400 a month |
| Close variant groups | 6 |
| Actual demand | 5,680 a month |
Where the other 23,720 went
| Group | Keywords | Each reports | Counts as |
|---|---|---|---|
| VG-01 | 14 | 2,400 | 2,400 |
| VG-02 | 4 | 880 | 880 |
| VG-03 | 3 | 1,000 | 1,000 |
| VG-04 | 3 | 720 | 720 |
| VG-05 | 2 | 480 | 480 |
| VG-06 | 1 | 200 | 200 |
Why
Google defines average monthly searches as the figure for a keyword and its close variants. Fourteen phrasings of the same question all report 2,400 because they are all reporting the same searches. Adding them gives 33,600 of demand that does not exist.
The tell is on the sheet already: identical figures on rows that read differently are one group, not fourteen data points.
What it changes
| Plan sized on the rows | 1,120,000 a month |
|---|---|
| Plan sized on the groups | 386,000 a month |
Every keyword plan anyone has been handed before was sized on the first number. It is 2.9 times the second one.
Every keyword clustering template does the same thing: groups an export by string similarity or result overlap, sums the volume in each group, sorts descending, and calls the top fifty a content plan. Two of those four steps produce a number that is wrong, and the plan is a list of clusters rather than a list of pages, which is not the thing anybody asked for. A cluster does not say how many pages it is worth, what type each one has to be, or whether you already rank for it.
Google defines average monthly searches as the figure for a keyword and its close variants, averaged over twelve months. So rows overlap, summing a cluster counts the same searches several times, and a seasonal term is reported as a number it never has. The Competition column in the same export counts advertisers relative to all keywords across Google, which is auction density and not organic difficulty. It never enters this plan. What does is organic impression share, the column that reports whether Google already shows a page of yours.
The worked example cuts 18,400 keyword ideas to 6,120, forms 214 clusters, and finds the real demand is 386,000 a month against the 1,120,000 the export claims. Every cluster gets checked against Google's own concept grouping. Pair it with the full Search Console export past the thousand row cap and the content audit that decides the pages you already have. Once two clusters end up pointing at the same query, the cannibalization review is what picks the survivor and maps the redirect.
What you get
Keyword Clusters
One row per kept keyword with its cluster, its intent, its close variant group, the peak month if it has one, and whether Google's grouping agreed. The variant group column is what makes the sizing checkable rather than asserted, because anybody can see which rows collapsed into one another and why.
Cluster to Page Map
The output, and the reason this is a plan rather than a cluster map. Every cluster carries a page count, a page type, the URL of any page already earning impressions for it, and one of five verdicts. Both directions are normal: forty-seven clusters fold into other pages and nine split into two.
The volume correction
Cluster volume computed as the sum of the maxima of its close variant groups, not the sum of its rows, with both figures kept side by side. On the worked example that is 386,000 a month against 1,120,000. The gap is the first thing to show anybody who has been handed a keyword plan before.
Google's own concept grouping as a second opinion
Google's keyword ideas service can return a concept group and concept name for every idea. Run against your clusters it disagreed 31 times out of 214, and the rule that fell out is durable: on intent disagreements Google was right, on wording disagreements it was not.
Coverage Gap
The clusters nobody owns, already in build order, each with what page one currently serves and who has to build it. Eight rows came off this sheet before publication because organic impression share found a listing from the site on a URL nobody connected to the topic.
Page Type Guidance and Plan Sequencing
Seven page types, the evidence each call rests on, and the two type errors that cost the most. Then the build order, which puts type corrections on pages that already rank above every new page, because distribution that has already been paid for is the cheapest thing in a content plan.
Discarded Keywords
Two thirds of a large export with the rule that cut each part and the reason. Longer than the plan, which is the normal outcome. It also records what is explicitly not a discard rule: high competition and a big incumbent on page one are sequencing inputs, not cuts.
How it works
- 1
Send the export
A keyword export from any tool, Search Console performance by query and by page, and the pages that already exist. An export somebody else pulled is the normal case.
- 2
River sizes it first
Close variant groups collapse, seasonal terms get their peak month, and the Competition column is set aside. You see the real demand figure before any clustering happens.
- 3
Clusters get a page count
Intent decides the type, Google's concept grouping checks the cluster, and existing coverage is measured rather than guessed. Then every cluster gets a page count and one of five verdicts.
- 4
The plan comes out ordered
Five bands, ship-by dates on anything seasonal, owners and reviewers on every row, and named dependencies where one page has to exist before another can link to it.
Frequently asked questions
Why is your volume figure lower than my export's?
Because your export counts some searches more than once. Google reports each keyword's average alongside its close variants, so a plural, a reordering and a synonymous phrasing all carry the same number. Collapsing those groups to their maximum cut the worked example from 1,120,000 a month to 386,000.
What does Edit with AI do that the download does not?
It installs this pack as a private Space and River works your own export instead of the example. It applies the discard rules, groups the variants, clusters by intent, measures your coverage against Search Console, then fills the page map and sequences it. You keep the reasoning on every row.
Should I not just target the highest volume keywords?
The highest volume rows in an export are usually category terms your product page should own. On the worked example that is a 40,500 a month query, recorded as a Drop with a note to whoever owns the product page. A content page winning it would replace a page that sells with one that does not.
How do you know whether a page already covers a cluster?
It gets measured, not string-matched against a sitemap. Search Console performance by query names the page and what it earns, and Keyword Planner's organic impression share column reports whether a listing from your site shows at all. Those two disagreed on eight clusters here.
Does it work with a Semrush or Ahrefs export instead of Keyword Planner?
Yes. All of them produce the same three things: a keyword list, a volume estimate and a difficulty or competition score. The method reads the list and treats the score as an estimate from a named tool. Where a column is missing, the sheet says which decision is running without it.
How many pages should a 20,000 keyword export produce?
Far fewer than the cluster count, and that is the point. The worked example ran 18,400 ideas down to 214 clusters and then to 164 pages, of which 88 already existed. Forty-seven clusters became sections rather than pages, which is what stops a plan being two hundred thin articles.
What happens to seasonal keywords?
They get a ship-by date instead of a priority. A twelve month average is the one figure a seasonal term never has: one cluster here averages 1,300 and does 9,400 in March. It ships in January, because a page published during its own peak has not been crawled or linked yet.
Find out how much of your keyword volume is counted twice
Send the export. River sizes it properly, clusters by intent, measures what you already cover, and hands back the pages in the order to build them.
Edit with AI