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Search term clusters for content priorities

Build a ranked SEO content backlog from keyword exports, page inventories and sales questions. For content leads and SEO managers.

5 min read

These prompts turn three messy inputs into a content backlog your team can assign: a keyword export, a site page inventory and questions collected by sales. They are for content leads and SEO managers deciding which pages to publish, improve, merge or leave alone.

Use the prompts in order. The first four create the evidence. The final prompt makes the publishing list. Do not start with the backlog, because a neat ranking built on duplicate keywords and unclear page ownership will send writers towards the wrong work.

Prepare the three source documents

Create a working folder with these documents before you paste anything:

  • Keyword export CSV: include the keyword, market, language, search volume and difficulty fields where available. Keep ranking URL and current rank if your export has them.
  • Site page inventory: export one row per indexable or live page. Include URL, title, page type, primary topic, organic sessions, conversions and last updated date where you hold them.
  • Sales question log: collect actual questions from call notes, demo notes, CRM fields or support handovers. Keep the original wording and identify the customer segment and deal stage.

Remove personal names, email addresses, phone numbers and deal-specific details from the sales log. The aim is to capture recurring customer language, not to copy a sales record into a planning document.

Key point

Start with the searcher task

Group terms because one page can answer the same job, not because the phrases contain the same noun.

If your files are too large to review at once, split them by country and language first. Keep the column names consistent across each part. File upload and input handling can vary by the model you are using, so check the xAI documentation overview if you need the current guidance.

Run the prompts in sequence

  1. Run Keyword export cleanup on the unedited export. Save its cleaned table as keyword-cleaned.
  2. Paste that output into Intent cluster map. Save the result as intent-clusters.
  3. Run Page overlap review with intent-clusters and the page inventory. Save it as page-overlap.
  4. Run Sales question mapping with the sales log and intent-clusters. Save it as sales-mapping.
  5. Paste the three outputs into Prioritised content backlog. Save the table as content-backlog.

Do not silently change labels between steps. For example, if the cluster map calls a group email marketing audit template, use that exact cluster ID in the overlap review and sales mapping. Stable IDs make it possible to trace a backlog item back to the keyword terms and customer questions that support it.

Note

Keep markets separate

A phrase can indicate a different need in another country or language. A shared English keyword is not enough reason to combine demand or assign one global page.

Choose the right prompt for the decision

If you need to decide Use this prompt What you should keep
Whether the export can be trusted Keyword export cleanup Duplicate and data-issue lists
Which terms belong on one page Intent cluster map Cluster table and unresolved terms
Whether a page already covers the need Page overlap review Canonical target and action
Whether sales language changes the plan Sales question mapping New cluster candidates and page additions
What the team should work on next Prioritised content backlog Ranked table with owner and dependency

A cluster is not automatically a new article. A high-volume informational group may belong in an existing guide. A commercial investigation group may need a comparison page. A repeated sales question may be better placed in a product page FAQ, or may remain sales enablement only if it has no plausible search intent.

Check the output before assigning work

Checking matters most at the boundaries. Look at the largest cluster, the clusters with the highest stated demand, and every recommendation to merge or redirect pages. Those are the decisions that can create the most wasted work.

Check

Test one page against one task

Read the primary keyword, supporting terms and proposed page type. If one page cannot satisfy them without becoming two different documents, split the cluster.

Use this review table with your SEO manager and content lead:

Check Warning sign What to do
Intent A guide and a pricing query sit in one cluster Split the cluster by searcher task
Market Volumes from different countries are added together Separate the rows and select a market owner
Existing coverage A new page is proposed beside a page with the same task Re-run the overlap review with both URLs
Sales evidence One call question is treated as a major demand signal Mark it as unvalidated and check frequency
Ownership The backlog says only content Assign a named function and a dependency

Read the evidence column in the final backlog. It should point to a supplied keyword cluster, page finding or sales question. If a recommendation has no evidence, it is an assumption. Move it to validation rather than publishing it as planned work.

Watch out

Do not treat page titles as proof of coverage

A page called “Email marketing guide” may not answer a query about audit templates, agency comparisons or pricing. Check the page task and content before you reject a new opportunity.

Turn the backlog into briefs

Take the first three validated rows only. For each, create a brief that records the primary keyword, audience, searcher task, page type, target URL decision, sections to include, internal pages to link, subject matter expert and approval owner. Keep the backlog row linked in the brief so the writer can see why the work exists.

Do not give writers a cluster with several unresolved intents. Resolve that decision first. A writer can draft a guide or a comparison page. They cannot reliably infer which document you intended from a mixed keyword list.

When the result does not work

If clusters are too broad, split the keyword export by modifier, audience, market or task and run the cluster prompt again. If every item becomes a new page, the page inventory is probably too thin. Add page summaries and rerun the overlap review. If the final ranking feels arbitrary, check whether metrics, ownership or sales-question frequency were missing. Keep those rows marked unknown and ask for the specific missing evidence rather than forcing a score.

Stop

Do not publish from an unresolved cluster

Resolve the searcher task, target page and owner before a brief reaches a writer.

Copy-ready prompts

5 prompts. Open one to read it, or take the whole pack.

1Keyword export cleanupUse this first when the keyword export contains duplicates, mixed countries, unclear metrics or several source tabs.
You are preparing a keyword export for search-intent clustering. Review [paste or upload keyword export CSV]. The expected fields are: keyword, country, language, monthly search volume, keyword difficulty, CPC, current rank, URL, and source. Fields may be missing.

Create a cleaned keyword table in Markdown with these columns: normalised keyword, original keyword variants, country, language, monthly search volume, keyword difficulty, CPC, current rank, ranking URL, duplicate status, and data issue.

Apply these rules:
1. Keep the original keyword wording in the original keyword variants field.
2. Remove only exact duplicates where country and language also match. Combine their metrics only when the values are identical. Otherwise flag the conflict.
3. Do not combine singular and plural terms, spelling variants, or terms with different modifiers unless they clearly express the same search need. Mark borderline cases as "review".
4. Preserve rows with missing metrics. State "not supplied" rather than estimating a value.
5. Identify malformed rows, mixed countries, mixed languages, zero-volume terms, and keyword strings that appear to be navigational queries.

After the table, provide: (a) a list of excluded exact duplicates, (b) a list of rows needing human review, and (c) a short data-quality summary. Do not create clusters yet. Do not invent metrics or infer country, language, ranking URL, or search volume from the keyword text.
2Intent cluster mapUse this after cleaning the keyword export, when you need groups that reflect one page's likely search job rather than loose topic labels.
Create search-intent clusters from [paste cleaned keyword table]. The table fields are: normalised keyword, original keyword variants, country, language, monthly search volume, keyword difficulty, CPC, current rank, ranking URL, duplicate status, and data issue.

Group keywords only when one page could credibly satisfy the same primary search need. Use the query wording, modifiers, implied task, audience and funnel stage. Do not group terms solely because they share a word.

Return a Markdown table with one row per cluster and these columns: cluster ID, cluster name, primary keyword, supporting keywords, intent, searcher task, funnel stage, suggested page type, total monthly search volume, difficulty range, country and language, existing ranking URL, and ambiguity note.

Use only these intent labels: informational, commercial investigation, transactional, navigational, or mixed. Use only these page types: guide, service page, product page, category page, comparison page, template, checklist, glossary page, case study, FAQ section, or no new page recommended.

Choose one primary keyword per cluster. Sum volume only for keywords from the same country and language. If a cluster mixes markets, split it. If the correct grouping or page type is uncertain, create a separate cluster and explain the uncertainty in the ambiguity note. Put terms that cannot be safely clustered in a final "unresolved terms" table. Do not invent SERP features, competitor behaviour, conversion rates or missing metrics.
3Page overlap reviewUse this when you need to decide whether a cluster needs a new page, a page update or a consolidation.
Review possible content overlap between [paste intent cluster map] and [paste site page inventory]. The cluster map fields are: cluster ID, cluster name, primary keyword, supporting keywords, intent, searcher task, funnel stage, suggested page type, total monthly search volume, difficulty range, country and language, existing ranking URL, and ambiguity note. The site page inventory fields are: URL, page title, page type, primary topic, target keyword, organic sessions, conversions, last updated date, and status.

Return a Markdown table with these columns: cluster ID, cluster name, relevant existing URL or URLs, overlap assessment, recommended action, proposed canonical target, proposed page type, reason, and evidence needed.

Use only these recommended actions: keep and optimise, expand existing page, create new page, merge pages, redirect after merge, add FAQ section, or investigate manually.

Treat similar wording as insufficient evidence of overlap. Compare the searcher task, intent, page type and topic. If two existing pages could target the same cluster, identify the page that should become the canonical target and state why. If the inventory lacks enough information to judge, use "investigate manually" and list the exact missing evidence. Do not recommend redirects unless the relevant URLs are supplied. Do not assume a page ranks, converts or has backlinks if the field is absent.
4Sales question mappingUse this when sales calls, demos or support notes contain language that keyword tools understate or miss.
Map customer questions to search-intent clusters using [paste sales question log] and [paste intent cluster map]. The sales question log fields are: question text, customer segment, deal stage, product or service mentioned, source, date, and frequency if known. The cluster map fields are: cluster ID, cluster name, primary keyword, supporting keywords, intent, searcher task, funnel stage, suggested page type, total monthly search volume, difficulty range, country and language, existing ranking URL, and ambiguity note.

Return a Markdown table with these columns: sales question ID, customer question, customer segment, matching cluster ID, match confidence, content gap, recommended content addition, recommended location, and ambiguity note.

Use only these recommended locations: new cluster candidate, existing page section, FAQ section, comparison page, template, sales enablement only, or needs research.

Match a question only when its underlying task is the same as the cluster's searcher task. Where there is no sound match, create a new cluster candidate with a plain-language name and mark its search demand as "unknown". Keep customer wording in the customer question field. Do not turn one anecdotal question into a priority claim. If frequency is not supplied, state "not supplied".
5Prioritised content backlogUse this last, after you have the cluster map, overlap review and sales-question mapping.
Produce a prioritised content backlog from [paste intent cluster map], [paste page overlap review], and [paste sales question mapping]. Treat the supplied documents as the only evidence.

Return a Markdown table sorted from highest to lowest priority. Include these columns: priority rank, cluster ID, content opportunity, primary keyword, intent, recommended action, recommended page type, owner, target URL or URL decision, evidence, effort, priority rationale, dependency, and first brief requirement.

Set owner to one of: SEO manager, content lead, subject matter expert, product marketing, web team, or sales enablement. Set effort to low, medium or high based on the stated action and dependencies, not on assumed writing speed.

Use these decision rules:
1. Prioritise clear search demand, strategic sales-question coverage, and gaps where no suitable page exists.
2. Do not prioritise a new page where the overlap review recommends improving a suitable existing page, unless the documents show a different searcher task.
3. Keep uncertain items in the backlog, but label the dependency as the specific research needed before work starts.
4. Use "unknown" where search volume, difficulty, conversion data or ownership is not supplied.

After the table, provide three short sections: "Top three next actions", "Items to validate before publishing", and "Deprioritised or duplicate opportunities". Do not assign numeric scores unless the input documents contain an agreed scoring method. Do not invent commercial value, traffic forecasts, rankings, or competitor gaps.

Last checked against xAI’s own pages on 2026-08-21. Grok changes quickly; anything version-specific should be confirmed upstream before you rely on it.

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