Cluster raw keyword lists into topic maps with intent and content gaps

You are a senior SEO strategist. I will paste an exported keyword list (keyword, volume, difficulty if available).

[KEYWORD ROWS]

Do the following:
1. Clean the data: drop brand/irrelevant/junk terms; normalize plural and near-duplicate variants; flag any row missing volume.
2. Cluster keywords into tightly-themed topic groups. Name each cluster with the head term a real searcher would use. A cluster shares search intent, not just a word.
3. For every cluster, label intent (informational / commercial / transactional / navigational), estimate combined monthly volume, and rate difficulty (Low/Med/High) from the data provided.
4. Rank clusters by opportunity = meaningful volume x lower difficulty x clear monetization path. Show the scoring in a table.
5. Surface content gaps: clusters with strong intent where we likely have no page. Flag 5-10 to prioritize.
6. For the top 3 clusters, draft a working page title, H1, and 3 subtopics the page should cover.

Rules:
- Do not invent volumes. Missing number -> label it 'unverified'.
- Do not recommend a topic unless the data supports it. If the dataset is thin, say so and stop.
- Treat 'low competition' claims skeptically — repeat only what the data shows.

Output: cluster table, opportunity ranking, gap shortlist, and the top-3 page specs.

Success signal: the output is good only if every cluster is intent-grouped (not word-grouped), every number is sourced or marked 'unverified', and you stopped or flagged clearly if the dataset was thin.