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Prepare a keyword import

Map a copied list or CSV export, resolve conflicting duplicate rows, and save a reusable import recipe.

  1. 1Add the source
  2. 2Map columns
  3. 3Resolve conflicts
  4. 4Export and record the run
Runs locally.No upload, account, or saved draft. Anonymous usage events exclude the source and result.
Keyword import workbenchPaste, map, clean, review, export
1

Add the source

Paste a list or load a local file. Use a table when other columns should survive the cleanup.

Reading the pasted table…

2

Choose what each row means

Pick the keyword column. Keep only the extra columns needed later.

Keep additional columns
3

Review the result

Counts and preview rows show what the cleaner changed before export.

First cleaned rows
Change log
    4

    Choose the handoff format

    The output changes immediately. No file is uploaded.

    Output

    TXT contains one cleaned keyword per line.

    Ready

    Keyword import recipeSave or reload the rules. Input and output are never included.
    Recipe preflight

    Review the saved mappings

      Keyword run manifestDownload settings, counts, and SHA-256 receipts for this run. Raw input and output stay out of the file.
      Keyword fixture

      Duplicate data stays visible. Moved columns are detected.

      The input fixture contains conflicting metadata for repeated keywords. The schema-aware recipe was saved with keyword, volume, and intent in a different order; loading it against a reordered export opens a preflight before anything changes.

      Download raw CSVDownload expected resultDownload schema-aware recipe

      The workbench contract records conflict resolution and moved-column behavior as separate regression cases.

      Use this workflow when…

      • You copied keywords from a spreadsheet or notes file and need one clean list.
      • A CSV export contains repeated entries, blank cells, bullets, or numbering.
      • Repeated keywords carry different volume, intent, language, or other source values.
      • You need lines, comma-separated values, CSV, or JSON for another tool.

      What changes, exactly?

      The cleaner removes only the noise you select. It does not invent SEO data.

      Before · 7 entries
      1. technical seo audit
"keyword clustering"
Technical SEO Audit
/
search intent
keyword clustering
site audit
      Unique output
      4
      Duplicates removed
      2
      Noise removed
      1
      After · 4 keywords
      technical seo audit
keyword clustering
search intent
site audit

      Search volume, intent, difficulty, rankings, and clustering are not inferred or added. This workflow only cleans and standardizes the supplied text.

      Check these edge cases

      Use the input mode deliberately when punctuation belongs inside a keyword.

      Edge caseInputExpected result
      Quoted comma"running shoes, women"running shoes, women
      Slash in a keywordrunning / jogging shoesKeep in Lines mode
      Numbered list2) trail running shoestrail running shoes
      Capitalized duplicateSEO Audit / seo auditGroup after case normalization
      Conflicting source dataseo audit · 900 / SEO Audit · 1,100Block export until resolved

      Where the result can go

      Download the result first. It stays useful without another product.

      1Keep the file

      Copy or download the cleaned output and use it in any compatible workflow.

      2Organize and track the list

      Crawl Foundry can take over when you need a shared keyword database, prioritization, or ongoing tracking.

      Continue in Crawl FoundryDevAwesome and Crawl Foundry are operated by Matthias Ramahi. This is a related workflow handoff, not an independent recommendation.

      Keep moving only when the next job is different.

      URL list normalizerPrepare the pages behind the keyword set.JSON formatterInspect or repair structured export data.Keyword import guideUnderstand mapping, safe cleanup rules, review, and format choices.