SERPTool · Docs

Export and use the CSV data

SERPTool gives you two CSV export formats. This page explains the difference, when to use each, and what to do with the data in Excel / Google Sheets / Airtable.

The two formats

Summary (default) — one row per keyword. 16 columns covering opportunity score, volume, CPC, difficulty, intent, weakness summary, and a deep-link back to the keyword's detail page in SERPTool.

Full SERP detail — one row per ranking URL. For a 100-keyword analysis that's 1,000 rows (10 URLs per keyword). 21 columns per row plus 17 boolean weakness columns (one per signal). This is the drill-down dataset.

Where to find them

  • Analysis-level: the CSV button at the top-right of any results page opens a dropdown with both formats.
  • Per-keyword: the CSV button on the keyword detail page. This one exports the Full SERP format, but scoped to that single keyword (10 rows).
  • Per-selection: select specific rows with the checkboxes on the analysis table, then the "Export CSV" button in the selection toolbar exports those rows (Summary format only).

Summary format — what to do with it

Filtering and sorting in Sheets Turn the first row into a header, then Data → Create filter. Sort by opportunity_score descending, filter by intent = commercial or transactional, filter by search_volume >= your threshold. That's your prioritised keyword list.

The weakness columns

  • weakness_codes = pipe-joined raw codes like LOW_DS|NO_BL|THIN_CONTENT.
  • weakness_labels = pipe-joined human labels like Low Domain Score | No Backlinks | Thin Content.

Codes are useful for programmatic filtering (CONTAINS "LOW_DS"); labels are useful for sharing with stakeholders who don't know the code vocabulary.

The keyword_link column Every row has a deep-link back into SERPTool for that keyword. When reviewing a list with someone else, they can click through and see the full SERP breakdown without needing to re-find the keyword.

Banner row The first line of the Summary export is a commented banner # [analysis name] — https://serp-tool.com/analysis/xxx. It looks like this in your spreadsheet cell but most importers skip commented lines. If yours doesn't, just delete row 1 after import.

Full SERP format — what to do with it

The real value here: pivot tables.

Import the CSV to Sheets/Excel. Create a pivot table where:

  • Rows = domain (or keyword).
  • Columns = weakness codes.
  • Values = count / sum.

You'll instantly see patterns like "in this SERP set, wikipedia.org appears 47 times, always with NO_BL, and always in top-3" or "reddit.com appears 210 times across my analyses but only 12 times in top-3 — mostly longer-tail queries". That's competitor intelligence you can act on.

The 17 boolean columns LOW_DS, LOW_PS, NO_BL, SLOW_PS, HIGH_SS, NO_HTTPS, BROKEN, OUTDATED_TECH, OLD_CONTENT, TITLE_MISMATCH, NO_KW_HEADING, NO_H_TAGS, UGC_HEAVY, WEAK_TITLE, THIN_CONTENT, NO_META_DESC, LOW_AUTH_TLD. Each is 1 (signal present) or 0 (not).

Filter WHERE THIN_CONTENT = 1 AND LOW_DS = 1 to surface the most exploitable pages — low-authority sites with thin content that are somehow still ranking.

Estimated traffic column estimated_monthly_traffic is volume × rank-dependent CTR. Summing this for all your target keywords gives a rough ceiling on the traffic available if you took the #1 slot for each.

Tactical recipes

"What domains rank most often for my competitor's keywords?"

  1. Run COMPETITOR mode against a competitor.
  2. Export Full SERP.
  3. Pivot by domain, count. Top 20 domains = the sites you'll repeatedly outrank / beat to the punch on this niche.

"Which of my target keywords have fixable weaknesses in position 1?"

  1. Export Full SERP of your analysis.
  2. Filter to rank = 1 and any weakness column = 1.
  3. The result is the list of keywords where rank 1 is vulnerable — your highest-priority targets.

"What's the total potential monthly traffic I could capture?"

  1. Export Summary.
  2. Filter to keywords you plan to target.
  3. For each, estimate realistic achievable rank (not #1, unless your site warrants it — see interpreting scores).
  4. Multiply search_volume × rank_ctr. Sum.

Caveats

  • UTF-8 characters. Keywords with non-ASCII characters (umlauts, CJK, emoji) export correctly but some old Excel versions choke on UTF-8. Use Google Sheets or a modern Excel if you see garbled characters.
  • Quoting. Any value containing a comma, quote, or newline is enclosed in quotes with internal quotes doubled. Standard CSV per RFC 4180. Every modern importer handles this.
  • Date format. last_published is an ISO-8601 date string (YYYY-MM-DD). Importers usually parse this correctly. If yours doesn't, format the column as date and it'll pick up.

Next steps