Share of Voice with the formula on the page.
The naive version (share of keywords in top 10) is just noise. SERPVoyager weights every keyword by its real CTR and real search volume, with the formula published on every chart. SoV in one report matches SoV in every other.
- /running-shoes/road/84(72)22.4%1.84%
- /running-shoes/nike/pegasus-41/24(22)16.8%2.41%
- /running-shoes/trail/56(41)10.2%1.36%
- /running-shoes/track/32(28)8.4%1.92%
One curve. Posted. Used in every report.
Each keyword contributes a slice of voice: monthly search volume × CTR at the position you hold. Divide by total volume and you have the share you’re actually capturing, not the share you’re vaguely present in.
The CTR curve is the variable that makes or breaks comparability between tools. Ours is published and used in the SoV chart, the movers ranking, and the experiments scoring, so the three numbers reconcile when you cross-check them.
v1 covers positions #1–#30; the exact value at every position is readable in the app on the same page as the chart it powers. Per-project GSC overrides are on the v2 roadmap.
- #131.7%
- #224.7%
- #318.7%
- #413.6%
- #59.5%
- #66.2%
- #74.2%
- #83.1%
- #92.2%
- #101.6%
- #11+decay to 0.28% at #20, 0.05% at #30
The actual production curve we ship today. Click numbers are live in-product on every chart that uses them.
Per-category leaderboards. Drill from Shoes to Nike to Running to a single URL without leaving the view.
Domain SoV is the headline. The slice is the answer.
Domain-level SoV is the headline number every tool ships, and the least actionable. The real question is which slice of your domain is gaining and which is bleeding, and which competitor is taking that share.
Because every keyword is mapped to its URL, category, sub-category, and page type, SoV becomes a function of those facets. Compare your /shoes/ against nike.com’s /shoes/. Filter to PDPs only and watch your category-leader gap shrink. Drill from “all of brand” to “Nike Running PDPs” without exporting anything.
None of this works on a flat keyword list. The URL-centric data model is the precondition.
Four neighbors that share the same curve.
SoV is the most-quoted number in SEO and the most often wrong. The fix is single-source: every report below reads from the same CTR curve, the same volume table, the same URL model.
Slicing depends on the URL model.
SoV by category, sub-category, page type, or URL pattern is only possible because every keyword carries those facets. The data model is the precondition for the slicing to work at all.
Recomputed nightly.
Same daily crawl as rankings and AIO. SoV is fresh by the time you open the dashboard — not lagging a week behind the data it summarises.
SoV deltas surface as movers.
A page that moves from #11 to #4 contributes a lot to today’s SoV bump. Movers is ranked by |ΔCTR| × volume — the same currency SoV uses — so the two views tell one story.
Cannibalization caps SoV.
Two URLs splitting a keyword between #4 and #11 capture less click volume than either could alone. The cannibalization workflow shows the SoV cost per pair, before and after the decision.
The four questions you should ask any SoV tracker.
What CTR curve do you use, and where does it come from?
A blended curve from industry click-distribution studies, calibrated to plain organic SERPs. v1 covers 30 positions; the exact numbers are visible on every chart that uses them. Future versions are pinned per snapshot, so historic SoV stays reproducible even after we publish a new curve.
How do you handle queries where no one really clicks (knowledge panels, ‘people also ask’)?
v1 applies a single organic curve regardless of SERP features. That tends to overstate absolute clicks on SERPs with heavy zero-click features, but it stays honest for relative SoV between you and your competitors because the same curve is applied to everyone on the same SERP. Feature-aware trims are on the v2 roadmap.
Can I bring my own CTR curve from GSC?
Not in v1. The shipped curve is global today, which keeps numbers comparable across projects but means it can’t be tuned to a specific vertical. Per-project overrides (upload a CSV or auto-import from a connected GSC property) are the planned v2. Hit us during trial if it’s a hard requirement.
How does SoV here compare to other tools’ SoV numbers?
Most other tools publish ‘visibility’ or ‘estimated traffic share’ numbers that mix volume, CTR, and a private weighting. Ours is the same Σ(volume × CTR) / Σ(volume) you’d write on a whiteboard, with the inputs visible. Numbers will differ between tools — the right question is which one reconciles with the next chart you look at. Ours always does, because the curve is shared.
See your CTR-weighted Share of Voice tomorrow morning.
Plug in your keywords today. Tomorrow morning, SoV computed the right way: Σ(volume × CTR by position) ÷ Σ(volume). Curve on every chart, broken out by page, category, and competitor.
14-day free trial. No credit card.