Movers ranked by clicks gained. Not position deltas.
A keyword going #15 → #11 is worth roughly zero clicks. A keyword going #4 → #3 might be 10× that. SERPVoyager sorts by the only number that pays rent: estimated monthly clicks gained.
- nike pegasus 41/running-shoes/nike/pegasus-41/835+12.4Knike pegasus 41/running-shoes/nike/pegasus-41/835+12.4K
- best running shoes 2026/guides/best-running-shoes-2026/1477+9.8Kbest running shoes 2026/guides/best-running-shoes-2026/1477+9.8K
- trail running shoes/running-shoes/trail/1165+6.2Ktrail running shoes/running-shoes/trail/1165+6.2K
- marathon shoes/running-shoes/marathon/15114+280marathon shoes/running-shoes/marathon/15114+280
Position delta is decoration. Click delta is the signal.
Every rank tracker has a movers view. Almost all of them sort the lazy way: by absolute position change. The result is a list dominated by deep-SERP shuffle where nobody clicks.
The fix is one substitution. Translate every move into estimated clicks before sorting: |CTR(p′) − CTR(p)| × volume. Same data, different sort, very different list. The visual on the right shows it: the top of the wrong list is +22 clicks; the top of the right list is +580.
- 1marathon shoes#15→#11
- 2best trail running shoes#8→#5
- 3nike pegasus 41#5→#2
- 4vaporfly review#4→#3
- 5running shoes for women#12→#11
Top of list = +22 clicks
- 1nike pegasus 41+580
- 2vaporfly review+546
- 3best trail running shoes+363
- 4running shoes for women+30
- 5marathon shoes+22
Top of list = +580 clicks
The reorder. Same window, same five keywords, two sort keys.
More than winners. And all sorted by impact.
Same window, same filters, four lenses. Each list is the top of its category by traffic impact — with the shared CTR curve doing the math underneath.
Where to send a Slack.
Keywords whose new position pays more clicks than the old one. Sorted by gain, capped to the top 100, exportable in two clicks.
Where to send the on-call.
Mirror of winners, but for traffic lost. Top row is the URL bleeding the most clicks today — typically the row to triage before standup.
First signs of life.
Keywords that broke into the top 100 from outside. Often the first measurable signal that a content sprint is starting to pay.
First signs of trouble.
Keywords that fell out of the top 100 entirely. Often the first sign of a competitor moving up or a page-template change going sideways.
Every bucket inherits the same set of facet filters from the URL-centric data model: page type, primary category, sub-categories, URL pattern. Watching /blog/* trend down while /shoes/* trends up is one filter, not three reports.
Four neighbors that share the same currency.
Movers isn’t a different product wedged into the dashboard — it’s the same data model, the same CTR curve, the same daily crawl, the same URL tree. That’s why filters compose and numbers reconcile.
Filters come from the URL tree.
Page type, primary category, sub-categories, URL pattern — the same facets that organise every other report filter Movers too. “/blog/* losers today” is one filter, not a spreadsheet.
Today’s movers, today.
Recomputed on the same nightly crawl as rankings. The morning view always reflects yesterday’s state — no separate weekly job to babysit.
Same currency as SoV.
|ΔCTR| × volume uses the same CTR curve that drives Share of Voice and Experiments. A row that adds +580 clicks here adds the same +580 clicks to your SoV roll-up.
Cannibalization shows up as a winner / loser pair.
When two of your URLs trade positions for a keyword, today’s Movers usually shows one as a winner and the other as a loser. The cannibalization queue picks it up automatically from the same signal.
The four questions teams ask on first scroll.
What date range does the comparison use?
Whatever you pick — the report compares the first and last day with data inside your selected window. Default is the last 7 days for the daily standup view, but 1, 14, 28, and 90 are one click each. Same date pickers as the rest of the dashboard.
Can I filter Movers by category, page type, or URL pattern?
Yes. The same URL-taxonomy filters that drive Rankings work on Movers: page type, primary category, sub-categories. Apply them and the four buckets (Winners, Losers, New, Dropped) recompute against the filtered set. So “movers on PDPs in the Running category” is two clicks.
What’s the impact formula, exactly?
impact = |CTR(newPos) − CTR(oldPos)| × monthlySearchVolume. CTR is looked up from the same shared CtrModel that powers Share of Voice and Experiments — so a row that says +580 clicks here will add up to +580 clicks in those reports too. The formula is on the chart in-product, not hidden in a help doc.
How quickly does a new ranking show up?
Same day. The nightly crawl populates rankings; Movers recomputes the delta from the previous day’s snapshot the moment that crawl finishes. A keyword that broke into the top 100 last night is in this morning’s “New entries” bucket.
See which overnight moves actually moved your traffic.
Plug in your keywords today. Tomorrow morning, every overnight move is ranked by |ΔCTR| × volume, the only number that maps to clicks, split into Winners, Losers, New, and Dropped.
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