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Card class: Non-HeroCategory: Ranking Analysis

At a glance

Position Histogram buckets every query your site ranks for by its average Google position and shows how many fall into each band over the selected period. It answers a question a single average cannot: are your rankings concentrated at the top of page one, spread thinly across page two, or piled up in the long tail? A healthy organic profile shows mass in the 1 to 10 buckets and a manageable tail.

What it tracks

The card reads the average position for each query from Google Search Console Search Analytics and groups those queries into position buckets, then draws a histogram of the counts. Source detail: “Position Histogram for the selected period.” Where the Position Trend card shows a moving average over time, the histogram shows the shape of your ranking spread at a glance, so you can see whether an average of, say, 12 comes from a tight cluster at position 12 or from a barbell of strong page-one terms plus a heavy page-three tail. Watch the top buckets (1 to 3 and 4 to 10): growth there is genuine page-one strength, while mass building only in the 11+ bands signals queries that earn impressions but rarely clicks. Pair with Position Distribution and Ranking Distribution for the grouped view, and with Position Trend to see how the shape changes over time.

Reconciling against the source

Rebuild this in Google Search Console by opening Performance on Search results, adding the Average position metric, and reading the Queries table. Remember the UI caps tables at 1,000 rows and drops rare anonymised queries, so a hand-built histogram will undercount the long tail; data is also 2 to 3 days delayed.

Tracked live in Vortex IQ Nerve Centre

Position Histogram is one of hundreds of KPI pulses Vortex IQ tracks across Google Search Console and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.