Visibility Scores and Share of Voice: What They Compute

A visibility score is your positions, each converted into an assumed share of clicks, weighted by search volume, and added up. Share of voice is the same calculation expressed as your slice of the total available across a keyword set, usually next to competitors.

Both are genuine improvements on averaging raw positions. Both carry an assumed click curve that nobody outside the tool can inspect, which decides exactly what the number does.

Why the calculation exists

Averaging positions across keywords is broken because position isn’t a quantity — that argument is made in full in position is an ordinal, not a quantity.

A visibility index fixes the two worst parts. It converts each position into something additive by mapping it through a curve, so first place contributes far more than tenth. And it weights by search volume, so a valuable term counts more than an obscure one. The result behaves like a quantity: it can be summed, compared over time, and split by segment.

That’s a real advance. The catch is what’s inside the mapping.

The curve is an assumption

Every tool needs a number for “what share of clicks does position four get.” No such universal number exists. Click distribution varies by query type, by intent, by how many feature blocks sit above the organic results, by device, and by brand familiarity. Tools pick a curve, apply it uniformly, and produce a clean number.

Consequences worth internalising:

Scores are not comparable between tools. Two trackers can report visibility of 14 and 31 for the same site and keyword set, both correctly, because they used different curves and possibly different volume data. There is no conversion.

The scale is arbitrary. Some tools normalise to 100, some don’t. “Visibility is 23” is not a fact about the world; it’s a fact about that tool’s arithmetic on your keyword set.

Feature blocks are usually ignored. Most curves are a function of ordinal position only, so being first below four ads and a shopping grid scores identically to being first on a clean page — see what position one means on a crowded result page.

Volume estimates are themselves models. The weighting depends on third-party search volume figures, which are estimates with their own error, and which differ between vendors for the same term.

What it’s genuinely good for

Used as a relative instrument, it’s one of the better numbers in rank tracking.

Trend on a fixed keyword set. If the set doesn’t change and the tool doesn’t change, the direction is meaningful and it aggregates hundreds of keywords into one line that doesn’t lie the way an average does.

Segment comparison. Visibility by section, by intent group, or by page template, computed the same way, tells you where you’re strong. The shared curve cancels out.

Competitive share. Share of voice against a named competitor set, tracked over time, is the closest thing rank data offers to a market-position metric. Again, the direction is the signal, not the level, and it inherits every limit of competitor data — tracking competitor rankings and what it can’t tell you.

What it must not be used for

As a target in itself. Visibility can be raised by adding easy keywords to the set, which is optimising the metric rather than the business. If the set can change, the number can be gamed, including by accident.

Comparing to another company’s reported figure. Different tools, different sets, different curves.

As a proxy for traffic. It’s a modelled expectation of clicks based on assumed curves and estimated volumes. Actual clicks are measured in Search Console, for free, and there’s no reason to model something you can observe — rank tracker vs. Search Console.

In a board deck without a definition. A number nobody can define invites challenges you can’t answer.

Building one you understand

If you want a version whose behaviour you can explain, count keywords by position band and weight the bands yourself — top three, four to ten, eleven to twenty, beyond. It’s cruder, it’s transparent, and you can state the weighting when asked.

Whatever you use, the discipline is the same as everywhere else in this topic: freeze the keyword set, freeze the tool, and report change rather than level. That also keeps your alerting honest — rank alerts that don’t cry wolf.

What to actually do

1. Freeze the keyword set before treating visibility as a trend. Note any change to it on the chart.
2. Report direction and percentage change in the index, never the raw level as though it means something externally.
3. Never compare across tools. Pick one and stay.
4. Split by segment — that’s where the metric is most informative.
5. Say what it is when you present it: a weighted sum of positions using the tool’s assumed click curve. One sentence, and it stops being challengeable.