Why Browser Market Share Reports Disagree

Browser share figures from different sources rarely agree, sometimes by a wide margin. The differences are methodological and largely predictable once the method is known.

Each source measures its own panel

A measurement network reports the browsers used on the sites it happens to serve. That set of sites is not a sample of the web; it is a sample of that network's customers.

Sites using a given network skew toward particular regions, industries and audience types. The browser mix of those audiences is what gets reported.

Two networks with different customer bases therefore produce different figures from correct measurement of different populations.

Regional weighting compounds this, because browser preferences vary sharply by country and a panel weighted toward one region reports that region's mix.

Filtering choices move the numbers

Automated traffic must be excluded, and there is no standard method. One source's aggressive filter and another's permissive one produce different denominators.

Because automation is heavily concentrated in a few claimed identities, filtering differences affect specific browsers disproportionately rather than scaling everything evenly.

Sources rarely publish enough detail about filtering to reconcile the gap, which is why comparison across sources is unreliable.

The unit of measurement differs

Share may be measured in page views, sessions or estimated people. These give different answers because browsing intensity varies by browser and platform.

Page-view share favours browsers used for long sessions. Person-based estimates rely on additional inference that introduces its own error.

Comparing a page-view figure with a session figure is comparing different quantities that happen to share a name.

Classification boundaries vary

Whether a derivative browser counts as itself or as its base engine changes the totals for both. Sources make this call differently.

Embedded browsers inside applications are another boundary case, sometimes counted as their host platform and sometimes as the underlying engine.

These decisions are usually documented briefly if at all, yet they can account for a meaningful part of the disagreement.

Reclassification also happens quietly. A source that begins separating a derivative browser from its base produces a step change that resembles adoption.

Using the figures sensibly

Cross-source comparison is the main error to avoid. Within one source, trends over time are consistent because the method is held constant.

For decisions about a specific site, the site's own measurement beats any published figure, since it reflects the audience that actually visits.

Published shares are best used as context for the general direction of the ecosystem, not as inputs to a decision about which browsers to support.