Smartphone arguments are usually framed as a contest between brands. Ofcom’s 2025 data suggests the more revealing contest may be between different parts of society. Among UK smartphone users in socio-economic group AB, 64% reported using an iPhone as their main smartphone and 35% Android. In group DE, the pattern reverses: 45% iPhone and 53% Android.
The gradient is clear across the four groups
Ofcom reports iPhone at 64% in AB, 57% in C1, 47% in C2 and 45% in DE. Android moves in the opposite direction: 35%, 41%, 53% and 53% respectively.
That creates a 29-percentage-point Apple lead in AB, a 16-point lead in C1, then Android leads of six points in C2 and eight points in DE. The national average — 54% iPhone, 45% Android — sits across these very different group profiles.
Price looks relevant, but the data does not prove causation
It is tempting to explain the gradient with one word: money. Premium iPhones are expensive, Android spans a much wider range of manufacturers and price points, and socio-economic group correlates with spending power. But the Ofcom table does not prove that price is the sole or even principal cause.
Age, household composition, employer-provided devices, brand loyalty, contract availability, family ecosystems and upgrade habits could all influence the result. Good data tells us where the pattern is; responsible analysis resists inventing a single neat reason for it.
Why this matters for digital services
For app developers and service providers, the split has practical consequences. A product designed around one platform can unintentionally serve different socio-economic groups unevenly if performance, features or testing quality differ by operating system.
This matters especially for essential or high-frequency services: banking, healthcare, public-sector apps, transport, utilities and employment platforms. Cross-platform quality is not just a technical nicety. It can become an inclusion issue.
Businesses can misread affluent customer data
A company whose customer base skews AB may see heavy iPhone traffic and assume that pattern applies to Britain as a whole. Another business serving a broader or more price-sensitive audience may see far more Android use.
Both could be correct about their own users and wrong about the country. Analytics is most useful when it is treated as audience-specific evidence rather than a universal weather forecast.
Gender differences are much smaller
Ofcom reports iPhone at 52% among men and 56% among women, with Android at 47% and 43% respectively. That four-point iPhone difference is modest compared with the 19-point gap between AB and DE iPhone share.
This is a useful reminder that not every demographic dimension is equally powerful. Marketers can waste a great deal of energy slicing audiences into decorative segments while ignoring the divisions that actually move the numbers.
Geography is smaller again
Across the four UK nations, Ofcom reports iPhone share at 56% in Northern Ireland, 54% in England, 51% in Scotland and 50% in Wales. The total range is six percentage points.
Compare that with the 19-point AB-to-DE difference, or the 28-point gap between 16–24s and people aged 65+. In this dataset, age and socio-economic group create much larger variation than national geography.
The lesson for product teams
If you are deciding test priorities, device support or campaign assumptions, “UK market share” is only the beginning. The relevant question is whether your actual users resemble the national population.
A premium financial service aimed at affluent professionals may legitimately see an iPhone-heavy audience. A council service used by every income group cannot make the same assumption. The technology strategy should follow the people, not the headline.
A percentage can describe inequality without explaining it
The Ofcom data is valuable precisely because it makes differences visible. It should not be used to stereotype individuals or declare one platform “for” one class. People are not demographic averages with charging cables.
The evidence supports a clear statement: primary smartphone operating-system choice varies substantially by socio-economic group in the UK. Why that happens is a deeper research question.