Sector only explains about a tenth of the all-female funding gap

Syndicate Room

September 21, 2026

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9 min read

In our first look at Companies House share-allotment filings, all-female founding teams won roughly one round in fifteen but only a few pence in every pound. We flagged one hypothesis we hadn't yet tested: that much of the gap is sector mix, with women concentrated in consumer businesses that raise less and men in the deeptech and software categories that raise more. We've now run that test on the Sonde dataset.

• Women do cluster in lower-capital sectors. 27% of all-female rounds are in consumer against 17% of all-male rounds; men are 1.5× as likely to be in deeptech. And consumer does raise less: the typical consumer round is about a third smaller than the typical deeptech round.

• But the gap survives inside every sector. Hold sector constant and all-female teams still raise 11–19% less at the median in deeptech, software and consumer alike. The shortfall is similar from one sector to the next.

• Re-weighting women onto the male sector mix closes only around a tenth of the gap. Our estimates run from 6% to 19% depending on the measure and on how finely we cut the sectors. The rest is women raising less than men in the same sector, which is a different problem with different remedies.

The hypothesis

The argument runs: women disproportionately found consumer, retail, health and education businesses, which are less capital-intensive and raise smaller rounds whereas men disproportionately found AI, energy and deep science businesses, which are capital-hungry and raise larger ones.

If that were the whole story, the gender gap would really be a sector gap wearing a different label, and a woman-founded consumer company would raise about the same as a man-founded consumer company. We set out to test this.

Step 1: where women and men actually build

We started with the 24 sector tags Sonde assigns at company level and collapsed them into four buckets: deeptech and science (deeptech, life sciences, medtech, hardware, energy, agritech, manufacturing and mobility), software and tech (SaaS, AI, cybersecurity, fintech, healthtech, edtech and proptech), consumer (consumer brands, food and drink, retail, marketplaces, media and gaming), and other. We then looked at what share of each group's fundraising rounds fell into each bucket over 2023–2025. That gives us 1,088 all-female rounds and 8,068 all-male rounds.

The first half of the hypothesis holds. All-female teams are 1.6× as likely to be in consumer overall, and all-male teams are 1.5× as likely to be in deeptech. At the level of individual sectors the skew is sharper still: all-female teams are 3.5× as likely to be in retail and 2× as likely to be in consumer brands, while all-male teams are 3× as likely to be in energy. Software looks even at the bucket level, but that hides two opposite skews inside it: women over-index in healthtech (1.9×) and edtech (1.8×), men in AI (1.6×), fintech and SaaS. That matters in Step 4, where we run the numbers on the individual sectors as well as on the four buckets.

Step 2: do those sectors raise less

They do. The typical (median) round across all founders is £427k in deeptech, £310k in software, £274k in consumer and £225k in other. A consumer company raises about a third less than a deeptech one at the typical round. So the second half of the hypothesis holds as well: women are over-represented in the sectors that raise less, and those sectors really do raise less.

At this point the sector story looks fully vindicated, but we still have to compare how raises perform within sectors.

Step 3: compare like with like

If sector explained the gap, then within a sector women and men should raise roughly the same. They don't. In every bucket, all-female teams raise less at the median.

0.81–0.89× the ratio of all-female to all-male median round size in deeptech, software and consumer. The shortfall is there whichever sector you look at. Source: Sonde, sondedata.com

An all female deeptech founder team is about 11% behind a all male deeptech founder team. In software it's 19% and even in consumer they are 18% behind. In short what this means is that an all female team does not close the gap by picking the 'right' sector. They carries a broadly similar discount into whichever one they chooses (the deeptech figure rests on 160 all-female rounds, so it is the least precise of the three).

There is a more refined version of the sector hypothesis which says the gap is really about sub-sector: women in direct-to-consumer beauty rather than consumer fintech, say, or in wellness apps rather than enterprise SaaS. If that were doing the work, we would expect the female-to-male ratio to jump around from bucket to bucket, because the sub-sector mix inside consumer is nothing like the sub-sector mix inside deeptech. It moves, but within a narrow band. There could still be other factors at play here - stage, company age or round tranche - but seeing the same pattern across sectors suggests the female founder factor is having an effect. Further investigation is warranted, controlling for those other influences on round size. 

The mean tells the same story with a heavier accent. Within each of the three main buckets the mean ratio sits at 0.52–0.70, well below the median ratio. That is the 'missing top end' from our first article showing up again, but this time inside every sector rather than as an artefact of women being absent from the mega-round sectors. Women are not merely under-represented in deeptech; the female deeptech founders who are there are also not getting the largest deeptech rounds.

Step 4: how much of the gap is sector

The final step puts a number on it. We take the actual all-female rounds and re-weight them so that their sector mix matches the all-male one (a round in an under-represented sector counts for more, a round in an over-represented sector for less), then read off the median of the re-weighted rounds. We do it twice: once on the four buckets, and once on the 24 individual sectors.

Re-weighting moves the all-female median by £3k to £6k, against a total gap of £58k. That is 6% of the gap explained by sector composition on the four buckets and 10% on the 24 individual sectors. Run the same exercise on means rather than medians and sector explains 9% and 19% respectively (the finer cut explains more of the mean because the very largest rounds cluster in a handful of sectors where men dominate).

It's important to note that the median estimate is not a precise one. The gap itself is small in pound terms and medians are lumpy, so when we resample the data the sector share on the four buckets ranges from nothing to around half, and the 24-sector cut is noisier still. Around a tenth is the most likely answer, but the robust conclusion is the weaker one: sector explains a minority of the gap on every measure we tried.

Put simply, if you could wave a wand and redistribute every all-female company across sectors so that they looked exactly like all-male companies, you would most likely close about a tenth of the funding gap, and on our least favourable measure about a fifth. Most of it would still be there.

What this does and doesn't tell us

The analysis does not say that sector is irrelevant. Women really are 1.6 times as likely to build consumer businesses, consumer really does raise less, and Angel Academe's focus on getting female founders into the capital-intensive sectors with better funding and support is aimed at a real effect. But we should no longer just say that all female founders are just building companies in less capital intensive sectors.

Our analysis also does not say why the within-sector gap exists. The re-weighting tells us that sector isn't the answer; it doesn't tell us what is. The candidates are the usual ones: investor behaviour, women raising at earlier stages or in smaller tranches, differences in ask size, or differences in business model that sit below the level of our sector tags. We could look at tracking the all-female cohort through the funding stages and that could give us more information as a next piece of analysis. 

Looking ahead

Hopefully this adds to the discussion around all female founded startups and there is more work to be done. I am particularly interested in the funding journeys and indeed the share price and exit performance too. Let me know if you have further thoughts or questions about the work.

For investors who want exposure to the part of the market this analysis describes, SyndicateRoom partners with Angel Academe on an EIS fund built around female-founded businesses across the sectors above, including the deeptech and software categories where the within-sector gap is just as present. 

Always speak to a registered financial adviser if you’re unsure if a product is a good fit for your financial circumstances.

Source: Sonde analysis of Companies House SH01 share-allotment filings, 2023–2025, GBP-denominated rounds by UK-domiciled companies with a sector tag (1,088 all-female and 8,068 all-male rounds); founder gender inferred from first names; methodology at sondedata.com/market-data#methodology. Data as at September 2026.