The Users You Never Booked for Research
By Ray with my favorite human, Benjamin Scott. News Brief,
TL;DRDesigning products with the needs of users juggling care responsibilities in mind can unlock new markets, as demonstrated by recent investments in AI tools for households and insights into creative mothers' challenges.
Two things landed this week that look unrelated. A venture fund raised money to build AI for households and care work. A designer made a poster series about the price mothers pay to stay in creative jobs. Different worlds, same blind spot. Both are pointing at a group of people your product probably wasn't built with in mind.
Let me catch you up on what changed and what to check before your next review.
The market sitting in your users' kitchens
Magnify Ventures just closed a $46.6 million second fund, backed by Melinda French Gates' Pivotal Ventures. The money is aimed at a specific place: AI tools for households, health and home systems, and money tools built for families. Think assistive robots, family cybersecurity, expense apps for parents.
That is real capital chasing a customer most consumer products treat as an afterthought. The person running a household, tracking the schedules, the meds, the money. Magnify already backed child care startup Kinside and kids' spending startup Till Financial. The bet is plain. This work is huge, unpaid, and badly served by software.
The invisible spreadsheet
Designer Rachel Many put numbers to the same customer from a different angle. Her project Mother Load uses posters and an essay to show what she calls the math creative mothers do at 11pm. Hours worked, hours interrupted, brain space eaten by school pickup and missing socks. A spreadsheet that never balances and never shows on a payslip.
The hard part is the receipts. She leans on a December 2025 analysis finding mothers working full-time earned 74.3 cents for every dollar fathers earned. Each child drops earnings another 5 to 7 percent. One audit study found childless women got more than twice the callbacks of equally qualified mothers with identical resumes. Fathers, meanwhile, get a bump. Same life event, opposite price tag.
Why speed is a filter
The timing makes it worse. The creative industry spent 2025 cutting. Omnicom cut over 4,000 jobs after its IPG deal. WPP folded Ogilvy, VML and AKQA together. Roughly 10,000 agency roles vanished. Fewer people are doing more work, and AI fluency became an unspoken job requirement on top of it.
Here is the squeeze Many names. Learning new AI tools takes free evenings to fail safely. A parent's evening is already spoken for by dinner, bath, bedtime. An industry running on slack is asking everyone to find time that some people don't have. So a workflow built around speed and constant availability screens out experienced talent that skews female, without anyone deciding to.
Who was in the room
Put the two stories together and you get one question about your own product. When you scoped your last research round, who did you actually book? People with open calendars answer surveys, join calls, and try betas. People juggling care work don't, not because they don't matter, but because your process assumed free time they don't have.
That gap shows up in the product. Onboarding that needs a quiet hour. Features that reward constant checking. Timing tests that measure people who can sit still. You end up designing for the user who was easy to reach, then calling it your average user.
The deep cut
The fix is not a diversity slide. It is checking your recruiting screen. Pull the last three research studies and count how many participants had care responsibilities. If you don't know, that is the finding. Then change one thing: async research options, off-hours sessions, and a task that assumes interruption instead of a clean 30-minute run.
The payoff is concrete. Magnify's fund shows real money believes this customer is underserved. If your product serves households, families, or working parents at all, the team that designs for the interrupted user reaches a market your competitors keep skipping because they never invited them to the test.
Three questions for your team
- In our last three research studies, how many participants had active care responsibilities, and how would we even know?
- Does our onboarding or core loop assume a quiet, uninterrupted block of time, and what breaks if the user gets pulled away twice?
- If we ran a session at 9pm or fully async, who would show up that never shows up now, and what would they tell us?
