Hyperlocal pollen forecasts for allergy sufferers

The idea

Allergy sufferers plan their lives around a number that’s wrong for them twice over: city-level pollen counts miss the microclimate variation between neighborhoods, and an overall count is useless when what matters is your species — a birch-allergic person doesn’t care that grass is low. Weather apps treat pollen as a footnote; dedicated allergy apps are pharma-sponsored content shells. Meanwhile the data for per-species, coordinate-level forecasts is available from commodity APIs.

UV-Blocker proves the playbook: take one environmental health metric, turn it into timely personal alerts, charge a few dollars a month. Pollen transfers directly with better fundamentals — more sufferers, a genuine daily-check habit for months at a time in season, and a differentiator generic apps won’t build: pre-season alerts (start antihistamines now, your season begins in 10 days) grounded in the clinical fact that antihistamines work best started before exposure. A symptom log that learns which species actually predicts your bad days turns commodity data into a personal product.

Who pays

Allergy sufferers — roughly a quarter of adults in most Western markets, with the moderate-to-severe segment highly motivated — pay $3-6 a month or ~$25 a year, with conversions concentrated in a spring spike the paywall should exploit by defaulting to annual. Distribution: ASO on pollen and hay fever terms (search volume is violently seasonal, so rank before March), TikTok/Reels allergy content, and press pitches that write themselves every time a pollen season breaks records.

MVP scope

• Allergy profile onboarding and coordinate-level forecasts with per-species breakdown from Google Pollen API, cached per geohash
• Morning briefing, medication-timing, and pre-season onset alerts
• One-tap symptom log with species-correlation insights after 3 weeks
• 5-day outlook and trip-mode city search
• RevenueCat free/paid split with seasonal annual push
• Skip for v1: Android (fast follow), air quality and mold as extra metrics, Apple Watch, doctor-shareable reports, home sensor integrations

Build PollenCast, a hyperlocal pollen forecast app for allergy sufferers, iOS first. Stack: React Native with Expo, Google Pollen API as primary data source (Ambee or Tomorrow.io as fallback), RevenueCat for subscriptions, a small server for alert scheduling and data caching.

Core flow: 1) Onboarding: location permission, then an allergy profile — which species trigger you (birch, oak, grass, ragweed, mugwort), symptom severity, current medications. 2) Home screen shows today at your coordinates: overall risk plus a per-species breakdown with your triggers highlighted, hourly trend curve, and a 5-day outlook. 3) Alert engine sends: morning briefings on high-trigger days with the best outdoor window (pollen dips after rain, peaks mid-morning), medication timing nudges (antihistamines work better taken before exposure), and the killer seasonal alert — your birch season starts in about 10 days, start daily antihistamines now, computed from forecast trends plus historical season onset for the user's region. 4) One-tap daily symptom log (none/mild/bad) builds a personal correlation: after 3 weeks, show which species actually predicts the user's bad days and re-weight their risk score accordingly. 5) Trip mode: check any city's forecast against your profile.

Screens: onboarding + allergy profile, today, 5-day forecast, symptom log + insights, trip search, settings, paywall.

Non-obvious details: cache API responses per geohash cell server-side — per-user API pricing kills margins; hard-sell annual during the spring spike since retention collapses off-season.

Pricing via RevenueCat: $4.99/mo, $24.99/yr (default), free tier shows overall risk only — per-species, alerts, and insights are paid.