John did not explicitly describe a specific launch campaign or outreach effort to get his first users. The app was launched in 2017 on iOS and Android after being rebuilt iteratively, and initial downloads appear to have come organically through the App Store. He began applying basic App Store Optimization (ASO) early on — adding location-specific keywords like city and transit system names (e.g., "New York MTA subway," "Chicago CTA L train") to his app title, subtitle, and keyword metadata. This caused downloads to increase "substantially," implying early traction was driven purely by App Store search visibility rather than any paid or social channel. He also localized screenshots to be city-specific — each localization showed transit imagery relevant to that city — which improved conversion from App Store listing views. No mention was made of a Product Hunt launch, social media push, press coverage, or beta user outreach. The first users were essentially self-selecting transit riders who found the app by searching the App Store.
Momego
Real-time bus and train tracking app covering 160+ cities worldwide
7 moves, in order
- Launch (2017)App Store optimization
Added location-specific keywords (e.g., 'New York MTA subway,' 'Chicago CTA L train') to the app title, subtitle, and keyword metadata. Updated screenshots to be city-specific for each localization so users saw transit imagery relevant to their location.
Downloads increased substantially; app began ranking for targeted city/transit search terms - Early GrowthApp store optimization localization
Exploited App Store localization loophole: added keywords in Mexican Spanish (and other localizations), which Apple indexes with equal weight in the US App Store as native English keywords — effectively doubling keyword slots without additional cost.
Expanded keyword coverage and US App Store ranking without extra spend - Early GrowthApp store search autocomplete research
Used the App Store's own search autocomplete to identify high-intent, low-competition keywords. By typing partial phrases, John observed the autocomplete list and targeted terms that appeared early — reasoning that most users tap the first or second autocomplete suggestion, making those terms high-conversion targets.
Achieved top-5 rankings for multiple specific transit keywords - Early GrowthApple search ads
Used Apple Search Ads to test small batches of keywords to identify which converted best before committing to them in organic metadata.
Validated high-converting keywords to feed back into ASO metadata - Pre Pandemic (~2017–2019)In app ratings prompts
Strategically placed rating request prompts at the 'golden moment' — when a user taps a bus stop and sees a live bus moving on the map. This moment of peak delight was used to solicit App Store ratings, driving a continuous inflow of positive reviews.
Accumulated 75,000+ ratings; improved App Store ranking for all targeted keywordsMRR $8.0k - Pandemic Pivot (August 2020)Subscription monetization pivot
Abandoned banner ads after COVID collapsed ad revenue. Rebuilt the app around a subscription model with premium features (trip assist, ML-powered delay notifications, alternative routing). Launched the new version in August 2020 with annual, weekly, and lifetime plan options.
Subscription revenue gradually replaced lost ad revenue (~$8K/month baseline restored over ~1 year)MRR $8.0k - Growth Phase (2021)Paywall ab testing
Used event-based analytics (Mixpanel) to run ~10 A/B tests on different paywall and onboarding designs over 2–3 months. Key unlock: added a 'reverse trial' — when users close the paywall, they automatically get a free 7-day Pro trial without needing to enter payment info. This removed commitment friction entirely.
Conversion rate jumped from 0.5% to 8%; MRR grew from ~$8K to $30K+MRR $30k
John worked for a bus company in Edinburgh, giving him insider familiarity with public transit data systems and real-world operator APIs — reducing the research burden most founders would face when building a transit tracking app.
app_store_optimization
Banner ad monetization was the original revenue model (~$8K/month), but the COVID-19 pandemic caused ad revenue to collapse entirely, forcing a pivot to subscriptions. Relying on vanity metrics like monthly active users (rather than event-based analytics) also failed to drive meaningful growth for the first few years.
How I built a $30K/month mobile app
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