Margins
A reading app for tracking books, notes, social and discovery with a deep book catalog.
Margins, a reading tracker, got 60,000 downloads in 10 to 12 days after a rushed December launch, driven by a 1.4 million view influencer post, and holds a 4.9 rating across about 21,000 ratings. Retention at viral spikes matched or beat normal days, but monetization is very bad and product market fit is not yet reached. Lesson: test virality with small spend, prioritize retention, and plan monetization early.
- US App of the DayAbout 3 days of passive growth
- Launch with what existedFirst influencer post: 1.4M views
- Downloads pour inAbout 60,000 downloads
- Resolution wave hitsUser base roughly doubled
- AU/NZ App of the DayBest download day ever
From Paul Warren on Margins' launch
What was said about Margins
1Building for the 20 million Americans who read a book a week
Margins aimed at mainstream heavy readers, not tech early adopters. Gallup has found that 6 to 8% of American adults, about 20 million people, have read at least a book a week since the 1990s. Paul Warren pictured his typical user as a 28-year-old realtor in North Carolina who reads spicy romance, highlights as she reads and puts stickers on her Kindle.
The team avoided personal networks, Twitter and tech circles at launch, partly because Paul's tech friends read less and lean on podcasts. Reading has grown since COVID, Barnes & Noble is opening about 65 stores this year, and BookTok has tens of millions of posts and tens of billions of views.
One well-crafted app replaces the 5 to 10 tools readers stitch together. Paul tracked on Goodreads, read on Kindle and Audible, kept notes in Apple Notes and found books on Reddit, and Amazon-owned tools recommended the book he had just finished. Margins puts tracking, notes, reading, social and discovery under one roof.
His design prompt was to imagine these apps run by Apple, with ecosystem integration. In a two-decade-old category, he took the Linear and Superhuman approach and made craftsmanship the edge, since nobody there had tried it.
A year of heads-down building with about 30 testers preceded launch. After eight months of research, funding and hiring a designer and an engineer, the team spent a year building with no beta program. Only about 30 people, mostly friends and family, tried the app in that time.
The cycle was a few weeks of building, then two testers taking notes, then two more weeks of building. The tests checked whether the team's guesses about what would confuse users were right.
2The book catalog and flexible tracker
- 1Track what mattersEach user logs only fields they want
- 2Match to the workEditions deduplicated, Dune has about 600
- 3Personalize vibe searchUses what they read, loved, rated low
- 4Better resultsGive reason to track more
From Paul Warren on Margins' catalog
Rebuilding book data around the work, not the edition, became Margins' moat. Paul spent about a year to a year and a half building a catalog from a couple billion data points, deduplicating editions into one work. Dune alone has about 600 editions, and Goodreads, Amazon, Open Library, WorldCat, ISBNdb and Google Books all center on the edition.
He did the work himself, drawing on his machine learning background and long hours reading raw data files. Other book startups now pay to license Margins' metadata instead of using free options like Google Books. "The foundation for basically every book activity that you're interested in is book tracking."
Let each user track only the fields they care about. Add forms with 17 boxes feel like a doctor's office, so users fill in junk or skip them. Margins built tracking so each person logs only what matters to them, which took a year of design and data model work.
Recommendations, stats, friends' activity and author or fandom news all depend on tracked reading, so tracking had to feel natural for hundreds of thousands of people who all track differently.
Vibe search came from turning a busy subreddit into a feature. r/suggestmeabook has a few million members and ranked among the 30 most active subreddits, full of mood-based requests like getting over a nasty breakup or a trip to Portugal. Margins built search by vibe and personalizes results with what the user has read, loved or rated low.
Paul's rule: when a subreddit shows heavy activity, ask "how can I turn that into a feature." The more a user tracks, the better the results get.
3The December launch on BookTok and X
Launching into the New Year's resolution wave beat waiting for polish. Book activity spikes around Christmas and New Year's from gifts and resolutions, and reading more is one of the top two resolutions. Margins launched around December 20th with whatever it had, and the user base roughly doubled over New Year's.
"We cannot afford to miss this wave."
A couple thousand dollars of influencer spend tested virality first. Margins paid a couple of influencers a couple thousand dollars to post videos. The first post got 1.4 million views, 100,000 likes, 60,000 bookmarks and 20,000 shares, and the app got about 60,000 downloads in its first 10 to 12 days.
Press roundups followed within days. The following year the team spent about $20,000 on influencers.
Each platform needed a format that suits how the app looks. Margins is calm and cozy, so short screen recordings did not work on TikTok; what worked was a person talking for about 2 minutes about the best app for readers while demoing features. On X, illustrated sharables like monthly recaps and the annual wrapped spread, with users' 2025 wrapped posts reaching about 3 million views organically.
"Our app is not very TikTok legible."
Have paid boosting ready before a post goes viral. Paul regrets not boosting a viral TikTok with a Spark Code, and the next spike came on X, where he did not know how to boost anything.
His takeaway is to set up the paid amplification process for each platform in advance. "I regret this. This is silly."
App of the Day mattered less than seasonal timing. US App of the Day on December 16th, a random Tuesday, produced about 3 days' worth of passive growth. App of the Day in Australia and New Zealand on January 2nd, during the New Year's rush, was the best download day ever.
"App of the day basically did nothing download wise for us."
4Retention and word of mouth
With little marketing spend, retention came before acquisition and monetization. Each planning cycle Paul asks which of the three matters most, and for two years the answer has been retention, fixing product gaps behind negative reviews. Monetization becomes a priority only once a marketer has a budget and spend can be tied to revenue.
Retention is described from Paul's recollection of the curves, with no numbers shown.
Viral users retained as well as or better than organic ones. Paul compared retention curves at every spike and non-spike, including word of mouth, influencer videos, sharables and App of the Day. Every spike showed the same or better retention.
He suspects readers need real motivation, which makes them high intent. "There has not been a single occasion" where a spike retained worse.
Word of mouth has been the most consistent growth source. After launch Margins did no marketing for four or five months and still stayed in the top 200 of its category, growing every day. Users tell book clubs, sisters, kids and classes.
Paul planned to build something to foster word of mouth in 2026 but did not yet know what.
A lamp Easter egg replaced a tacky five-star prompt. Margins put a lamp and reading chair at the bottom of the home tab; tapping the lamp turns on a light with a switch click, with the rating ask beside it. It drove probably thousands of ratings, hundreds of reviews mention the lamp, and the app holds a 4.9 average across about 21,000 ratings.
"Let's just add an Easter egg and manufacture that moment of delight."
5Monetization, the unsolved part
Be good enough at acquisition, retention and monetization, best at one. Paul says a venture-scale consumer business needs reasonable performance in all three and S tier in at least one. He rates Margins reasonably good at retention and acquisition, very bad at monetization, and not yet at product market fit.
A five-minute 'subscribe because you love us' paywall still converted. The only paywall appeared once in onboarding, as a hidden step many users never saw, with no members-only features. A surprising number of people subscribed anyway, and users asked for a one-time tip jar.
At current conversion, hitting this year's user goals would roughly break even, which assumes growth goals are met and conversion holds.
Gate cosmetics and streak tools, keep core features free. Margins plans a soft paywall every user sees at least once, gating streak freezes, streak rescue and profile cosmetics. Core features stay free because they drive social growth, mirroring Duolingo's free core and paid streak repair.
"I will have a paywall. It will be like mostly the nice to haves."
A buy button aims to earn more from heavy readers than subscriptions. The sequence is to build an app readers love, then monetize an audience of hundreds of thousands with a buy button that takes a cut of each book sale. Ebooks and audiobooks would follow.
The buy-button revenue is untested. "I want a buy button in this."
6Keeping AI features unlabeled
In an AI-hostile category, Margins uses little AI and never labels it. Many readers ask whether the app uses AI and how to turn it off, and book apps with obvious AI features get cancelled and flooded with bad reviews. Margins keeps AI use minimal and does not call features AI.
Paul expects sentiment to shift once AI is common enough to go unnamed. "If you do a feature and call it AI and it's very obviously an AI feature we will get cancelled."
How Margins Built a Viral Reading App
Went viral on BookTok and X after a rushed December launch, with 60,000 downloads in 10 to 12 days and a 4.9 rating across about 21,000 ratings. Retention and acquisition are good, but monetization is very bad and it has not hit product market fit.
Margins aimed at mainstream heavy readers, not tech early adopters. Gallup has found that 6 to 8% of American adults, about 20 million people, have read at least a book a week since the 1990s. Paul Warren pictured his typical user as a 28-year-old realtor in North Carolina who reads spicy romance, highlights as she reads and puts stickers on her Kindle.
The team avoided personal networks, Twitter and tech circles at launch, partly because Paul's tech friends read less and lean on podcasts. Reading has grown since COVID, Barnes & Noble is opening about 65 stores this year, and BookTok has tens of millions of posts and tens of billions of views.
One well-crafted app replaces the 5 to 10 tools readers stitch together. Paul tracked on Goodreads, read on Kindle and Audible, kept notes in Apple Notes and found books on Reddit, and Amazon-owned tools recommended the book he had just finished. Margins puts tracking, notes, reading, social and discovery under one roof.
His design prompt was to imagine these apps run by Apple, with ecosystem integration. In a two-decade-old category, he took the Linear and Superhuman approach and made craftsmanship the edge, since nobody there had tried it.
A year of heads-down building with about 30 testers preceded launch. After eight months of research, funding and hiring a designer and an engineer, the team spent a year building with no beta program. Only about 30 people, mostly friends and family, tried the app in that time.
The cycle was a few weeks of building, then two testers taking notes, then two more weeks of building. The tests checked whether the team's guesses about what would confuse users were right.
Rebuilding book data around the work, not the edition, became Margins' moat. Paul spent about a year to a year and a half building a catalog from a couple billion data points, deduplicating editions into one work. Dune alone has about 600 editions, and Goodreads, Amazon, Open Library, WorldCat, ISBNdb and Google Books all center on the edition.
He did the work himself, drawing on his machine learning background and long hours reading raw data files. Other book startups now pay to license Margins' metadata instead of using free options like Google Books. "The foundation for basically every book activity that you're interested in is book tracking."
Let each user track only the fields they care about. Add forms with 17 boxes feel like a doctor's office, so users fill in junk or skip them. Margins built tracking so each person logs only what matters to them, which took a year of design and data model work.
Recommendations, stats, friends' activity and author or fandom news all depend on tracked reading, so tracking had to feel natural for hundreds of thousands of people who all track differently.
Vibe search came from turning a busy subreddit into a feature. r/suggestmeabook has a few million members and ranked among the 30 most active subreddits, full of mood-based requests like getting over a nasty breakup or a trip to Portugal. Margins built search by vibe and personalizes results with what the user has read, loved or rated low.
Paul's rule: when a subreddit shows heavy activity, ask "how can I turn that into a feature." The more a user tracks, the better the results get.
Launching into the New Year's resolution wave beat waiting for polish. Book activity spikes around Christmas and New Year's from gifts and resolutions, and reading more is one of the top two resolutions. Margins launched around December 20th with whatever it had, and the user base roughly doubled over New Year's.
"We cannot afford to miss this wave."
A couple thousand dollars of influencer spend tested virality first. Margins paid a couple of influencers a couple thousand dollars to post videos. The first post got 1.4 million views, 100,000 likes, 60,000 bookmarks and 20,000 shares, and the app got about 60,000 downloads in its first 10 to 12 days.
Press roundups followed within days. The following year the team spent about $20,000 on influencers.
Each platform needed a format that suits how the app looks. Margins is calm and cozy, so short screen recordings did not work on TikTok; what worked was a person talking for about 2 minutes about the best app for readers while demoing features. On X, illustrated sharables like monthly recaps and the annual wrapped spread, with users' 2025 wrapped posts reaching about 3 million views organically.
"Our app is not very TikTok legible."
Have paid boosting ready before a post goes viral. Paul regrets not boosting a viral TikTok with a Spark Code, and the next spike came on X, where he did not know how to boost anything.
His takeaway is to set up the paid amplification process for each platform in advance. "I regret this. This is silly."
App of the Day mattered less than seasonal timing. US App of the Day on December 16th, a random Tuesday, produced about 3 days' worth of passive growth. App of the Day in Australia and New Zealand on January 2nd, during the New Year's rush, was the best download day ever.
"App of the day basically did nothing download wise for us."
With little marketing spend, retention came before acquisition and monetization. Each planning cycle Paul asks which of the three matters most, and for two years the answer has been retention, fixing product gaps behind negative reviews. Monetization becomes a priority only once a marketer has a budget and spend can be tied to revenue.
Retention is described from Paul's recollection of the curves, with no numbers shown.
Viral users retained as well as or better than organic ones. Paul compared retention curves at every spike and non-spike, including word of mouth, influencer videos, sharables and App of the Day. Every spike showed the same or better retention.
He suspects readers need real motivation, which makes them high intent. "There has not been a single occasion" where a spike retained worse.
Word of mouth has been the most consistent growth source. After launch Margins did no marketing for four or five months and still stayed in the top 200 of its category, growing every day. Users tell book clubs, sisters, kids and classes.
Paul planned to build something to foster word of mouth in 2026 but did not yet know what.
A lamp Easter egg replaced a tacky five-star prompt. Margins put a lamp and reading chair at the bottom of the home tab; tapping the lamp turns on a light with a switch click, with the rating ask beside it. It drove probably thousands of ratings, hundreds of reviews mention the lamp, and the app holds a 4.9 average across about 21,000 ratings.
"Let's just add an Easter egg and manufacture that moment of delight."
Be good enough at acquisition, retention and monetization, best at one. Paul says a venture-scale consumer business needs reasonable performance in all three and S tier in at least one. He rates Margins reasonably good at retention and acquisition, very bad at monetization, and not yet at product market fit.
A five-minute 'subscribe because you love us' paywall still converted. The only paywall appeared once in onboarding, as a hidden step many users never saw, with no members-only features. A surprising number of people subscribed anyway, and users asked for a one-time tip jar.
At current conversion, hitting this year's user goals would roughly break even, which assumes growth goals are met and conversion holds.
Gate cosmetics and streak tools, keep core features free. Margins plans a soft paywall every user sees at least once, gating streak freezes, streak rescue and profile cosmetics. Core features stay free because they drive social growth, mirroring Duolingo's free core and paid streak repair.
"I will have a paywall. It will be like mostly the nice to haves."
A buy button aims to earn more from heavy readers than subscriptions. The sequence is to build an app readers love, then monetize an audience of hundreds of thousands with a buy button that takes a cut of each book sale. Ebooks and audiobooks would follow.
The buy-button revenue is untested. "I want a buy button in this."
In an AI-hostile category, Margins uses little AI and never labels it. Many readers ask whether the app uses AI and how to turn it off, and book apps with obvious AI features get cancelled and flooded with bad reviews. Margins keeps AI use minimal and does not call features AI.
Paul expects sentiment to shift once AI is common enough to go unnamed. "If you do a feature and call it AI and it's very obviously an AI feature we will get cancelled."
More in Lifestyle
LifestyleDrunk Mode
A nightlife app that helps students find parties while staying safe with friends.
2 sources · 26 tips
LifestyleGojek
An Indonesian super app for ride hailing, food delivery, payments and many other on-demand services.
2 sources · 23 tips
LifestyleThumbtack
A marketplace connecting homeowners with local service professionals for home projects.
7 sources · 10 tips
LifestyleHermes
A French luxury house making handcrafted leather goods, silk scarves and clothing, run by the Dumas family.
2 sources · 18 tips
LifestyleHouzz
A home remodeling and design app and marketplace connecting homeowners with products and professionals.
2 sources · 5 tips
LifestyleLife360
A family safety app that locates and protects people, pets and things through shared circles.
2 sources · 19 tips
LifestylePurpose
An AI mentor app for personal growth, co-founded by Mark Manson, that pushes back on users.
2 sources · 17 tipsCaveman
A paid app giving men one romantic tip for every day of the year.
1 source · 9 tips