Brett Bauman
Where to hear and read about Brett Bauman2 episodes and tests
SuperwallCOPY this ai app's $6.7m/yr marketing strategy
Sub Club$6.7M ARR, No Paid Ads, and an Exit to Quizlet in 2 Years – Brett Bauman & Zack Hargett, CoconoteBrett Bauman is an ex-Loom designer and product lead who co-founded Coconote with Zack Hargett, bootstrapped it to $6.7M ARR, and sold it to Quizlet, where he now works on subscription growth. The most useful thing to learn from him is the paying-customer playbook: problem-framed content, a long personal onboarding, a late login and a trial-extension offer at cancel.
is this like a repeatable use case and two is is it core to the person's identity?
COPY this ai app's $6.7m/yr marketing strategy
Brett Bauman: the story and the lessons
1Brett Bauman's path from Loom to Coconote
Bauman came up through Loom as a designer and product lead. He joined Loom as its second designer, became product lead and started its mobile team. He later co-founded Coconote with Zack Hargett, another Loom veteran.
The two never overlapped at Loom. Friends introduced them at a Loom offsite in Los Angeles and told them they should meet.
A shared Loom past gave the pair a similar culture and network. The hosts note that most early startup failures come from co-founder mismatch. Shared employer and mutual friends gave the pair a similar culture and a reason not to hurt each other.
Hargett pitched ideas and Bauman kept answering "maybe" until one made him agree to build it.
Earlier projects went nowhere before Coconote pulled them in. Before Coconote the pair tried replacing Siri with GPT-4 in 2023, triggered by double-tapping the back of the phone. Apple gave trouble approving it and it went nowhere.
Their earlier projects felt unremarkable. With Coconote, people were pulling it out of the founders once marketing began.
Bauman and Hargett launched into a market with almost no student AI note-takers. AI note-takers on the App Store were aimed at professionals, and the student web apps were not taken seriously. They chose to execute properly on mobile.
The model was Brian Chesky's line: build the Navy SEALs, not the Navy, meaning a few skilled people instead of a big roster.
2How Coconote reached $6.7M ARR without venture money
Revenue compounded fast: $100K in 45 days, $5M in a year. Coconote crossed $100K ARR in 45 days, $1M in four months, about $2M at five months and $5M after a year, reaching $6.7M. It had over 2 million registered users and generally over 50% EBITDA.
These are the founders' own figures with no outside check, and no baseline is given for most of the gains.
They charged from day one with a scoped-down April 2024 launch. The app gave one free note, then required a trial, which worked like a hard paywall. Some audio recordings were lost at first, and much of the product still looks as it did at launch.
Later gains came from better models and new features such as podcasts made from lectures. Paying customers were a stronger signal of value than usage events.
Early revenue paid for growth, so the founders put in little cash. Each founder put in about $10K up front. Apple pays out slowly at first, but free use was tightly limited, so AI costs stayed small and startup credits covered the first year.
Models get cheaper over time, so worrying about margins early risks poor decisions. Margins stayed near 50% EBITDA through the acquisition.
Bootstrapping kept cash flowing but limited long-term bets. Lean spending gave steady cash flow for the whole period. Ownership came with trade-offs on reinvestment.
As an independent company they expected return on marketing within a month or two.
3How Coconote built its short-form video engine
Bauman's team judged videos by conversion, not view count. The PDF-to-brain-rot videos drew 100 to 200 million views and about 3,000 trial starts. That converted to roughly $25,000 against a $360,000 ceiling.
One brain-rot video hit 41M views and drove no revenue. The team said it would rather have a 10 million view video aimed at students with a real problem.
Problem and identity framing convert, while toy framing does not. Identity content ("I am a runner, so I use Strava") and problem-solving content were the two types that converted best. Novelty content made the app look like a toy.
The shock hook plus demo worked early, when the product was novel in its market. Later content had to frame the app as a solution.
They kept the creator team small and coached each person. The team ran 5 to 10 creators, 12 at most, before the acquisition, with one coach per 12 creators. Hargett interviewed every creator, usually deciding in 15 to 30 minutes.
Creators were told what converted and what did not. A 20 to 30 million view spike lets you see downfunnel effects within a couple of days.
They hired undiscovered marketers, not influencers. Creators came from DMs, Handshake, referrals and email. A Spanish tutor with no content history became a top creator within nine months.
The rule of thumb: 5 to 10K followers, good engagement and a Gmail address in the bio. An agency email means you are too late. About 30 creators were tried in two months, and three made the big difference.
Creators are judged on a three-level pyramid. The base is wanting to win: showing up on time, camera on, engaged in Slack. The middle is studying other content, such as guessing why a video went viral with the view count hidden. The top is making your own scripts and trends.
There are no quizzes and no fixed curriculum. Coaches mostly review content and walk creators through metrics.
Creators got special product screens that look better on camera. The recording and transcribing screens in the viral videos were creator-only versions, such as a big rainbow wave with the app name. Creators sit in Slack with engineers and ask for more.
A lecture-hall demo video using this approach hit 18 million views, about 99% organic.
Paid ads never became first-purchase profitable. Neither founder gave ads half their time. Clips cut by an outside agency beat the organic approach but still fell short.
Ads are hard to do half-heartedly, and an agency has weaker incentives than you. A founder who does not know where customers hang out online is not ready for ads.
The team echoed customer words in screenshots and content. Asked how they would describe the product, most customers said they use Coconote to never miss a key detail. That line went on the first App Store screenshot, next to "great for ADHD".
They chose short-form video and the ADHD angle from the start, where their users already spend time.
4Bauman's onboarding, paywall and cancel-flow changes
Doubling onboarding length lifted trial starts by 16%. Onboarding roughly doubled, from about five screens to 13 in one telling and to about 15 in the other. The added screens mostly personalized the app, for example by asking what the user studies, and added social proof.
Earlier tests of one or two screens at a time gave small wins. After the big jump they could not say which screens helped most.
Moving login after the paywall was the biggest onboarding win. Apple and Google already identify the buyer, so no account is needed to purchase. Login as the first screen had caused about 10% drop-off.
It takes plumbing because store purchase state and account state differ. Engineers build login first and it stays at the front out of habit.
They showed the paywall after a full recording, not before. Users can record an entire lecture, an hour or more, before seeing the paywall. Showing it after the first core action was described as a big win.
Letting people get invested before asking for payment lifted trial conversion.
A seven-day trial extension at cancel beat discounts and pauses. Three web offers were tested: 30% off, a 3-month pause aimed at summer break, and a seven-day extension. The extension won by far.
Web cancel flows kept 25% of would-be cancellers. In the app flow, an extra seven days stopped 27% of people entering cancel, though a smaller share went on to pay. Auto-renew is worth protecting because leavers rarely return.
5Pricing and positioning choices behind Coconote
They charged students a premium instead of capping the price. The app launched at $99 a year and $19.99 a month. A test at $129 brought more users and more revenue, and about 80% of subscribers take the annual plan.
Comparable utilities cost about a third as much. Premium pricing signals reliability, since cheaper apps can lose a recording when a phone call comes in.
The team marketed to the buyer as well as the user. Early viral videos used the hook "my mom just changed my college life forever", aimed at parents who would pay. Creators were asked to picture a mother and daughter at orientation and who would be offered a $130 app.
They later stepped back from moms. The aim is whoever has the most buying intent, and $130 looks small beside $40K to $100K in yearly tuition.
Ignoring conventional wisdom exposed a wider audience of lifelong learners. Smart skeptics would have said nobody pays for apps aimed at students. Coconote's customers turned out to be mostly lifelong learners, not 18 to 22 year olds.
Hargett asks what happens if it works, not why it won't. Pricing norms from other products, like weather apps, may not apply to a new AI product.
6What Brett Bauman looks for in a product
Bauman wants a repeatable use case that is core to identity. He points to Ladder, AllTrails and Strava as apps tied to who people are and to a repeated action. Recording lectures happens daily or a few times a week.
Notes pile up over time, such as physics 1, 2 and 3, which locks users in. The growing corpus is strong for retention.
Wow moments matter most for products sold through short-form video. Bauman's example of a wow app is Ladder, where the coach's voice makes it feel like your own app. He also cites Runna, bought by Strava, a running coach in your ear.
The aha is what the ad shows. Runna's users see themselves as runners, so it builds a habit.
Without a deep moat, copycats arrive within days. Lower barriers to building software mean a hit can get a hundred copies within a week. Without a moat, the team's ability to ship wow products is the main growth engine.
The seven powers include network effects, cornered resources and brand. Quizlet's brand, built over almost 20 years, is one such moat. Clones of Coconote were treated as possible lead gen, since users try the cheap one and may come back.
7How Bauman and Hargett sold Coconote to Quizlet
Bauman slept on the first inbound call and argued to take it. Quizlet reached out when Coconote was only a couple of months old. Hargett's first instinct was to stay heads down, and Bauman came back wanting to take the call.
Hargett's doubt was what could possibly come of that. Most inbound talks lead nowhere, so take the call only for a company you admire.
They hired an investment bank so they could keep building. Chris Park of Creative Partners ran the process from early talks through close. They advise asking a buyer for a ballpark range after a few calls and moving on if it is off.
An M&A process pulls attention from customers, building and marketing, and losing focus shows in negotiations. Hargett called the banker "our third co-founder a little bit".
The sale took about a year while revenue roughly doubled. The process ran in phases through the year, mostly waiting, and the deal closed in December. One telling puts the exit about 18 months after launch and another about two years from founding.
Only the two founders knew how far talks had gone. Engineers and creators learned on the day of close, on the advice that a great leader shelters other people.
Quizlet offered scale and patience that a bootstrapped company lacked. Quizlet's user base is an order of magnitude larger, and its finances allow bigger bets such as a media arm. Both founders are staying.
Bauman says Quizlet wants to build something similar to the founders' vision. Coconote's mission is to give learners superpowers by tailoring foundation models for learners.
8Where Bauman works now: subscription growth at Quizlet
Bauman now runs paywall experiments at Quizlet scale. He works on Coconote engineering and on subscription growth at Quizlet, and also with Cram. He says Quizlet is one of the biggest premium consumer apps.
At that scale a single paywall experiment can add a million dollars of revenue a year. He is looking for an iOS or Android engineer who enjoys running them.
The next target is bringing the cancel flow to Apple payments. The trial-extension flow runs on web and in the app for Stripe subscribers through a web view. Bringing it to Apple payments is harder but the stated next goal.
Apple's own retention-offer feature is in limited beta, and Hargett thinks it supports only discounts, not extra trial time.
COPY this ai app's $6.7m/yr marketing strategy
Two ex-Loom employees explain how they grew Coconote to 6.7 million ARR in about 18 months, bootstrapped, using a small team of part-time creators, targeted short-form video, a longer onboarding and trial-extension anti-churn flow. The result: 100K ARR in 45 days, 5 million in a year, over 50% EBITDA, and an acquisition by Quizlet.
Bauman came up through Loom as a designer and product lead. He joined Loom as its second designer, became product lead and started its mobile team. He later co-founded Coconote with Zack Hargett, another Loom veteran.
The two never overlapped at Loom. Friends introduced them at a Loom offsite in Los Angeles and told them they should meet.
Earlier projects went nowhere before Coconote pulled them in. Before Coconote the pair tried replacing Siri with GPT-4 in 2023, triggered by double-tapping the back of the phone. Apple gave trouble approving it and it went nowhere.
Their earlier projects felt unremarkable. With Coconote, people were pulling it out of the founders once marketing began.
Bauman and Hargett launched into a market with almost no student AI note-takers. AI note-takers on the App Store were aimed at professionals, and the student web apps were not taken seriously. They chose to execute properly on mobile.
The model was Brian Chesky's line: build the Navy SEALs, not the Navy, meaning a few skilled people instead of a big roster.
Revenue compounded fast: $100K in 45 days, $5M in a year. Coconote crossed $100K ARR in 45 days, $1M in four months, about $2M at five months and $5M after a year, reaching $6.7M. It had over 2 million registered users and generally over 50% EBITDA.
These are the founders' own figures with no outside check, and no baseline is given for most of the gains.
Bootstrapping kept cash flowing but limited long-term bets. Lean spending gave steady cash flow for the whole period. Ownership came with trade-offs on reinvestment.
As an independent company they expected return on marketing within a month or two.
Bauman's team judged videos by conversion, not view count. The PDF-to-brain-rot videos drew 100 to 200 million views and about 3,000 trial starts. That converted to roughly $25,000 against a $360,000 ceiling.
One brain-rot video hit 41M views and drove no revenue. The team said it would rather have a 10 million view video aimed at students with a real problem.
Problem and identity framing convert, while toy framing does not. Identity content ("I am a runner, so I use Strava") and problem-solving content were the two types that converted best. Novelty content made the app look like a toy.
The shock hook plus demo worked early, when the product was novel in its market. Later content had to frame the app as a solution.
They kept the creator team small and coached each person. The team ran 5 to 10 creators, 12 at most, before the acquisition, with one coach per 12 creators. Hargett interviewed every creator, usually deciding in 15 to 30 minutes.
Creators were told what converted and what did not. A 20 to 30 million view spike lets you see downfunnel effects within a couple of days.
They hired undiscovered marketers, not influencers. Creators came from DMs, Handshake, referrals and email. A Spanish tutor with no content history became a top creator within nine months.
The rule of thumb: 5 to 10K followers, good engagement and a Gmail address in the bio. An agency email means you are too late. About 30 creators were tried in two months, and three made the big difference.
Creators are judged on a three-level pyramid. The base is wanting to win: showing up on time, camera on, engaged in Slack. The middle is studying other content, such as guessing why a video went viral with the view count hidden. The top is making your own scripts and trends.
There are no quizzes and no fixed curriculum. Coaches mostly review content and walk creators through metrics.
Creators got special product screens that look better on camera. The recording and transcribing screens in the viral videos were creator-only versions, such as a big rainbow wave with the app name. Creators sit in Slack with engineers and ask for more.
A lecture-hall demo video using this approach hit 18 million views, about 99% organic.
The team echoed customer words in screenshots and content. Asked how they would describe the product, most customers said they use Coconote to never miss a key detail. That line went on the first App Store screenshot, next to "great for ADHD".
They chose short-form video and the ADHD angle from the start, where their users already spend time.
Doubling onboarding length lifted trial starts by 16%. Onboarding roughly doubled, from about five screens to 13 in one telling and to about 15 in the other. The added screens mostly personalized the app, for example by asking what the user studies, and added social proof.
Earlier tests of one or two screens at a time gave small wins. After the big jump they could not say which screens helped most.
Moving login after the paywall was the biggest onboarding win. Apple and Google already identify the buyer, so no account is needed to purchase. Login as the first screen had caused about 10% drop-off.
It takes plumbing because store purchase state and account state differ. Engineers build login first and it stays at the front out of habit.
They showed the paywall after a full recording, not before. Users can record an entire lecture, an hour or more, before seeing the paywall. Showing it after the first core action was described as a big win.
Letting people get invested before asking for payment lifted trial conversion.
A seven-day trial extension at cancel beat discounts and pauses. Three web offers were tested: 30% off, a 3-month pause aimed at summer break, and a seven-day extension. The extension won by far.
Web cancel flows kept 25% of would-be cancellers. In the app flow, an extra seven days stopped 27% of people entering cancel, though a smaller share went on to pay. Auto-renew is worth protecting because leavers rarely return.
The team marketed to the buyer as well as the user. Early viral videos used the hook "my mom just changed my college life forever", aimed at parents who would pay. Creators were asked to picture a mother and daughter at orientation and who would be offered a $130 app.
They later stepped back from moms. The aim is whoever has the most buying intent, and $130 looks small beside $40K to $100K in yearly tuition.
Bauman wants a repeatable use case that is core to identity. He points to Ladder, AllTrails and Strava as apps tied to who people are and to a repeated action. Recording lectures happens daily or a few times a week.
Notes pile up over time, such as physics 1, 2 and 3, which locks users in. The growing corpus is strong for retention.
Wow moments matter most for products sold through short-form video. Bauman's example of a wow app is Ladder, where the coach's voice makes it feel like your own app. He also cites Runna, bought by Strava, a running coach in your ear.
The aha is what the ad shows. Runna's users see themselves as runners, so it builds a habit.
Without a deep moat, copycats arrive within days. Lower barriers to building software mean a hit can get a hundred copies within a week. Without a moat, the team's ability to ship wow products is the main growth engine.
The seven powers include network effects, cornered resources and brand. Quizlet's brand, built over almost 20 years, is one such moat. Clones of Coconote were treated as possible lead gen, since users try the cheap one and may come back.
Bauman slept on the first inbound call and argued to take it. Quizlet reached out when Coconote was only a couple of months old. Hargett's first instinct was to stay heads down, and Bauman came back wanting to take the call.
Hargett's doubt was what could possibly come of that. Most inbound talks lead nowhere, so take the call only for a company you admire.
They hired an investment bank so they could keep building. Chris Park of Creative Partners ran the process from early talks through close. They advise asking a buyer for a ballpark range after a few calls and moving on if it is off.
An M&A process pulls attention from customers, building and marketing, and losing focus shows in negotiations. Hargett called the banker "our third co-founder a little bit".
The sale took about a year while revenue roughly doubled. The process ran in phases through the year, mostly waiting, and the deal closed in December. One telling puts the exit about 18 months after launch and another about two years from founding.
Only the two founders knew how far talks had gone. Engineers and creators learned on the day of close, on the advice that a great leader shelters other people.
Quizlet offered scale and patience that a bootstrapped company lacked. Quizlet's user base is an order of magnitude larger, and its finances allow bigger bets such as a media arm. Both founders are staying.
Bauman says Quizlet wants to build something similar to the founders' vision. Coconote's mission is to give learners superpowers by tailoring foundation models for learners.
Bauman now runs paywall experiments at Quizlet scale. He works on Coconote engineering and on subscription growth at Quizlet, and also with Cram. He says Quizlet is one of the biggest premium consumer apps.
At that scale a single paywall experiment can add a million dollars of revenue a year. He is looking for an iOS or Android engineer who enjoys running them.
$6.7M ARR, No Paid Ads, and an Exit to Quizlet in 2 Years – Brett Bauman & Zack Hargett, Coconote
Two ex-Loom builders launched an AI lecture note-taking app with a free trial from day one, grew it through a small team of content creators, and used a long onboarding and trial-extension cancellation offers to convert and retain students. They reached $100K ARR in 45 days, $1M in 4 months and $6.7M ARR with no paid ads, then sold to Quizlet in about two years.
Bauman came up through Loom as a designer and product lead. He joined Loom as its second designer, became product lead and started its mobile team. He later co-founded Coconote with Zack Hargett, another Loom veteran.
The two never overlapped at Loom. Friends introduced them at a Loom offsite in Los Angeles and told them they should meet.
A shared Loom past gave the pair a similar culture and network. The hosts note that most early startup failures come from co-founder mismatch. Shared employer and mutual friends gave the pair a similar culture and a reason not to hurt each other.
Hargett pitched ideas and Bauman kept answering "maybe" until one made him agree to build it.
Earlier projects went nowhere before Coconote pulled them in. Before Coconote the pair tried replacing Siri with GPT-4 in 2023, triggered by double-tapping the back of the phone. Apple gave trouble approving it and it went nowhere.
Their earlier projects felt unremarkable. With Coconote, people were pulling it out of the founders once marketing began.
Bauman and Hargett launched into a market with almost no student AI note-takers. AI note-takers on the App Store were aimed at professionals, and the student web apps were not taken seriously. They chose to execute properly on mobile.
The model was Brian Chesky's line: build the Navy SEALs, not the Navy, meaning a few skilled people instead of a big roster.
Revenue compounded fast: $100K in 45 days, $5M in a year. Coconote crossed $100K ARR in 45 days, $1M in four months, about $2M at five months and $5M after a year, reaching $6.7M. It had over 2 million registered users and generally over 50% EBITDA.
These are the founders' own figures with no outside check, and no baseline is given for most of the gains.
They charged from day one with a scoped-down April 2024 launch. The app gave one free note, then required a trial, which worked like a hard paywall. Some audio recordings were lost at first, and much of the product still looks as it did at launch.
Later gains came from better models and new features such as podcasts made from lectures. Paying customers were a stronger signal of value than usage events.
Early revenue paid for growth, so the founders put in little cash. Each founder put in about $10K up front. Apple pays out slowly at first, but free use was tightly limited, so AI costs stayed small and startup credits covered the first year.
Models get cheaper over time, so worrying about margins early risks poor decisions. Margins stayed near 50% EBITDA through the acquisition.
Bootstrapping kept cash flowing but limited long-term bets. Lean spending gave steady cash flow for the whole period. Ownership came with trade-offs on reinvestment.
As an independent company they expected return on marketing within a month or two.
Bauman's team judged videos by conversion, not view count. The PDF-to-brain-rot videos drew 100 to 200 million views and about 3,000 trial starts. That converted to roughly $25,000 against a $360,000 ceiling.
One brain-rot video hit 41M views and drove no revenue. The team said it would rather have a 10 million view video aimed at students with a real problem.
Problem and identity framing convert, while toy framing does not. Identity content ("I am a runner, so I use Strava") and problem-solving content were the two types that converted best. Novelty content made the app look like a toy.
The shock hook plus demo worked early, when the product was novel in its market. Later content had to frame the app as a solution.
They kept the creator team small and coached each person. The team ran 5 to 10 creators, 12 at most, before the acquisition, with one coach per 12 creators. Hargett interviewed every creator, usually deciding in 15 to 30 minutes.
Creators were told what converted and what did not. A 20 to 30 million view spike lets you see downfunnel effects within a couple of days.
They hired undiscovered marketers, not influencers. Creators came from DMs, Handshake, referrals and email. A Spanish tutor with no content history became a top creator within nine months.
The rule of thumb: 5 to 10K followers, good engagement and a Gmail address in the bio. An agency email means you are too late. About 30 creators were tried in two months, and three made the big difference.
Paid ads never became first-purchase profitable. Neither founder gave ads half their time. Clips cut by an outside agency beat the organic approach but still fell short.
Ads are hard to do half-heartedly, and an agency has weaker incentives than you. A founder who does not know where customers hang out online is not ready for ads.
The team echoed customer words in screenshots and content. Asked how they would describe the product, most customers said they use Coconote to never miss a key detail. That line went on the first App Store screenshot, next to "great for ADHD".
They chose short-form video and the ADHD angle from the start, where their users already spend time.
Doubling onboarding length lifted trial starts by 16%. Onboarding roughly doubled, from about five screens to 13 in one telling and to about 15 in the other. The added screens mostly personalized the app, for example by asking what the user studies, and added social proof.
Earlier tests of one or two screens at a time gave small wins. After the big jump they could not say which screens helped most.
Moving login after the paywall was the biggest onboarding win. Apple and Google already identify the buyer, so no account is needed to purchase. Login as the first screen had caused about 10% drop-off.
It takes plumbing because store purchase state and account state differ. Engineers build login first and it stays at the front out of habit.
A seven-day trial extension at cancel beat discounts and pauses. Three web offers were tested: 30% off, a 3-month pause aimed at summer break, and a seven-day extension. The extension won by far.
Web cancel flows kept 25% of would-be cancellers. In the app flow, an extra seven days stopped 27% of people entering cancel, though a smaller share went on to pay. Auto-renew is worth protecting because leavers rarely return.
They charged students a premium instead of capping the price. The app launched at $99 a year and $19.99 a month. A test at $129 brought more users and more revenue, and about 80% of subscribers take the annual plan.
Comparable utilities cost about a third as much. Premium pricing signals reliability, since cheaper apps can lose a recording when a phone call comes in.
The team marketed to the buyer as well as the user. Early viral videos used the hook "my mom just changed my college life forever", aimed at parents who would pay. Creators were asked to picture a mother and daughter at orientation and who would be offered a $130 app.
They later stepped back from moms. The aim is whoever has the most buying intent, and $130 looks small beside $40K to $100K in yearly tuition.
Ignoring conventional wisdom exposed a wider audience of lifelong learners. Smart skeptics would have said nobody pays for apps aimed at students. Coconote's customers turned out to be mostly lifelong learners, not 18 to 22 year olds.
Hargett asks what happens if it works, not why it won't. Pricing norms from other products, like weather apps, may not apply to a new AI product.
Bauman wants a repeatable use case that is core to identity. He points to Ladder, AllTrails and Strava as apps tied to who people are and to a repeated action. Recording lectures happens daily or a few times a week.
Notes pile up over time, such as physics 1, 2 and 3, which locks users in. The growing corpus is strong for retention.
Without a deep moat, copycats arrive within days. Lower barriers to building software mean a hit can get a hundred copies within a week. Without a moat, the team's ability to ship wow products is the main growth engine.
The seven powers include network effects, cornered resources and brand. Quizlet's brand, built over almost 20 years, is one such moat. Clones of Coconote were treated as possible lead gen, since users try the cheap one and may come back.
Bauman slept on the first inbound call and argued to take it. Quizlet reached out when Coconote was only a couple of months old. Hargett's first instinct was to stay heads down, and Bauman came back wanting to take the call.
Hargett's doubt was what could possibly come of that. Most inbound talks lead nowhere, so take the call only for a company you admire.
They hired an investment bank so they could keep building. Chris Park of Creative Partners ran the process from early talks through close. They advise asking a buyer for a ballpark range after a few calls and moving on if it is off.
An M&A process pulls attention from customers, building and marketing, and losing focus shows in negotiations. Hargett called the banker "our third co-founder a little bit".
The sale took about a year while revenue roughly doubled. The process ran in phases through the year, mostly waiting, and the deal closed in December. One telling puts the exit about 18 months after launch and another about two years from founding.
Only the two founders knew how far talks had gone. Engineers and creators learned on the day of close, on the advice that a great leader shelters other people.
Quizlet offered scale and patience that a bootstrapped company lacked. Quizlet's user base is an order of magnitude larger, and its finances allow bigger bets such as a media arm. Both founders are staying.
Bauman says Quizlet wants to build something similar to the founders' vision. Coconote's mission is to give learners superpowers by tailoring foundation models for learners.
Bauman now runs paywall experiments at Quizlet scale. He works on Coconote engineering and on subscription growth at Quizlet, and also with Cram. He says Quizlet is one of the biggest premium consumer apps.
At that scale a single paywall experiment can add a million dollars of revenue a year. He is looking for an iOS or Android engineer who enjoys running them.
The next target is bringing the cancel flow to Apple payments. The trial-extension flow runs on web and in the app for Stripe subscribers through a web view. Bringing it to Apple payments is harder but the stated next goal.
Apple's own retention-offer feature is in limited beta, and Hargett thinks it supports only discounts, not extra trial time.