Dan Vykhopen - This app makes $2m/year using this ridiculously easy strategy

Before building, Dan posted the idea (use AI to fill out job applications) on LinkedIn as 'Hey, if I built this tool, would anyone want it?' with only ~500 connections, without sharing it with anyone.

During the ~2 months of building, Dan kept posting on LinkedIn (e.g. 'here are the top 200 companies hiring now') to collect emails, plus some UGC posts driving to the site, and Typeform surveys. Inspired by Tabs' UGC.

After the waitlist flopped, weeks of guerrilla marketing: a big push on Hacker News, manually scraping emails and posts, and reaching out with heartfelt messages ('Hey, I think you should use this'). Continued manual grinding from April to December with two people.

Uses 'Tinder for jobs' in content and creator outreach instead of 'your job search on autopilot' or 'use AI to fill out job applications', because people get it instantly.

Early on, with few viral videos, check Stripe or RevenueCat when a video takes off to see whether it converts; Dan watched conversions live as one video's views grew. Build this muscle before scaling to multiple videos per day, when attribution gets muddy.

Ran skit videos targeting college students. Skits don't target the problem well enough, and college students don't care about internships or job applications and won't pay for job search.

Same video concept, different platform name in the hook. 'Stop using LinkedIn to apply to jobs' reaches white-collar workers who apply to hundreds of jobs and will pay to automate it. 'Stop using Indeed' / 'Who's still using Indeed?' reaches blue-collar workers who get interviews easily and flood the comments with hate about paying to apply. Read the comments to tell whether you hit the right audience.

On organic, don't experiment much: ~80% of videos replicate formats that have already gone viral (in your own way), ~20% net-new. Look for formats that go viral consistently across accounts and verticals (e.g. competitor Sorce's 'Career Dave' discovery style, copied by a dozen-plus accounts). Break down why it works, find UGC creators who understand it, coach them, and have them keep pumping it for weeks. Never copy word for word.

After running a UGC program for about a year, Dan restarted it with new energy. Within ~4 days it produced an 11M-view video, but the program needs heavy management and fizzled. To scale the format he'd need 200-400 creators doing the same style, so he considers UGC not scalable for Massive and prefers paid ads for conversion data.

Scaled the influencer and UGC side and tested lots of new content, scaling up what got views and what they thought converted, from ~500K to 3-4M views/week.

Worked with influencers on a monthly retainer basis. The influencers' audiences weren't people actively applying for white-collar jobs.

Massive runs a hard paywall subscription. Pricing changes (not described) doubled revenue.

Dan prefers paid ads to UGC for a conversion-focused product because you pay for real data on what works and iterate much faster. Running ads 'in a specific way' (undisclosed) raised revenue 50%.

Dan says he 'ripped' Massive's onboarding from somewhere, as did another founder he asked; he argues the gains are in the ad creative, not onboarding or checkout polish.

Ads that call out a precise audience and symptom ('If you are running more than 10 mi and you have tight hips, here's why'), then present the solution. Several follow-up ads keep the same messaging with proof points, each probing for the viewer's pain point. Ads run for ~2 years. Checkout was so bad it took Dan 15 minutes and a switch to his computer.

Sorce's creator 'Career Dave' repeats one or two formats: a discovery-style video with his face and a friend's face in the hook and a moving camera, so it feels organic. Dozens of videos in this style now run on a dozen-plus accounts across apps.

Dupe's creator (Alyssa Home Finds) posted the discovery format for weeks at hundreds of views. When one hit 6,000 views she kept iterating on it for another ~4 weeks. Low-view versions felt inauthentic; the winners nailed the micro-expressions.

PrepAI copied viral videos of real people landing jobs or getting laid off word for word with actors, making it seem the creator landed a job, then converted in heavily moderated comments ('I got it from PrepAI', 'use my code'). Also copied Massive's onboarding, colors and buttons. Dan warns against it as illegal (FTC risk).

Headway (15-minute book summaries) grew on straight performance marketing and paid ads arbitrage while bootstrapped, pushing persistently despite not solving an obviously painful problem.

Neuro Gum has near in-house affiliates and UGC creators plus ~100,000 affiliates on TikTok Shop. Because the product is for everyone, they only need views, so paid matters less.

Masterschool launched 'Maestro', an AI-positioned funnel: users answer what they want to be (e.g. software engineer building next-gen apps) and every answer leads to applying to the bootcamp. Many get 100% scholarships (likely government-funded, Dan guesses), aimed at new vibe coders who want a real degree.

Minutes AI offers essentially the same AI note-taking product as student-focused apps like TurboLearn but targets an older audience.