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Crush (formerly TBH)

by Nikita Biervia My First Million
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Nikita Bier had already proven himself a viral app wizard. His previous app TBH—which let high school students answer anonymous superlatives-style questions about their peers ("Who has the best smile?" "Who would you trust to bail you out of jail?")—had gone massively viral and gotten acquired by Facebook for between $40-100 million. After a five-year non-compete period ended, Nikita decided it was time to strike again. In a group chat with friends, he made an audacious declaration: "I'm just thinking about how I can make $10 million in three months."

Instead of chasing retention and building the next Snapchat like he'd been pressured to do at Facebook, Nikita had learned a different lesson. He realized the superlatives format itself was the magic—people are obsessed with themselves and what others think of them. So he decided to launch TBH 2.0, but this time with a crucial difference: a paywall. The hook would be simple and powerful: pay $6.99 per week (roughly $28/month, or double Netflix's price) to see who voted for you.

Building the First Version

Nikita set up a lean operation: four engineers living in his LA house. Instead of building a nationwide app, he employed a hyper-targeted playbook he'd actually documented in a memo at Facebook about how to launch social apps effectively. The key insight: high schools are perfect Petri dishes. In a school of ~2,000 students, most know each other or know of each other. You can test, tweak, and iterate in one cohesive network before scaling.

He started with a surgical strike into three high schools in Georgia, geofencing the app so it was only available in those specific locations. To drive adoption, he used a clever Instagram strategy: create accounts like "crush_archelagohs2022" (combining the app name with the high school), follow every kid who had that class year in their bio, keep the account private, then—right at 4 PM on launch day when kids get out of school—accept all pending follow requests at once. The notification flood drives them to check the account bio, which says "Download the app, see who likes you." It's psychological theater.

He communicated progress like a tactician: "Now we're adding a thousand people an hour." He used academic language about "K-factor" and "density coefficient," hiding the app in the Games/Puzzles category to avoid competition until hitting the "switch."

Finding the First Customers

The app worked. It went viral within the high schools, exactly as planned. Users loved it—the basic app was free, but the friction of curiosity about who voted for you was irresistible to teenagers. Conversion to the $28/month subscription tier seemed viable. The math was seductive: if you achieve 4% conversion across Georgia's high schools (~1.8 million students), you'd hit $1.8 million a month in revenue from a single state.

But within about two weeks, things started to unravel. Rumors spread on social media that the app was being used for human trafficking or abuse. A TikTok video went viral claiming misuse. Whether the rumors had substance or not didn't matter—app store algorithms started surfacing negative reviews. Apple took notice. The app got flagged and removed from the App Store.

What Worked (and What Didn't)

What worked: the core mechanic. The viral loop was airtight. The geofenced high school strategy was genius—it created a contained network where the app could dominate.

What didn't: brand perception and context. The TBH name had baggage from the previous iteration, which people also associated with potential abuse. So Nikita pivoted, rebranding as "Crush"—a name that, ironically, looked exactly like the orange Crush soda logo. It was so effective that people watching the demo got thirsty. The rebrand worked from a design perspective but didn't solve the perception problem long-term.

He relaunched in Alabama instead, using the same high-school-by-high-school playbook. But the cycle seemed destined to repeat: grow viral within a network, attract the wrong kind of attention, face pressure from app store gatekeepers, rebrand and move on.

Where They Are Now

The story cuts off here, but what's remarkable is the pattern. Nikita proved he could repeat the viral formula—it wasn't a fluke with TBH. He built a repeatable system for seeding apps within bounded networks and achieving rapid organic growth. The challenge isn't virality; it's sustainabilty and context. A quiz app that lets teenagers anonymously rate each other will always live on the edge of misuse accusations, regardless of intent. Nikita's ability to launch, pivot, and relaunch quickly is formidable, but whether the $10-million-in-90-days target was ever achievable given the regulatory and reputational headwinds remains unclear.

Why It Worked
  • Nikita leveraged deep pattern recognition from a previous viral success to identify that the superlatives mechanic itself—not the broader social platform—was the core driver of engagement, allowing him to rebuild around the proven psychological hook rather than chasing feature bloat.
  • By geofencing the launch to three high schools in Georgia, he created an isolated network effect where the app's value (seeing who voted for you) compounds fastest, enabling rapid iteration and testing before scaling to markets where density couldn't be controlled.
  • The Instagram account strategy ($28/month paywall targeting teenagers' fundamental psychology around peer validation) combined psychological timing (4 PM school dismissal notification floods) with distribution precision, converting organic curiosity into acquisition without competing on app store visibility.
  • Nikita's previous five-year non-compete forced a deliberate restart with documented playbooks and lean infrastructure (four engineers), eliminating the temptation to over-build and allowing him to execute with the discipline of someone who had already succeeded once at scale.
How to Replicate
  • 1.Document the core mechanic from your previous successful product or from existing tools that frustrate users, then isolate what specific behavior drives engagement, rather than rebuilding the entire feature set.
  • 2.Identify a geographically or socially bounded network (like three high schools or a single university) where you can achieve 30%+ saturation before scaling, and use density as your testing variable instead of national launches.
  • 3.Create targeted social accounts (e.g., [app_name]_[specific_community_identifier]) that follow potential users by matching their profile attributes, then trigger mass-notification events (like simultaneous follow-back) during predictable behavior windows (school dismissal, lunch breaks) to drive app discovery.
  • 4.Set a subscription paywall that exploits a known psychological vulnerability in your target demographic (curiosity, social validation, FOMO) at a price point that tests conversion before optimizing, and hide the app in a non-obvious category until product-market fit is confirmed.

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