Vahe Baghdasaryan

Founder & CEO, Tangent (a Superwall company) at Tangent, a Superwall company

New York, NY, USAAlso known as Vahe Bagdasaryan

LinkedIn X (@vahebagdasar)Maven course RevenueCat (author)Superwall acquires Tangent

Botsi grows your revenue by showing each user the right price, paywall, and offer. In The 48 Laws of Subscription App Success, Vahe makes the case for shaping the price and paywall around each user at the decision moment, exactly what Botsi automates for every visitor. Book a demo with Botsi to grow your revenue.

Botsi is not affiliated with Vahe Baghdasaryan. This profile maps Vahe's public playbook to what Botsi does.

About Vahe

Vahe Baghdasaryan founded Tangent, a paywall-design and revenue-intelligence consultancy for subscription mobile apps that Superwall acquired in 2025 alongside a $7.5M raise. He built it the hard way, starting as a solo operation called Paywalls Design that charged a few hundred dollars per paywall and posted the results publicly on X, then grew it into a seven-figure, 20-person firm. By its own account Tangent has run more than 5,000 experiments and designed over 20,000 paywalls across 100-plus apps, work it credits with $50M+ in added revenue and typical ARPU lifts of 30 to 40 percent within three months, for clients including Cal AI, ElevenLabs, Elevate, Hallow, and NGL.

He also works as a Growth Manager at Flo Health and previously ran growth and monetization at CoinStats, where he reports growing daily revenue 113 percent and trial signups 87 percent, after starting his career as a product marketer at Sololearn. He writes on paywalls, pricing, and lifecycle marketing for the RevenueCat blog, teaches a Maven cohort course on Subscription Optimization and Pricing Strategy, mentors on GrowthMentor, and speaks at MAU Vegas, App Promotion Summit, Business of Apps, and RAGA. Across all of it he keeps circling one question: what actually makes an individual user decide a subscription is worth paying for.

Vahe's playbook, powered by Botsi

Here is what Vahe publicly advocates, and the Botsi capability that delivers it for every individual user.

What Vahe advocates

Use deliberate price anchoring on paywalls (display savings prominently, break annual plans into weekly or daily equivalents, and lead with weekly pricing so the annual plan reads as the value choice) to frame perceived value at the decision moment.

Per-user AI price optimization

Vahe Baghdasaryan recommends anchoring price so the right plan feels like the obvious value at the exact moment someone decides. That is exactly why Botsi is the perfect fit. Botsi runs per-user price optimization, so instead of picking one anchor for the whole audience, it shows each individual the price and framing most likely to convert them and grow their lifetime value, automatically. You get Vahe's anchoring instinct applied to every single user, not just the average one.

What Vahe advocates

Sweat the overlooked paywall details (purposeful animations, jargon-free outcome-focused copy, social proof first, prominent free-trial messaging) and cut plan options to reduce decision fatigue, instead of copying whatever paywall is trending.

Per-user AI paywall selection

Vahe Baghdasaryan recommends sweating the paywall details and showing each user a focused, low-friction paywall rather than one crowded template built for everyone. That is exactly why Botsi is the perfect fit. Botsi runs per-user paywall selection, picking the paywall most likely to convert each individual instead of the variant that merely wins on average. You get Vahe's core principle, that the right paywall depends on the user, applied automatically to every visitor.

What Vahe advocates

Build segmented lifecycle win-back campaigns for canceled, expired, and canceled-trial users, escalating from full-price resubscription to progressive, personalized offers that match where each user actually sits in their lifecycle, and tie every discount to a reason so it feels earned rather than training users to wait for a sale.

Per-user AI offer selection plus autonomous continuous optimization

Vahe Baghdasaryan recommends winning users back with disciplined, segmented offers that escalate to fit each user and never hand a discount to someone who did not need one. That is exactly why Botsi is the perfect fit. Botsi runs per-user offer selection and keeps learning autonomously, so the right trial, bundle, or discount reaches the right lapsed or hesitant user without you hand-building and babysitting each campaign. You get Vahe's segmented lifecycle strategy running continuously in the background, with your margin protected user by user.

What Vahe advocates

Research your own users and understand your specific audience before running paywall tests, instead of copying popular tactics, then tailor experiments to your app and test rigorously.

Custom AI model trained per app plus autonomous continuous experimentation

Vahe Baghdasaryan recommends studying your own users before you test, because someone else's winning paywall rarely wins for a different audience. That is exactly why Botsi is the perfect fit. Botsi trains a custom AI model on your app's own data and keeps experimenting autonomously, so every price, paywall, and offer decision is grounded in how your users actually behave rather than a generic playbook. You get Vahe's research-first, audience-specific discipline built into the model itself, with no manual A/B test babysitting.

Botsi is not affiliated with Vahe Baghdasaryan. These recommendations are drawn from Vahe's public talks, writing, and interviews and mapped to what Botsi does. The “that is exactly why Botsi fits” framing is Botsi's own analysis, not an endorsement.