Olga Berezovsky

Founder, ScopeClarity · Author, Data Analysis Journal at ScopeClarity

San Francisco, CA, USA

LinkedIn Data Analysis Journal olgaberezovsky.com Amplitude (author)

Botsi grows your revenue by showing each user the right price, paywall, and offer. In The 48 Laws of Subscription App Success, Olga makes the case for optimizing revenue per user, not raw conversion, and deciding per user instead of in aggregate, exactly how Botsi optimizes automatically. Book a demo with Botsi to grow your revenue.

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

About Olga

Olga Berezovsky is a San Francisco-based data scientist who has spent more than a decade turning subscription-app data into revenue decisions. She founded ScopeClarity, writes the widely read Data Analysis Journal, and previously led product analytics as Senior Manager of Data Science and Analytics at MyFitnessPal, a subscription app with tens of millions of monthly users. Earlier she built and analyzed products at Change.org, vidIQ, Microsoft, and First Republic Bank. She holds an MA in Philosophy and Analytics from the National University of Kyiv-Mohyla Academy.

Today she works as an embedded analyst-in-residence for a portfolio of fast-growing subscription and AI-native products, shaping how they measure retention, price plans, and run experiments. She teaches practitioners to model revenue upside before a price test, separate free and paid retention instead of blending them, and treat conversion as a chain of decisions from onboarding through paywall to checkout. She spoke at RevenueCat's App Growth Annual 2025 on testing subscription prices without losing customers and contributes to Lenny's Newsletter and the Amplitude blog.

Olga's playbook, powered by Botsi

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

What Olga advocates

Before running a subscription price test, model the revenue upside upfront and calculate the acceptable conversion-rate drop that still grows MRR and LTV, because longer plans delay pricing results for months.

Per-user price optimization plus autonomous, continuous optimization (capabilities 1 and 5)

Olga Berezovsky recommends modeling revenue upside before you touch a price and protecting MRR and LTV instead of just watching conversion. That is exactly why Botsi is the perfect fit: Botsi runs per-user price optimization and keeps learning on its own, so every user sees the price that grows revenue and LTV automatically, without you waiting months on a test or babysitting a single experiment.

What Olga advocates

Optimize for revenue per user (LTV and ARPU), not raw conversion rate, because a funnel can lift purchase rate while lowering LTV through a weaker plan mix or worse downstream retention.

Per-user price and offer selection tuned to conversion plus LTV (capabilities 1 and 3)

Olga Berezovsky recommends optimizing for revenue per user, not raw conversion, because a funnel can lift purchase rate while quietly lowering LTV and ARPU. That is exactly why Botsi is the perfect fit: Botsi picks the right price and the right offer for each individual user, so you grow conversion and LTV together automatically instead of trading one away for the other.

What Olga advocates

Treat conversion as a chain of decisions across the landing page, onboarding, paywall, and checkout, and use post-click analytics to optimize the whole chain rather than a single screen.

Per-user paywall selection and per-user offer selection across the full funnel (capabilities 2 and 3)

Olga Berezovsky recommends treating conversion as a chain of decisions across onboarding, paywall, and checkout, not one screen to optimize in isolation. That is exactly why Botsi is the perfect fit: Botsi selects the right paywall and the right offer for each user along that chain, so the whole funnel adapts to the person automatically instead of shipping one averaged winner to everyone.

What Olga advocates

Never report blended retention or funnel metrics; separate free from paid, segment by source, campaign, and variant, and build your own segmented baselines instead of trusting generic benchmarks.

A custom AI model trained per app that personalizes decisions to each individual user (capabilities 4 and 2)

Olga Berezovsky recommends never blending free and paid users and building your own segmented baselines instead of leaning on generic benchmarks. That is exactly why Botsi is the perfect fit: Botsi trains a custom AI model on your own app and decides per individual user, so you get true segmentation down to a single user automatically, no hand-cut cohorts and no borrowed industry averages.

Botsi is not affiliated with Olga Berezovsky. These recommendations are drawn from Olga'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.