Second- and third-order effects on retention

What if you could know whether your product change was going to work — before a single real user ever saw it?

In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Tom Charman, co-founder of Blok, a synthetic user simulation platform that lets product teams test interfaces, onboarding flows, and product changes against AI-powered behavioral personas, not just to predict conversion, but to model second and third order effects like churn, confusion, and long-term retention. Tom opens by naming what’s changed: shipping is faster than ever, but the tools PMs use to decide what to build haven’t kept up. AB tests still take two to three weeks. Traditional user research still skews toward power users. And as personalization gets more complex, getting to statistical significance gets harder. That’s the gap Blok is trying to close.

They explore how Blok’s behavioral personas go beyond demographics to model psychographics, emotional state, and memory, including what happens when a user has a bad first experience and comes back to your product skeptical. Tom walks through the ICP trap that kills retention, why the “show don’t tell” principle protects against confirmation bias, and why he thinks the biggest shift happening in product right now is the move from reactive to proactive, replacing AB tests and feature flags with pre-ship simulation that gets you to directional confidence in 12 minutes instead of three weeks.

If you’re a PM tired of going to battle in product reviews without data to back your intuition, a founder trying to understand how synthetic users actually work and whether they’re worth it before Series A, or a product leader looking to understand how the entire feedback loop from idea to deployment is about to be rebuilt, this episode is for you.

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In this episode, we covered the following topics:

* (01:40) Why PMs are becoming the bottleneck: shipping is fast, deciding what to ship isn’t

* (04:00) The two problems with traditional user research: paid participants and sampling bias

* (08:19) Ben’s summary of Blok: how synthetic users work at a high level

* (11:04) Tom’s “show don’t tell” principle and how Blok actually simulates behavior vs. just asking questions

* (13:32) The four layers of a behavioral persona: demographics, psychographics, emotion, and memory

* (16:21) The anxious user example: how emotional state changes conversion behavior step by step

* (20:00) Second and third order effects: why optimizing conversion can quietly kill retention

* (21:52) The ICP trap: why the lower-converting variant might actually be the right call

* (28:05) The agentic loop: how the full product development stack is being rebuilt

* (33:27) Confirmation bias: how Blok’s chat interface helps remove it from the experiment design

* (42:19) Who should be using this: Tom’s honest answer on post-Series A timing

* (46:26) Scrappy alternative vs. Blok: 30–60% accuracy with Claude versus 87% with purpose-built models

* (53:15) How to build trust with skeptical stakeholders: run Blok alongside a real AB test

* (55:41) The biggest shift in product: proactive vs. reactive, and why feature flags may become obsolete

* (58:53) Where to find Tom and how to be helpful to Blok

* (01:00:48) Gratitude Corner: Olivia (co-founder), the team, and investors Hannah, Ashkan, Marlon, Kevin, and Brendan

* And more!

Links:

* Blok: https://www.joinblok.co/

* Tom Charman: https://www.linkedin.com/in/tcharman/

* Olivia Higgs (Tom’s Co-founder): https://www.linkedin.com/in/oliviahiggs/

* Hannah Chelkowski: https://www.linkedin.com/in/hannahchelkowski/

* Ashkan Mizani: https://www.linkedin.com/in/ashkanmizani/

* Marlon Nichols: https://www.linkedin.com/in/marloncnichols/

* Kevin Novak: https://www.linkedin.com/in/novakkm/

* Brendan Baker: https://www.linkedin.com/in/brendanbaker/

* Chris Neumann: https://www.linkedin.com/in/ckneumann/

* Marc: https://www.linkedin.com/in/marcbaselga/

* Ben: https://www.linkedin.com/in/benerez/

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