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Büşra Coşkuner | How I Test B2B vs B2C
AI has made building cheap.
The cost of being wrong is still expensive.
I help organizations make better AI and growth investment decisions before committing major capital.
→ Book a Growth Strategy Call at Precoil.com/EMT
Summary
In this episode, I’m joined by Büşra Coşkuner, a product management coach and trainer who helps teams move from project thinking to product thinking.
We explore how she approaches product discovery and testing. From building zero-to-one products at Doodle to coaching teams across B2B and B2C environments, Büşra shares how to actually operationalize experimentation beyond just A/B tests.
We also dig into how to test when you don’t have much data, how to combine qualitative and quantitative insights, and why many teams get stuck thinking they’re doing product work when they’re really just managing tickets.
If you’re trying to build a stronger testing culture or just want to make better decisions this episode will challenge how you think about product metrics and experimentation.
Takeaways
- Product transformation is a leadership decision - If leadership isn’t backing the shift from projects to products, it won’t happen, bottom-up enthusiasm isn’t enough.
- Most “product orgs” aren’t actually product orgs - Adopting Scrum and calling someone a product owner doesn’t mean you’re doing product, many teams are still just managing tickets.
- You can’t test what you can’t measure - Without proper data instrumentation, teams fall into a “build, build, build” loop instead of build–measure–learn.
- Metrics frameworks are a starting point, not the system - Pirate metrics (AARRR) or customer factory models help, but real insight comes from adapting them to your actual business model.
- Qualitative data is not optional - Quant tells you what is happening, qual tells you why. In low-data environments, qual becomes your primary signal.
- “No data” is usually an excuse - Even in B2B, you can extract directional insights, from sales teams, customer conversations, and patterns across feedback.
- A/B testing is over-indexed and often misused - Experimentation goes beyond A/B testing. Many teams default to it even when it’s impractical or irrelevant.
- Sometimes building is the test - For low-risk features, the fastest way to learn is to ship and observe behavior, treat the release itself as the experiment.
- B2B testing requires creativity, not scale - From sales-assisted experiments to prototype validation and even WhatsApp groups, testing in small markets is possible if you rethink the approach.
- AI changes the cost of being wrong - When building becomes cheap, you don’t always need heavy upfront validation, you can test the problem through the solution, as long as you’re willing to kill what doesn’t work.
Guest Links
LinkedIn: https://www.linkedin.com/in/busra-coskuner/
Website: https://busra.co/
View all episodes
By David J BlandAI has made building cheap.
The cost of being wrong is still expensive.
I help organizations make better AI and growth investment decisions before committing major capital.
→ Book a Growth Strategy Call at Precoil.com/EMT
Summary
In this episode, I’m joined by Büşra Coşkuner, a product management coach and trainer who helps teams move from project thinking to product thinking.
We explore how she approaches product discovery and testing. From building zero-to-one products at Doodle to coaching teams across B2B and B2C environments, Büşra shares how to actually operationalize experimentation beyond just A/B tests.
We also dig into how to test when you don’t have much data, how to combine qualitative and quantitative insights, and why many teams get stuck thinking they’re doing product work when they’re really just managing tickets.
If you’re trying to build a stronger testing culture or just want to make better decisions this episode will challenge how you think about product metrics and experimentation.
Takeaways
- Product transformation is a leadership decision - If leadership isn’t backing the shift from projects to products, it won’t happen, bottom-up enthusiasm isn’t enough.
- Most “product orgs” aren’t actually product orgs - Adopting Scrum and calling someone a product owner doesn’t mean you’re doing product, many teams are still just managing tickets.
- You can’t test what you can’t measure - Without proper data instrumentation, teams fall into a “build, build, build” loop instead of build–measure–learn.
- Metrics frameworks are a starting point, not the system - Pirate metrics (AARRR) or customer factory models help, but real insight comes from adapting them to your actual business model.
- Qualitative data is not optional - Quant tells you what is happening, qual tells you why. In low-data environments, qual becomes your primary signal.
- “No data” is usually an excuse - Even in B2B, you can extract directional insights, from sales teams, customer conversations, and patterns across feedback.
- A/B testing is over-indexed and often misused - Experimentation goes beyond A/B testing. Many teams default to it even when it’s impractical or irrelevant.
- Sometimes building is the test - For low-risk features, the fastest way to learn is to ship and observe behavior, treat the release itself as the experiment.
- B2B testing requires creativity, not scale - From sales-assisted experiments to prototype validation and even WhatsApp groups, testing in small markets is possible if you rethink the approach.
- AI changes the cost of being wrong - When building becomes cheap, you don’t always need heavy upfront validation, you can test the problem through the solution, as long as you’re willing to kill what doesn’t work.
Guest Links
LinkedIn: https://www.linkedin.com/in/busra-coskuner/
Website: https://busra.co/