Why Your 'Correct' Discovery Method Might Be Wrong

​Dear Reader,​

"Which experiment should we run next?"

This question comes up in almost every Discovery coaching session I facilitate. Teams often focus on finding the methodologically perfect way to test their assumptions. But here's the thing: the most technically correct experiment isn't always the right one to run.

When choosing methods for Product Discovery, we often focus on what fits our research question or assumption best. Say you want to understand how users perceive features in your product.

A diary study might be the perfect method—capturing real usage patterns over time. But what if it takes three months to get reliable insights? A series of well-structured interviews or shadowing sessions might get you 80% of the way there in just two weeks.

Several factors determine your lead time to insight:

• Your team's skills and capabilities
• Industry context and constraints
• Available infrastructure
• Customer interaction patterns
• Product characteristics

Here's another way to think about it: An A/B test might seem quick to start—taking just hours or days to implement. But depending on your traffic and conversion rates, it could take weeks or months to reach statistical significance. In contrast, while recruiting participants for qualitative interviews might take two weeks, you could have reliable insights within days of completing them.

Neither method is inherently better. What matters is the total time to reliable insight, not just how quickly you can get started.

So, when picking your next Discovery priority, ask yourself:

1. How well does the method answer our research question?
2. How technically correct is the method for our needs?
3. What's our lead time to the next viable insight?

Here's a practical tip: When evaluating lead time, avoid abstract scoring systems. Instead, estimate the actual duration by adding:

• Setup time (recruiting, preparation)
• Execution time (running the experiment)
• Synthesis time (analyzing and learning)

This concrete timeline helps you make practical trade-offs between methods.

Remember: The goal isn't to achieve perfect certainty. It's to reduce uncertainty enough to make confident decisions about what to build next.

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Thank you for Practicing Product,

​Tim​

Good News!

Some last tickets are available for my in-person Product Discovery workshop on March 10 in London (as part of Mind the Product conference).

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Who is Tim Herbig?

As a Product Management Coach, I guide Product Teams to measure the real progress of their evidence-informed decisions.

I focus on better practices to connect the dots of Product Strategy, Product OKRs, and Product Discovery.