Analyze Product Data in Claude Code

Hosted by Shane Butler, Hai Guan, and Sravya Madipalli

Wed, Mar 18, 2026

7:00 PM UTC (1 hour)

Virtual (Zoom)

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AI Analytics for Builders
Shane Butler, Sravya Madipalli, and Hai Guan
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What you'll learn

Run a deep dive analysis in Claude Code

Analyze conversion or retention by segment, spot where drop-offs happen, and quantify where impact is coming from.

Validate results and catch common AI analysis errors

Pressure-test the analysis with sanity checks and sensitivity cuts so conclusions hold up in reviews.

Turn findings into a clear product recommendation

Translate the analysis into structured presentation of “what changed, why, who it affects, and what we should do next”.

Why this topic matters

Product development teams move fastest when they can answer questions with evidence, not opinions. Too often, analysis stalls in messy definitions, inconsistent segments, or results that do not survive scrutiny. Claude Code can massively accelerate execution, but only if the workflow includes validation. This lesson shows an end-to-end product analysis deep dive you can reuse yourself.

You'll learn from

Shane Butler

Principal Data Scientist at Ontra

Shane Butler is a Principal Data Scientist at Ontra, where he leads evaluation strategy for AI product development in the legal tech domain. He has more than ten years of experience in product data science and causal inference, with prior roles at Stripe, Nextdoor, and PwC. Shane is also the co-host of the AI podcast Data Neighbor, where he interviews product, data, and engineering leaders who are pioneering the next generation of data science and analytics in an AI-driven landscape.

Hai Guan

Head of Data at Ontra

Hai Guan leads the data organization at Ontra, the leading legal tech AI solutions for private markets. He previously led Data Science & Analytics at LinkedIn, Nextdoor, Pinterest, and Meta. He's spent a decade teaching product development teams how to ask questions that actually drive decisions—and now teaches how to combine that judgment with AI to move 10x faster.

Sravya Madipalli

Senior Manager, Data Science @Superhuman (Prev. Grammarly)| Ex-Microsoft

Sravya Madipalli is a Senior Manager of Data Science with 14+ years of experience helping teams make better decisions with data. She has built and led data science and product analytics teams at Microsoft, eBay, Nextdoor, and Superhuman (prev. Grammarly), working closely with product, engineering, marketing, and leadership. Her expertise spans experimentation, metrics design, modeling, analytics, and translating complex user behavior into clear, actionable insights.

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