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๐ŸŽ™๏ธ Speakers: Thomas Wiecki, Niall Oulton, Tim McWilliams, Carlos Trujillo, Kemble Fletcher, Evan Wimpey | โฐ Time: 16:00 UTC / 9:00 AM PT / 12:00 PM ET / 5:00 PM Berlin

Marketing measurement is evolving faster than most teams can keep up, and 2025 pushed every model, method, and assumption to its limits. With shifting budgets, new privacy pressures, and a market full of hype disguised as innovation, the real question is: what actually worked?

In this session, the PyMC Labs team opens the curtain on what we learned from working hands-on with some of the worldโ€™s leading brands, across MMM, CLV, forecasting, causal inference, generative AI, and fully custom Bayesian models. Instead of polished slides or scripted talking points, this roundtable is a guided, honest conversation about what this year revealed, and what 2026 will demand from marketing leaders.

Drawing from dozens of real client engagements, model builds, and experiments, youโ€™ll see how our team approached this yearโ€™s hardest measurement problems, where the industry is heading, and how to think more clearly about marketing effectiveness in a chaotic environment.

Youโ€™ll learn:

  • The biggest challenges brands faced in MMM, CLV, forecasting, and attribution in 2025.
  • The breakthroughs that actually moved the needle, and the ones that didnโ€™t.
  • What turned out to be genuine measurement trends vs. overhyped noise.
  • How Bayesian modeling helped solve problems traditional approaches couldnโ€™t.
  • The solutions, playbooks, and ideas our team used to drive meaningful decisions.
  • What 2026 will require from marketing measurement, experimentation, and strategy.

Join us for a sharp, candid, and practitioner-led discussion that surfaces the lessons, surprises, and strategies shaping smarter marketing decisions, not theory, but what weโ€™ve seen in the trenches.

๐Ÿ“œ Outline of Talk / Agenda:

  • 5 min: Introduction to PyMC Labs and speakers
  • 40 min: Panel discussion
  • 15 min: Q&A

๐Ÿ’ผ About the speakers:
Thomas Wiecki (Founder of PyMC Labs)
Dr. Thomas Wiecki is an author of PyMC, the leading platform for statistical data science. To help businesses solve some of their trickiest data science problems, he assembled a world-class team of Bayesian modelers and founded PyMC Labs -- the Bayesian consultancy. He did his PhD at Brown University studying cognitive neuroscience.
๐Ÿ”— Connect with Thomas:
๐Ÿ‘‰ Linkedin: https://www.linkedin.com/in/twiecki/
๐Ÿ‘‰ Website: https://www.pymc-labs.com/
https://twiecki.io/
๐Ÿ‘‰ GitHub: https://github.com/twiecki
๐Ÿ‘‰ Twitter: https://twitter.com/twiecki

Niall Oulton (Vice President of Sales - PyMC Labs)
Niall Oulton has built a reputation as a leading expert in the field of marketing analytics, with a specialization in Bayesian Marketing Mix Modelling. His career, spanning over a decade, has seen him on both sides of the business landscape - agency and client. His rich background provides him with a unique perspective, making him an expert in understanding and navigating the complexities of both worlds.

๐Ÿ”— Connect with Niall:
๐Ÿ‘‰ LinkedIn: https://www.linkedin.com/in/nialloulton20/
๐Ÿ‘‰ Twitter: https://twitter.com/niall20
๐Ÿ‘‰ GitHub: https://github.com/nialloulton
๐Ÿ‘‰ Website: https://1749.io/

Tim McWilliams (Principal Data Scientist - PyMC Labs)
With over 7 years of experience in the marketing mix modeling and marketing analytics space, Tim specializes in applying Bayesian modeling techniques to solve complex business challenges and uncover actionable insights. Passionate about bridging advanced statistical methods with real-world marketing strategy, he has worked across diverse industries to optimize media investments and measure impact.

๐Ÿ”— Connect with Tim:
๐Ÿ‘‰ LinkedIn: https://www.linkedin.com/in/tim-mcwilliams-a4b647b3/
๐Ÿ‘‰ Github: https://github.com/timbo112711

Kemble Fletcher (Director of Product Development - PyMC Labs)
Before joining PyMC Labs, Kemble co-founded SweepLift and co-invented its patent-pending in-stream survey and measurement technology. He later led omnichannel attribution and measurement strategy at Google for its top 300 global clients, influencing $2B in ARR. Prior to that, he drove digital analytics and predictive modeling at OMD for brands like Leviโ€™s, Hilton, and eHarmony. He also advises SaaS and start-up leaders on data architecture, attribution, and growth. At PyMC Labs, Kemble helps organizations solve complex challenges through advanced Bayesian modeling.

๐Ÿ”— Connect with Kemble:
๐Ÿ‘‰ LinkedIn: https://www.linkedin.com/in/kemblefletcher/

Carlos Trujillo (Principal Data Scientist - PyMC Labs)
Carlos is a Marketing Scientist passionate about using data and AI to turn marketing strategy into measurable results. Heโ€™s worked with teams across Latin America, Europe, and Africa, including roles at Wise, Bolt, and Omnicom Media Group. As a core member of PyMC Labs, he contributes to open-source projects like PyMC-Marketing, blending statistical rigor with practical marketing insight.

๐Ÿ”— Connect with Carlos:
๐Ÿ‘‰ LinkedIn: https://www.linkedin.com/in/cetagostini/
๐Ÿ‘‰ Github: https://github.com/cetagostini

๐Ÿ’ผ About the Host:
Evan Wimpey (Director of Analytics at PyMC Labs)
Evan helps clients design Bayesian solutions tailored to their goals, ensuring they understand both the how and why of inference. With masterโ€™s degrees in Economics and Analytics, he focuses on delivering clear value throughout projects and brings a unique twist with his background in data comedy.
๐Ÿ”— Connect with Evan:
๐Ÿ‘‰ Linkedin: https://www.linkedin.com/in/evan-wimpey/
๐Ÿ‘‰ GitHub: https://github.com/ewimpey

๐Ÿ“– Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.

๐Ÿ”— Connecting with PyMC Labs:
๐ŸŒ Website: https://www.pymc-labs.com/
๐Ÿ‘ฅ LinkedIn: https://www.linkedin.com/company/pymc-labs/
๐Ÿฆ Twitter: https://twitter.com/pymc_labs
๐ŸŽฅ YouTube: https://www.youtube.com/c/PyMCLabs
๐Ÿค Meetup: https://www.meetup.com/pymc-labs-online-meetup/
๐ŸŽฎ Discord: https://discord.gg/mTc64cAz

Artificial Intelligence
Data Science
Business Intelligence & Data Warehousing
Marketing Strategy
Bayesian Statistics

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