talk-data.com

🎙️ Speakers: Thomas Wiecki, Niall Oulton, Tim McWilliams, Carlos Trujillo, Kemble Fletcher, Evan Wimpey \| ⏰ 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 world’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, you’ll see how our team approached this year’s hardest measurement problems, where the industry is heading, and how to think more clearly about marketing effectiveness in a chaotic environment.

You’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 didn’t.
• What turned out to be genuine measurement trends vs. overhyped noise.
• How Bayesian modeling helped solve problems traditional approaches couldn’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 we’ve seen in the trenches.

📜 Outline of Talk / Agenda:

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

💼 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. 🔗 Connect with Thomas: 👉 Linkedin: https://www.linkedin.com/in/twiecki/ 👉 Website: https://www.pymc-labs.com/ https://twiecki.io/ 👉 GitHub: https://github.com/twiecki 👉 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.

🔗 Connect with Niall: 👉 LinkedIn: https://www.linkedin.com/in/nialloulton20/ 👉 Twitter: https://twitter.com/niall20 👉 GitHub: https://github.com/nialloulton 👉 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.

🔗 Connect with Tim: 👉 LinkedIn: https://www.linkedin.com/in/tim-mcwilliams-a4b647b3/ 👉 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 Levi’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.

🔗 Connect with Kemble: 👉 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. He’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.

🔗 Connect with Carlos: 👉 LinkedIn: https://www.linkedin.com/in/cetagostini/ 👉 Github: https://github.com/cetagostini

💼 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 master’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. 🔗 Connect with Evan: 👉 Linkedin: https://www.linkedin.com/in/evan-wimpey/ 👉 GitHub: https://github.com/ewimpey

📖 Code of Conduct: Please note that participants are expected to abide by PyMC's Code of Conduct.

🔗 Connecting with PyMC Labs: 🌐 Website: https://www.pymc-labs.com/ 👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/ 🐦 Twitter: https://twitter.com/pymc_labs 🎥 YouTube: https://www.youtube.com/c/PyMCLabs 🤝 Meetup: https://www.meetup.com/pymc-labs-online-meetup/ 🎮 Discord: https://discord.gg/mTc64cAz

Can algorithms help you find love? Many happy couples successfully brought together via online dating websites show us that data science can help you find love. I'm joined this week by Thomas Levi, Senior Data Scientist at Plenty of Fish, to discuss some of his work which helps people find one another as efficiently as possible. Matchmaking is a truly non-trivial problem, and one that's dynamically changing all the time as new users join and leave the "pool of fish". This episode explores the aspects of what makes this a tough problem and some of the ways POF has been successfully using data science to solve it, and continues to try to innovate with new techniques like interest matching. For his benevolent references, Thomas suggests readers check out All of Statistics as well as the caret library for R. And for a self serving recommendation, follow him on twitter (@tslevi) or connect with Thomas Levi on Linkedin.