Measure Up

There's often a "human API" bottleneck when implementing marketing mix models in a business. What if AI agents could help?

That's what we talked about with Dr. Luca Fiaschi, partner at PyMC Labs. 

Find out how agents can support the full MMM chain - data consolidation and validation, model building with priors and business knowledge, deployment and retraining pipelines, and interactive Q&A for scenario planning - shifting data scientists toward designing agent workflows and guardrails rather than manual iteration. 

Learn how Skills files can improve coding-agent correctness, token-cost and vendor lock-in concerns. And find out what PyMC Labs is cooking up with their open-source “Decision AI” stack (Decision Hub, Decision Lab, Decision Lens).

Links from the show:

Decision AI Discord Server

discourse.pymc.io

00:00 Cold Open and Agents Joke

01:17 Meet Dr Luca Fiaschi

03:51 What Is Agentic MMM

06:11 Agents Across MMM Workflow

09:16 Do We Still Need Data Scientists

17:44 Skills vs Vanilla Coding Agents

25:27 Guardrails, Hard Checks and R-hat

28:50 Token Costs and Business Value

33:05 PyMC Labs Open Source Strategy

36:46 Decision AI Stack and Lens Demo

40:11 Agent to Agent Media Buying

45:34 Future Foundational MMM Models

49:31 Wrap Up Tips and Community

While this episode is real, the content is all made up... or more accurately, it's about data that is made up. Synthetic data. A term that's popping up more and more regularly in marketing and measurement conversations.

Listen to Winston Li (Founder @ Arima) and T.S. Kelly (Managing Director, US @ Arima) as they describe the 5 Ws (and H) of synthetic data, along with some great examples and use cases of how they answered some valuable questions for Coca-Cola and other companies.

This episode was recorded live in front of a studio audience at MeasureCamp New York.00:00 Simon Missing Intro

00:50 Guests And Donuts

02:17 What Is Synthetic Data

03:53 Related Terms Confusion

05:20 Who Uses Synthetic Data

06:51 How To Create It

09:55 Data Sources & Legal

11:50 PII Free Probabilistic Joins

13:39 Validation & Trust

17:09 Marketing Use Cases

18:18 Coca-Cola Vending Simulation

23:39 Where Synthetic Data Goes Next

25:50 Audience Questions Lightning Round

32:00 Wrap Up

Google officially retired its workhorse analytics platform, affectionately known as Universal Analytics, almost 3 years ago. Since then, people have started to learn about other platforms as they scrambled to find something more useful than GA4.Jason Packer wrote the book on Google Analytics alternatives (literally, it's titled "Google Analytics Alternatives: A Guide to Navigating the World if Options Beyond Google").Here's what we think of the analytics landscape - how we got here, and what's coming next.

Links from the show:

(eBook) Google Analytics Alternatives

(paperback) Google Analytics Alternatives01:29 Universal Analytics Sunset02:31 Meet Jason Packer05:53 Jasons Early Web Days10:20 Why Analytics Matters13:05 Fragmentation vs Consolidation17:22 GA4 as Ads Companion21:13 Googles Motives23:50 GA4 Pain Points24:32 Why Users Are Leaving26:51 Privacy Compliance Pressure29:33 Top GA4 Alternatives30:15 Simplified Analytics Tools32:06 Product Analytics Picks35:38 Comprehensive Web Platforms36:42 Future of Analytics AI42:23 MCP, LLMs and Trust49:49 Closing Insight and Wrap

We needed some help regulating and validating our podcast (and models), so we invited Henry Innis - Co-Founder of Mutinex - to help out.Listen in to this lovely chat about the quirky differences between the American and Australian markets, challenges and realities of MMM, and the future of media measurement and regulation. Buckle up for the hot takes.00:00 Casual Catch-Up and Thanksgiving Stories01:08 Topic Introduction - Marketing Mix Modeling01:34 Guest Introduction and Background03:00 Differences in Marketing Practices: US vs Australia06:27 Innovative Applications and Hackathon Projects09:51 Marketers and Money Conference Overview13:32 Challenges and Realities of Marketing Mix Modeling16:36 Campaign Varying Model and Its Impact24:30 Future of Media Measurement and Regulation28:09 Introduction to Industry Insights28:33 Integrating Work's Knowledge into Mate30:02 The Role of MMM in Marketing32:53 Challenges in Data-Driven Decision Making34:48 Partnering with WARC for Effectiveness35:53 Common Questions Asked to MAITE38:34 Validating Outputs and Handling Errors49:33 Open MMM Validation Framework54:40 The Impact of Google and Meta on MMM55:22 Conclusion and Future Discussions

Version A: Join Simon and Jim as they babble about button colors while the experts tell them what really matters in experimentation.

Version B: Have you ever wondered what makes for a great experimentation culture?

(Let us know in the comments which version you prefer!)

We were lucky to talk with Kelly Worthham and Ton Wesseling, both experts in decision science and experimentation.We cover the transition from traditional conversion rate optimization (CRO) to broader growth engineering, organizational transformation for better decision-making, and the impact of AI on experimentation.

Discover how conferences like Experimentation Island and Conversion Hotel foster deep, meaningful conversations and collaborations within the community.

Links from the show:

The Conference known as Conversion Hotel

The Conference known as Experimentation Island

Test & Learn Community

No Hacks Podcast

Experimentation Culture Awards

00:00 Introduction and Casual Banter

00:52 Halloween Candy Stories

02:27 Introducing the Special Guests

02:41 Kelly Worthham's Background

03:58 Todd's Background and Contributions

05:18 Experimentation Island Conference

13:57 Conversion Optimization vs. Growth Optimization

25:07 The Risk of Imitating Big Brands

25:22 Helping Businesses Make Data-Driven Decisions

27:02 Building Effective Experimentation Processes

30:22 Challenges in Replicability and Experimentation

34:54 The Role of AI in Experimentation

40:52 Future of Experimentation and AI

48:32 Concluding Thoughts and Recommendations

Ever wonder how Walmart, Kroger, Home Depot, and Instacart are different from a guy in a trench coat? They ask for consent before exposure! Join Simon and Jim as they dive into the often misunderstood world of retail media networks with Sky Frontier, EVP at Incremental.Discover why retail media is the Wild West of advertising, how it's moving up the funnel, and the unique challenges it poses. Learn about Sky's journey from philosophy to advertising, and why your branded search strategy might need a rethink. Plus, we tackle Amazon's recent Google Shopping mystery – did they just pull off the greatest experiment of all time?

Links from the show:

Skye Frontier on LinkedIn

IncrementalShow Notes:00:00 Welcome Back and Summer Catch-Up00:34 AI Measurement Solutions and Future Prospects01:10 Retail Media Networks: An Introduction02:21 Guest Introduction: Sky Frontier04:15 Defining Retail Media Networks06:46 Challenges in Retail Media Measurement14:12 Incrementality in Retail Media18:42 Operational Challenges and Clean Rooms22:55 Challenges in Retail Media Experimentation23:41 Econometrics and Granularity in Retail Media25:18 Synthetic Experimentation and Difference-in-Differences Analysis28:30 Future Trends in Retail Media32:28 Amazon's Strategic Shift in Advertising41:55 Concluding Thoughts on Retail Media Measurement

Should you measure SEO by its ability to climb a tree? Hear Mike King's take on all things SEO - how AI is disrupting the space, and how measurement is (or should be) changing for this channel.Mike King is the founder and CEO of digital marketing agency iPullRank. King's journey from battle rapping with the Wu-Tang Clan to decoding Google's algorithms lays the foundation for a spirited discussion on the future of SEO, the impact of AI on search behavior, and innovative measurement techniques.Listen as we explore the shift from traditional click-based metrics to more complex, probabilistic methods driven by AI. Learn how SEO is adapting to changes in user behavior, including the rise of AI overviews and the challenges of measuring their impact.Plus, don't miss King's tips on leveraging advanced tools and strategies to stay ahead in the ever-changing SEO landscape.

Links from the episode:

Mike King on LinkedIn

iPullRank

Qforia

Show Notes:00:00 Introduction to Mike King00:23 Mike King's Early Career and Achievements00:38 Transition to Digital Marketing01:08 Future of SEO and Measurement Challenges01:51 Understanding SEO Metrics04:36 Google's AI Overviews and User Behavior05:21 SEO as a Brand Channel07:45 Challenges in Measuring SEO Effectiveness09:21 Impact of AI on SEO Traffic11:49 Evolving SEO Measurement Techniques18:22 Tools and Strategies for SEO Measurement25:07 Understanding Query Fan Out and Reasoning in SEO28:42 Client Education and Shifts in Search Behavior32:57 Improving Relevance and Content Structure36:04 Measuring SEO Performance and Authoritativeness43:25 Sentiment Analysis and Query Fan Out46:03 Reframing SEO for Better Investment48:41 Final Thoughts and Incremental Insights

Google Marketing Live 2023: Key Announcements, AI in Search, and the Future of Measurement

Simon and Jim unpack the highlights of Google Marketing Live 2025. Fresh from the conference, Simon "delves" (yes, AI was a big part) into key announcements, including AI in Search, AI Max for Search, VEO advancements, and measurement challenges.

They discuss the excitement around AI mode, scenario planning in Google Analytics, and the evolving landscape of Marketing Mix Modeling (MMM).

Additionally, they touch on insights from Google's new tools and partnerships, underscoring a shift towards more integrated and accessible marketing strategies.

▶️ Watch on YouTube

00:00 Introduction and Casual Banter

00:15 Google Marketing Live Highlights

01:23 Shaq and T-Pain at GML

03:19 Measurement Announcements at GML

05:13 Incrementality Testing

13:01 Google Analytics and Attribution

20:44 Meridian Scenario Planning

25:21 Making MMM Accessible: A Double-Edged Sword

25:57 The Complexity of Tagging and MMM

28:14 Validation and the Dangers of Simplification

32:11 AI's Role in MMM and Marketing

37:48 Google Marketing Live: Key Announcements

38:53 The Future of AI in Search and Advertising

42:42 VEO and the Evolution of Creative Development

47:37 Final Thoughts and Community Engagement

Are you wondering what to do next in your career? Is AI going to leave you living in a van, down by the river? What paths have others taken through this crazy measurement industry we're in?Let's learn from a sample of 1: Sani Manić - who has gone from web dev to CRO to co-founder of a SaaS company. Find out how he transitioned across various web development and CRO roles and how decided what to do next.

▶️ Watch on YouTube

Links from the show:

Sani Manić on LinkedIn

Podpacer

Cohesio

Book - Can't Hurt Me (David Goggins)

The School of Greatness podcast (ep. with Leila Hormozi)

Show Notes:00:00 Introduction and Friendly Banter01:33 Career Backgrounds and Education01:57 Career Progression and AI Impact02:58 Guest Introduction and Career Journey06:08 WordPress Beginnings11:57 Transition to Marketing and SEO13:21 Bridging the Gap Between Teams19:36 Challenges in CRO and Statistics23:16 AI and Best Practices in Website Optimization23:59 The Future of Hyper-Personalized Experiences26:38 The Problem with Historical Data in CRO28:11 Universal Experiences vs. Individual Optimization31:53 The Journey to Becoming a Founder34:15 Building Tools to Solve Real Problems38:04 Advice for Aspiring Entrepreneurs39:16 The Importance of Focus and Small Steps48:09 Incremental Insights and Recommendations

Is MMM the right solution for your company?

With seasoned professionals Gabriel Franco (Founder of Cassandra) and TS Kelly (Managing Director at Arima), we go deep into the world of Marketing Mix Modeling (MMM).

What does the adoption of MMM look like? What's the role of open-source tools like Meta's Robyn and Google's Meridian? When is MMM the NOT the right solution? What do MMM critics get wrong? And what's in store over the next few years for MMM?

▶️ Watch on YouTube

00:00 Introduction and Opening Remarks

00:34 Introduction to Marketing Mix Modeling

00:55 Current Trends and Sponsors in Marketing Mix Modeling

01:36 Choosing the Right Marketing Mix Modeling Approach

02:55 Consultant vs. In-House vs. Open Source

04:17 Challenges and Success Stories in Marketing Mix Modeling

08:31 Adoption and Education in Marketing Mix Modeling

23:20 Future of Marketing Mix Modeling

30:18 Audience Q&A

37:10 Conclusion and Closing Remarks