Measure Up

A professor, an analytics director, and a podcaster walk into a bar and order a whiskey. Which brand do they order? And how does that data make it's way into a marketing mix model?

That's what Simon and Jim wanted to know, so they asked Elea Feit - Associate Dean of Research and Professor of Marketing at Drexel, and Karen Chisholm, Director of Transformation Analytics at Pernod Ricard.

Find out the biggest challenge marketers are facing today regarding measurement, and how they're tackling it. 

Find out what's in store for marketing measurement and MMM in the next 3 years.

Grab a drink and have a listen :)

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Links from the show:

Marketing Science Institute

The Advertising Research Foundation

Elea Feit on LinkedIn

eleafeit.com

Karen Chisholm (email about job opportunities!)

00:47 Today's Topic: Marketing Mix Modeling

02:10 Introducing the Guests

05:07 MSI and ARF Initiative

07:52 Survey Insights and Challenges

12:20 Measurement Techniques and Strategies

16:34 Brand-Level Optimization and Earned Media

22:44 Granularity in Marketing Mix Modeling

28:54 Understanding Marketing Mix Modeling

29:18 The Four Ps and Their Importance

30:20 Media Mix Modeling vs. Marketing Mix Modeling

32:29 Challenges in Media and Marketing Mix Modeling

34:09 Always-On Discounts and Their Impact

37:14 Data Quality and Availability Issues

40:38 The Future of Marketing Mix Modeling

43:08 Industry Perspectives and Best Practices

50:28 Open Source Solutions and In-House Modeling

54:58 Job Opportunities and Final Thoughts

There's been a lot of excitement about Google's recent launch of Meridian - their open-source MMM framework. But does it live up to the hype?

Jim and Simon explore what sets Meridian apart from other tools like Meta's Robyn and PyMC Marketing. They also discuss the evolution and impact of open-source MMM, the role of new data streams such as Google Query Volume and Reach & Frequency data, and how the availability of Meridian might shift industry standards. Listen in to understand the features, benefits, and the potential gaps Meridian fills within the marketing measurement ecosystem.

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Links from the show:

Google's Meridian

Meta's Robyn

PyMC Marketing

Recast - Validating MMM

MMM Hub

00:00 Introduction and Host Switch-Up

00:37 Discussing Google's Meridian Announcement

02:00 Understanding Meridian's Name and Popularity

03:48 Google's Open Source MMM Framework

05:53 Comparing Lightweight MMM and Robyn

12:02 The Role of AI and Data in MMM

21:52 Debunking Meridian's Myths

22:13 Understanding Meridian's Role in Experimentation

22:54 The Importance of Competition in Open Source MMM

23:28 Unique Features of Meridian Compared to PyMC and Robin

23:49 Choosing the Right MMM Tool: Robyn, Meridian, or PyMC?

24:22 Explaining Time Varying Coefficients

24:30 Entry-Level Recommendations for MMM Tools

25:00 Static vs. Time Varying Baselines in MMM

28:44 Evaluating the Accessibility of MMM Tools

35:20 The Need for Robust Validation in MMM

37:38 Challenges in Incrementality Testing

39:07 Bridging the Gap Between MMM and Media Managers

43:17 Future of MMM: In-Platform Incrementality Testing

43:46 Final Thoughts and Joining the MMM Hub

Big Bets for 2025: AI, Marketing Mix Modeling, and the Future of Retail MediaJoin Simon and Jim as they place their bets for 2025. Find out why Jim thinks MMM adoption is going to skyrocket, and why Simon is all in on retail media measurement.More importantly, find out why Simon's house was once listed on Google Maps as a Forever 21 location.

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00:00 Introduction and Year-End Reflections00:24 Cauzle's First Year and Growth01:02 Podcast Popularity and Listener Engagement01:35 Career Transitions and New Roles03:49 The Future of Measurement and Media04:05 Big Bets for 202504:55 Big Bet #1: Retail Media Measurement14:33 Big Bet #2: Marketing Mix Modeling Predictions26:05 Big Bet #3: AI Answer Engines and Search Behavior30:55 Big Bet #4: AI's Role in Marketing33:18 Big Bet #5: Synthetic Audiences in Market Research43:39 Big Bet #6: External Performance Calibration59:48 Concluding Thoughts and Incremental Insights

Do you ever feel like your activities online are being watched? Well, it's probably because they are 🤣

Join Simon and Jim as they explore behavioral analytics with guest Josh Silverbauer. Josh explains the intricacies of tools like Microsoft Clarity, the comparison between marketing and behavioral analytics, and the potential future of AI-driven personalization.

We also dive into Josh's unique contribution to the analytics community through his rock opera 'User Journey'.

Links from the show:

Josh Silverbauer on LinkedIn

User Journey - The Rock Opera

Steve from Milwaukee (iykyk)

Show Notes:

00:00 Introduction

02:08 Behavioral Analytics Overview

02:15 Introducing the Guest: Josh Silverbauer

08:06 Deep Dive into Microsoft Clarity

24:47 Future of Behavioral Analytics and Personalization

29:45 The Assumption of Personalization

29:56 Hyper-Personalization in Practice

30:33 Challenges of Hyper-Personalization

31:34 User Privacy and Personalization

32:20 First Party Cookies and Identity Resolution

33:40 The Future of Web Identity

34:57 Personalization Gone Wrong

38:30 The Ethics of Screen Recording

40:14 The Analytics Rock Opera

45:32 Creative Projects and Community Integration

51:23 Final Thoughts and Recommendations

Did you know that pre-roll podcast ads cost half as much and drive twice the ROI of mid-roll ads?

That's just one of the many insights today's guest brings to the table. Listen in to understand the intricacies of podcast advertising with Amila Coomber, Head of Marketing & Growth at Podscribe. We explore everything from the technicalities of measuring podcast ad effectiveness, the evolution of podcast advertising, the role of pixel-based measurement, and the differences between host-read and dynamic ads. Amelia also shares valuable insights into the future of podcast advertising, including the potential impact of video on platforms like YouTube.

Links from the show:

Amelia Coomber on LinkedIn

Podscribe

Quarterly (Podcast Advertising) Performance Benchmark Reports

00:00 Introduction and Nickname Banter

01:28 Discussing Podcast Ads

02:17 Introducing the Guest

05:01 Understanding Podcast Advertising

14:32 Technical Aspects of Podcast Ad Measurement

26:16 The Rise of Podcast Advertising

26:38 Simulcast and Pixel-Based Attribution

27:20 YouTube's Role in Podcasting

27:59 Challenges in Measuring Podcast Ads

31:10 Programmatic Advertising and Future Trends

33:38 Dynamic Feedback Loops and MMM

44:22 Creative Strategies in Podcast Ads

45:56 Insights and Future of Podcast Measurement

47:32 Final Thoughts and Incremental Insights

⁠Mike Taylor⁠, co-author of ⁠Prompt Engineering for Generative AI⁠ and first two-time guest of the pod joins us to "delve" into the important questions around getting the best answers out of ChatGPT and the like.

Learn about the principles of prompt engineering, the role of generative AI in analytics, and how to effectively use AI for data cleaning, code generation, and more.

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Links from the show:

• ⁠Ep. 2 with Mike - Marketing Memetics & Measurement⁠
• ⁠Prompt Engineering for Generative AI⁠ [book]
• ⁠Cursor⁠ (AI code editor)

00:00 Introduction and Casual Banter

01:16 Speed Reading and Da Vinci Jokes

02:52 Introducing the Guest: A Modern Day Da Vinci

05:19 Diving into Prompt Engineering

08:35 Generative AI in Analytics and Marketing

14:37 Practical Applications and Challenges

18:38 Prompt Engineering Tips and Tricks

24:54 Crafting Effective Prompts for Social Media

25:37 The Value of Prompt Engineering in Automation

26:39 Exploring Prompt Marketplaces and Tool Use

27:51 Automating Prompt Creation and Its Implications

29:28 The Future of Prompt Engineering as a Skill

32:50 Applications of AI in Copywriting and Image Generation

34:58 AI in Data Extraction and Analytics

45:12 Leveraging AI for Industry Insights and Efficiency

48:45 Conclusion and Book Pitch

What do PMax, Advantage+ and an 8-year-old in an arcade have in common?They'll spend as much as they can, if you let them!In this episode, join Jim and Simon as they dive deep into the world of PPC with Navah Hopkins, a seasoned expert with over 16 years in the marketing industry. Navah shares her insights on Google’s Performance Max (PMax) campaigns, discussing the intricacies of managing them, excluding branded searches, and overcoming broader measurement challenges.Links from the show:

Navah on LinkedIn

Optmyzr00:00 Vacation Plans and PPC Jokes01:25 Introducing Today's Guest: Navah Hopkins03:21 Diving into Performance Max Campaigns06:23 Challenges and Strategies in PPC10:42 Understanding Performance Max and Asset Management16:54 The Role of Ad Strength and Measurement in PPC24:16 Incrementality Testing Challenges24:35 Meta's Advantage Plus and A/B Testing25:06 Google's Approach to Testing and Privacy25:57 Geo-Based Holdout Testing26:24 PMax Campaigns and Branded Search27:46 Testing Strategies and Market Considerations28:29 Google's Targeting Limitations28:55 Branded Search in PMax33:05 Data Teams and PPC Collaboration38:16 Onboarding and Training for Measurement Practitioners47:45 Creative and Data-Driven Marketing49:47 Productivity Tips and Metal Music

How much should you be paying for Marketing Mix Modeling (MMM)? How do you make day-to-day tactical decisions when MMM isn't that granular? Should you go with open source MMM solutions, or stick with a vendor?Join Jim and Simon in this in-depth discussion about the current state and future of Marketing Mix Modeling (MMM). They cover the evolution of open-source MMM platforms like Meta's Robyn, Google's Meridian, and PyMC Marketing, and explore their pros and cons. They also discuss the implications of AI-driven ad units and the challenges they pose for measurement.

📺 ⁠⁠⁠Watch on YouTube⁠

Links from the show:

• MMM Solution Comparison
• Questions to ask MMM Vendors
• Meta's Robyn
• Google's Meridian
• PyMC Marketing
• Uber's Orbit
• Recast
• PyMC Labs

00:00 Introduction and Greetings00:44 Discussing the State of MMM02:02 Exploring MMM Platforms08:33 Quick Tangent - Baseball and Data Analytics09:41 Comparing MMM Packages12:23 Open Source MMM and Future Trends25:45 The Origin of PyMC Marketing26:54 Comparing Open Source Options29:23 The MMM Gap: Challenges and Solutions31:55 Triangulation and Platform Data39:53 The Role of AI in Ad Buying49:50 Future of MMM and Industry Trends

What are the biggest challenges facing marketers and analysts today? Is it privacy regulations? Technology changes? AI?In two words: unmet expectations.Neil Hoyne, Chief Strategist at Google, shares his insights into the evolution of marketing measurement given the current environment and challenges.

Even with MMMs and incrementality testing, at the end of the day the organizations that win will be the ones that can take action and make decisions based on the data. This is not a tool problem, or a data problem - it’s a people problem. Organizational friction and human behavior is still there.

Listen in as we discuss the resurgence of Marketing Mix Modeling (MMM) as essential tool for marketers in a privacy-centric era, the importance of adaptability within the marketing industry, and the crucial role of storytelling and relationship building in data interpretation.

📺 ⁠⁠Watch on YouTube⁠

Links from the show:

Timeline:00:21 A Dive into Historical Context01:08 Setting the Stage for Today's Episode: The Marketing Measurement Dilemma02:44 Introducing the Expert: Neil Hoyne03:54 The Evolution of Marketing Measurement Post-COVID06:19 Challenges and Expectations in Modern Marketing Measurement16:51 The Resurgence of MMM and Addressing Organizational Challenges22:08 Bridging the Gap Between Data and Decision-Making23:22 The Future of Measurement and Analytics in Marketing26:47 Exploring the Imperfections of Marketing Tools27:05 The Complexity of Understanding Consumer Behavior28:10 Navigating Uncertainty in Marketing Decisions29:04 Competitive Advantage in Consumer Behavior30:26 The Quest for Better, Not Perfect, Marketing Models32:12 Bridging the Gap Between Data Science and Business Goals33:52 Embracing Imperfection and Business Impact38:05 The Future of AI and Its Impact on Marketing43:08 Adapting to Change and Embracing New Skills46:25 Final Thoughts and Advice for Marketers

Billboards, transit posters, digital signage - these are just a few of the options for out-of-home (OOH) advertising. OOH is a format that as digital marketers and analysts, we don’t typically consider. But when it comes to measuring billboards and other OOH channels, how exactly do we do that?We brought on an expert at the cutting edge of OOH to answer this question, and bring light to how OOH is changing in today’s digital world.Ty Tinker is Head of Analytics at AdQuick - a company that is modernizing the out-of-home advertising space. We talked with him about the finer details of OOH measurement, including the past, present and future capabilities.

📺 ⁠Watch on YouTube

Links from the show:

• Ty on LinkedIn
• AdQuick
• MeasureUp Ep. 6 with Greg Dolan
• MeasureUp Ep. 22 with Nick Stoltz
• AdQuick Madvertising Podcast
• Billboard Cost Calculator