Funnel Reboot

Episode 173

Today, we’re talking about the future of data with Google Analytics 4.

It’s been about 6 months since we all had Universal Analytics. It’s good to talk to others who use GA4 to do their jobs, to compare notes. Although GA4 is here to stay, it still has gaps that need bridging.

That’s why I spoke with Jason Hackenberry, Head of Partnerships from web development agency Arctic Leaf. Prior to Arctic Leaf, he held Digital Marketing and operations roles at Weatherby and Save Khaki United, along with roles in Merchandising.

What you’ll hear is from a virtual event he and I did in December 2023, on topics including

• How Google is migrating users of its free version differently from its 360 version
• How to capitalize on the information provided by GA4
• The data you actually need vs. what you THINK you need
• Tips on finding insights, reporting, conversion tracking and data retention
• New GA4 features that can help your lead generation or e-commerce website.

Episode 172

GA4 is now our de facto analytics tool. Regardless of how familiar we were with the previous  tool, GA4 is here to stay so we may as well get good at using it. 

I’ve got just the person to make the transition relatively painless for us. 

Our guest’s love for analytics was a happy accident after she worked in marketing at a company with a sales director. They told the executive team that marketing’s budget would be put to better use hiring new salespeople. But beyond having a warm fuzzy feeling in one’s tummy, it wasn’t clear marketing’s impact could be articulated in the way that executives talked.

Not willing to watch her department disappear, she dug in and found the data that showed marketing was having an impact. She took the evidence to the next board meeting and her department was able to continue with its work.

She chose to go out on her own so she could empower marketers to do as she’d done. She now heads up The Colouring In Department, a consultancy that has completed close to 230 GA audits now, and has trained thousands of people on how to get good at their analytics. 

Joining from London England – here is Jill Quick

People/Products/Concepts Mentioned in Show

Tools – David Vallejo – Event checker

Adobe analytics

Matomo analytics

Piwik pro

Episode 170

Whenever your marketing is being assessed by an analyst, they will use one of two approaches. 

The first is called Multi-touch attribution, which takes a customer who’s made a purchase decision, then puts weights on the touchpoints they had on various channels (Google calls their model ‘Data-driven attribution”) on the way to that point, to say which touchpoints were most influential. 

The other approach they may use is Media Mix Modeling. From what previous podcast guest Kevin Hartman told me about MMM, it’s a ‘tremendous undertaking.’  It involves collecting and analyzing historical data in different geographies at different times of the year: sales figures, both legacy and digital marketing channels, and external factors like economic indicators and even weather. It has its own jargon: Incrementality, ratios, betas, impact on objectives. Then there’s the math. It uses regression methods, both linear and non-linear, Frequentist vs Bayesian statistics. 

I get so overwhelmed with these modeling solutions, it’s like the old Who’s On First skit. I needed someone who would sort this out for me. 

Our guest has been a consultant in the marketing and digital analytics space for 15 years. I’m currently focusing on helping clients quantify the impact of their marketing efforts using Marketing Mix Models, experimentation, and various attribution methodologies.

He is so passionate, he started a newsletter called MMM Hub

He graduated from Carnegie Mellon with a Masters degree in Information Technology, focused on Business Intelligence & Data Analytics.

Jim is great at showcasing other people in the analytics community -He truly believes that all of us are smarter than any one of us. He, along with Simon Poulton, co-host the MeasureUp podcast. 

He talked with me from his home in Pittsburgh. Let’s meet Jim Gianoglio.

People/Products/Concepts Mentioned in Show

Jim’s Cauzle Analytics consultancy

The MeasureUp podcast.

John Wallace

Randomized Control Trials (RCTs)

Bayesian Statistics

Media mix modeling ratio:

1. The Marketing Channels Being Used
2. The Money Being Spent on Each Marketing Channel
3. Campaign Results & Insights

Episode Reboot – articles & videos shared by Jim:

What is Marketing Mix Modeling? 3 Benefits and Limitations – this is a very high-level article, explains some of the basics (but none of the ‘how-to-do-it’ pieces)

Market Mix Modeling (MMM) 101 – This is a good intro-level article highlighting the important high-level concepts of MMM

A Complete Guide to Marketing Mix Modeling – although this article/site is littered with a bunch of ads, the content is actually pretty good. It touches on the concepts as well as providing some code snippets for R, Python and SAS.

Videos / Courses to help get started with modeling:

MASS Analytics – Marketing Mix Modeling Master Classes – (free) 14 courses (YouTube videos) – very well done, starts at a beginner introduction to MMM and goes all the way through advanced modeling techniques. It’s about 3 hours in total.

Marketing Mix Modeling 101 – (free) online course (YouTube videos). This is 2.5 hours over 5 courses that focuses on MMM using Robyn, so is good if you’re comfortable using R.

Vexpower – What’s the impact of TV ads? – (free) this is a good intro into the concepts of modeling and MMM, and should only take 1-2 hours to complete 

Vexpower – Can we try Facebok Robyn? – (free) this one walks you through a complete example of using Robyn to do MMM