Episode 150: Marketing Analytics Summit – Experts on where we go from here

episode-150-marketing-analytics-summit-experts-on-where-we-go-from-here

It’s fitting, given how this is Funnel Reboot’s 150th episode, that we veer off of the standard format and dig into a niche within marketing that’s becoming a de facto part of every marketing function and is dictating new skills that every marketer must learn. I’m talking about marketing analytics. 

This episode is compiled from experts in the world of analytics. It was recorded on location at the Marketing Analytics Summit that was held in Las Vegas. It’s coming  hot off the press from the June 2023 event.

This episode is divided into themes discussed at the summit. Here they are shown with time markers for each chapter:

ChapterStarts atSpeaker (mentioning only first time they appear)
INTRO3:00Jim Sterne
GA5:56Sheena Green
Sara Hoffman
Kelly Anne Wortham
Kenya Gillette
Jenn Kunz
UX/Testing11:58Geddy van Elburg
Deborah O’Malley
Anna Smolina
Process17:53June Dershewitz
Brianna Mersey
People20:19Rachel Heseltine
Ali Groepper
Lina Mikolajczyk
AI’s impact23:50Ryan Levander
Mary Owusu
Facing Change28:48Anil Batra

People and events mentioned in the show: 

Deborah O’Malley, who was the guest on Funnel Reboot Ep 65

The winning analogy of the conference made fun of how loosely people add the term AI to everything. Kenya Gillette used soccer to characterize this. Imagine you were the person who designed the game, documented all the rules and scouted the earth for people to play it. 

Then someone says they can make soccer better…by simply playing the game ON THE MOON. That is the equivalent of saying that any business activity can be made better by adding AI to it.

Episode 139: What Google Analytics 4 Makes Possible, with Mark Edmondson

Mark Edmondson

We’re ending our series on advancing analytics today. We’ll focus on the software that, for many marketers, is at the core of this field: Google Analytics. It was introduced in 2005 as a read-only tool that tracked basic info on websites. The name has stayed the same over these last 18 years, but so much else of Google’s technology landscape has changed: they have released many other tools:  Tag Manager, Google Data Studio, now Looker Studio, ways for API’ing between systems in and outside of Google, and most importantly a place where it can all be managed – Google cloud.  

The new Google Analytics GA4 was born of this environment.It’s been criticized as being immature since it lacks features that were in the old UA interface. However, if judged by how well Google integrated it into their stack and how much those with technical skills can do with it, we would rate it as ready for prime time. Add to that the fact – in a matter of weeks Google teams won’t have to maintain two analytics tools, and they’ll get to focus exclusively on just one – GA4.  

We can debate Google’s motives for tightly integrating GA4 with the whole Google cloud. I’m not wading into how good or evil it is to give away a product and hope users try the paid cloud platform that comes with it. But I’ll say that using Google Analytics with these other pieces lets you do much more with your data that you couldn’t do with the old GA. And when tools directly or indirectly  make money for Google, that incents them to keep those tools and keep improving them. I’ll leave it at that. 

Our real question is how do  we economically benefit from the available tools. And that’s what our guest is going to tell us. His book which came out in early 2023 is called “Learning Google Analytics: Creating Business Impact and Driving Insights”  The business impact spoken of there doesn’t mean using GA4 as a standalone lookup tool. Using it like that and ignoring what’s possible, would make the rest of the whole Google stack seem (to quote from the Movie ‘Contact’, “like an awful waste of space” 

Our guest knows the value of integrating Google’s tools for many world-wide brands, as he’s done through digital agencies on his own as a GA consultant since 2008.  Mark Edmondson has helped turn the out-of-the-box Google Analytics into a package that automatically describes, predicts and activates better marketing outcomes. He currently works at Devoteam as their Principal Data Engineer. 

Mark grew up in Cornwall, UK before gaining his Masters in Physics at Kings College London. He now lives in Copenhagen with his wife and two children, enjoying playing music and cycling around the many lakes.

People/Products/Concepts Mentioned in Show

Mark’s blog

The ‘jewel in the crown’ of Google Cloud: BigQuery

What it means to implement Server-Side Google Tag Manager 

Episode Reboot. Mark’s takeaway: ‘Moving all the useful data to one place has had the most transformational effects on a client’s digital maturity,’

Episode 138: How Data Pipes Operationalize Analysis, with Noah Learner

Noah Learner

Today we’ll talk about automated marketing data pipelines for reporting and even activation. If that last sentence didn’t make total sense to you, don’t worry, our guest is going to tell us why we need it and how we can set out implementing it. 

The place where Noah Learner got his start was on the island of Nantucket.  It’s around 20km (15 mi) long, which is small enough that most visitors leave their cars on the mainland, come across on the ferry and rent a bike. 

Noah’s journey started with a job at one of the island’s bike rental shops. Over the next decade as he rose to become the company’s GM, he became convinced of the power of SEO for driving traffic. 

He relocated to Colorado, at various points he worked in corporate SEO roles and worked out on his own. He even mashed up skills from his past to serve businesses in the pedal-powered rental market, calling it ‘bike shop SEO.’

In the past 4-5 years he’s built cutting edge SEO tools using Google Cloud technology and has shared how to deploy them by speaking at MozCon, SearchLove and LocalU and in the agencyautomators.com community which he cofounded. he’s just taken on a new role  that has tool-building  baked into his mandate, as Director of Innovation for Sterling Sky

When not at work, he loves doing typical Colorado things like fly fishing and skiing, along with family-friendly activities like hiking and camping where their two dogs can tag along.

People/Products/Concepts Mentioned in Show

DBT, or  Data Build Tool is a set of scripts or programs that, when deployed, cleans and transforms a data source’s original tables and fields into a usable format for analysis.

VS code environment

Noah’s LinkedIn profile

Two Octobers

Learner’s model: Revenue = Transactions X Conversion Rate X Average Order Value 

Episode 137: Data Storytelling with Looker Studio – Sireesha Pulipati

Sireesha Pulipati

You have strategized and run a program with positive results, you would think that you simply show leadership your data and then you can sit back while they lavish you with praise.

Not quite.

If it isn’t packaged right, it won’t have that hoped-for impact. Remember Maya Angelou said ‘people will forget what you said…what you did….but will never forget how you made them feel.’ That feeling is conveyed through stories. To find and tell those stories, you need business intelligence and data visualization tools. I sought out a Googler who’s an expert in their tool for doing this: Looker Studio.

Sireesha Pulipati is an experienced data analytics and data management professional. She has spent the last decade building and managing data platforms and solutions, and she is passionate about enabling users to leverage data to solve business problems. 

Sireesha holds a master’s degree in business administration and a bachelor’s degree in electrical engineering. Her work history spans multiple industries – healthcare, media, travel, hospitality and high-tech 

She is currently at Google as a technical lead, helping with the business intelligence and analytics strategy for internal teams.

She is the author of the newly-published book Data Storytelling with Looker Studio

People/Products/Concepts Mentioned in Show

Google Looker Studio

Google Looker Studio Pro

This host has loved stories, all the way back to when he read them to his kids.

Episode 136: Building Analytics Teams, with John Thompson

Building Analytics Teams

John Thompson is the author of the 2020 book Building Analytics Teams, and a 35-year technology executive in the fields of data, advanced analytics and artificial intelligence (AI). 

He is Global Head, Artificial Intelligence (AI) at EY.  John was an Executive Partner at Gartner. He was the global advanced analytics and AI function at  biopharmaceutical company CSL Behring, where he led an analytical applications team.

John has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run – sales, marketing, consulting, support and product development organizations.

He has been a technology leader with expertise and experience spanning all operational areas with a focus on strategy, product innovation, growth and efficient execution.

Thompson holds a Bachelor of Science degree in Computer Science from Ferris State University and a MBA in Marketing from DePaul University.

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Tom Davenport

Data Science modules on Coursera by U Michigan’s Dr Charles “Chuck” Severance

Shawn Rogers

Diagram showing work of analytics being approached in either an artisanal or a factory style; used with permission

Episode Reboot. John’s book  “Data for All” published in 2023

Episode 135: Data Clean Rooms, with Puneet Gangrade

Data Clean Rooms

Disclaimer:When I bring technology vendors on the show, you should know that they are not sponsors or affiliates. They’re simply here to give you a broader perspective.

Puneet Gangrade is a Customer Success Engineer, an active amateur soccer and badminton player and a resident of New York City who originally hails from Indore, India

He works at Habu, a data clean room software company, with the goal of creating reliable data and media strategies for all of his clients. He is responsible to work with Habu’s Engineering, Product teams, and clients on end-to-end workflows including clean room adoption, onboarding, planning, implementation, and growth. Habu works across distributed data platforms that allow agencies, publishers, advertisers, and their partners to truly unlock the potential of data and collaborate in a privacy-safe manner. 

He has been a data clean room enthusiast since the beginning of 2018. Previously, he worked as a Digital Analytics Specialist at Time Inc till Oct 2017 and as a Data Science Team Lead at MightyHive, an adtech agency from early 2018 to mid-2022. He has a BS in Computer Science and earned his MS in Marketing Intelligence from Fordham University Gabelli School of Business, with a concentration in Marketing and Analytics.

Amid the rise of advanced measurement techniques in media and other industries, he likes to keep learning about various data clean room technologies and constantly think of use cases in media, finance, CPG, pharma, etc. where data clean rooms could be leveraged. He continues his passion for everything related to data clean rooms and data collaboration at Habu.

People/Products/Concepts Mentioned in Show

Puneet’s LinkedIn Profile

Puneet’s Twitter Profile

Company where Puneet works: Habu

Description of Walled Gardens

Concept of an Escrow (example given with finance can also be applied to data)

Episode Reboot: Read this background article: Data clean room: A silver bullet to a post-cookie transition?

Episode 121: Looker Studio 101, with JJ Reynolds

No about analytics is complete without talking about how to visualize data. A picture’s worth a thousand words, right? In the past, when data was in a spreadsheet, it only took hitting that ‘chart’ button to render some numbers visually. But for many of us, this experience has moved to a browser where we build our own report, either in an interface like GA or in a standalone visualization tool. 

I’m talking with someone who’s really good at a visualization tool, but came by his power-user status in a roundabout way. My guest was born and raised in Hawaii.  After he got his Marketing degree, he worked at an ad agency where he did everything from videography to FB and G-ads writing. That, and also building a few websites, stoked his curiosity for how the tagging and the analytics behind all these things worked. He didn’t just want to get at raw data, he wanted actionable data.  He felt that to optimize his marketing, if he only knew how to present visitor behaviour data visually, the answer would be apparent – even obvious.  

He went down YouTube rabbit holes, asked around at conferences, and eventually landed on the beta of Google Data Studio, now called Looker Studio.  And that’s the Data Visualization tool we’re talking about with JJ Reynolds, who joins us from Reno NV.

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You may want to check out these related episodes:

Episode 120: The Analyst’s Role in Marketing, with Tim Wilson

We had to see it coming. We marketers have been getting more and more data. From on-premise CRMs and site logs in the early days, then marketing SaaS products and API calls that pipe data in all directions, there’s data everywhere. It goes without saying that we need help making sense of all this data. Most marketers wouldn’t consider themselves natural statisticians. Enter the analyst, who knows how to wrangle, normalize and visualize those data points, and maybe even get it cleaned and dressed for dinner. 

There are marketing teams who’ve got analysts onboard, but it isn’t an industry-standard practice just yet. Some leaders in the analytics community make the case elegantly of how this role helps marketers. And I’d count my guest today as being a vocal advocate for why we need analysts.  

In his day job, he is Senior Director of Analytics at Search Discovery. But that only scratches the surface of all that he does. He’s also a perennial  conference speaker and writer on many topics in analytics.  To me, he typifies how one can be a digital analyst despite having a non-analytics background. In his case, he obtained an Architecture degree before entering the field.

Joining me from Columbus, Ohio, let’s hear from a man who some call the quintessential analyst, Tim Wilson

People/Products/Concepts Mentioned in Show

Episode Reboot:

Check out the podcast which Tim co-hosts, Analytics Power Hour

Glenn & Tim at MeasureCamp NY

Episode 119: Digital Marketing Analytics, with Kevin Hartman

As Google’s Chief Analytics Evangelist, Kevin Hartman is responsible for leading the design, implementation, and evolution of programs and approaches that help businesses around the world realize the opportunities presented by data. 

Kevin has a proven track record of building large, global, high-functioning analytics organizations from scratch and deep experience in leading large profit & loss centers and cross-functional teams, identifying business opportunities, and creating effective marketing programs. He has also written “Digital Marketing Analytics: In Theory And In Practice” which is now in its second edition.

Kevin’s decades of work in the digital analytics space, with most of that time spent leading large analytics teams at a major global advertising agency and Google. He has taught analytics for nearly 10 years at Universities near to his home, such as The University of Chicago, The University of Notre Dame, and The University of Illinois.

People/Products/Concepts Mentioned in Show

Episode Reboot:

look into Kevin’s course on ELVTR

Episode 118: Converted, with Neil Hoyne

Converted, Neil Hoyne

In digital marketing, we’re all striving to do what works. Yet whether we’re in-house or at an agency, we’re basing our definition of what works on a small sample size. Honestly, none of us can zoom out far enough to the general traits of successful marketing. That is, unless you’re someone who’s tasked with measuring marketing data at the organization with the single-largest quantity of it on the planet. 

My guest has gained a lot of insight on successful sellers in his role as Google’s Chief Measurement Strategist, where he has led over 2,500 engagements with the world’s biggest advertisers. He is a Senior Fellow at Wharton and holds degrees from Purdue University and UCLA. And in his book “Converted: The Data-Driven Way to Win Customers’ Hearts” the difference (I’m simplifying here) is that the  best ones humanize their funnels for their buyers. 

“Wait,” you say, “we already know  how to treat people nicely, we’ve known how to do that since humans have been around. You’re right, yet it’s surprising how we lose the human element is when we move commercial interactions online. My guest wants us to learn – or more correctly, relearn how to make our marketing more human. 

People/Products/Concepts Mentioned in Show

Episode Reboot