Category: Analytics/AI

Johan van de Werken thrives best at the sweet spot between data, business & technology. 

Graduating with a philosophy degree from the University of Utrect, my guest started his career as a journalist for several Dutch publications, writing about everything from events and  pop culture to media, politics and economics. Around 2014 he switched from letters to numbers, working in CRO for several European e-commerce businesses. That led him to building dashboards and leveraging cloud platforms to turn raw data into usable marketing insights.

Working at an analytics firm that exposed him to BigQuery, he thought about sharing  what he was learning. Seeing that the  domain GA4BigQuery.com was available, he registered it and started posting there as a side gig. It got noticed by Simo Ahava, the founder of Simmer. That led Johan to release the GA4 and BigQuery course on their training platform. As we fast forward to 2023, GA4BigQuery is now a well-known resource for marketers. And its creator is now consulting full-time on data analytics under his own brand, Select Star.  Except for when he’s having fun playing in a punk rock cover band. 

People/Products/Concepts Mentioned in Show

SelectStar

GA4BigQuery

Johan on Medium

Funnel Reboot episode with “Learning Google Analytics” author Mark Edmondson

Definition of ETLDefinition of an IDE

Data warehouses are amazing things: you can toss all kinds of information into them then pull mind-blowing insights out the other end. This feat can happen because you’re connected to outside systems holding their own database tables. A copy of whatever has recently gone into the table is taken out and shot through a data pipeline and pushed into your data warehouse. But today’s data stacks contain Multiple clouds, hybrid environments, and so many data pipelines the programs in charge of monitoring and logging the flows almost can’t manage them. It becomes overwhelming to manually check and ensure the quality and integrity of the data.  The more sophisticated the systems, the more errors creep into the data. If we rely on flawed data, the outcomes and insights we generate will be equally flawed. This is where data observability comes in.

In this episode you will hear about something called an observability platform. It identifies real-time data anomalies and pipeline errors in data warehouses. Now there’s a twist here because we’re in a cloud computing environment that charges by number of computing cycles. You don’t want an observability tool that’s another pipe accessing client data and running up the meter. The good news is there’s an easier way to detect when data has gone awry, by comparing log files – basically  metadata – they are just as effective at alerting you to problems. 

If you’d like what this is doing described in a completely non-technical way, think of Hans Christian Andersen’s Princess and the Pea. There is a girl who comes to a castle seeking shelter from the rain claiming to be a princess. The queen doubts whether she is truly of noble blood, and offers her a bed, but this bed has twenty mattresses and twenty down-filled comforters on it. A pea is placed underneath the bottom mattress to test if this girl detects anything. The next morning, the princess says that she endured a sleepless night; there must have been something hard in the bed. They realize then and there that she must be a princess, since no one but a real princess could be so delicate.

I spoke with Yuliia Tkachova, the co-founder and CEO of Masthead Data, a company which recently received $1.3M in a pre-seed round. Originally  from Ukraine, Yuliia came to found Masthead after work that convinced her of the need for an observability solution. She had roles as a Product Manager roles at OWOX BI and Boosta, where their data solutions encountered problems. Prior to that, she did marketing for RAGT.  She has Bachelors and Masters degrees from Suma State University, specializing in MIS & Statistics. She also serves as an Organizer at MeasureCamp, a volunteer community where analytics professionals come together to learn.

People/Products/Concepts Mentioned in Show

Masthead’s YouTube Channel

Connect with Yuliia Tkachova on LinkedIn 

Splunk

NewRelic

Image credit: Edmund Dulac in Hans Christian Andersen tales

Analytics is something that everyone says they want, and some brag that they can analyze very well. But few people know what investment’s required to build a quality analytics function, and even fewer are good at justifying its value. 

Our guest Martin McGarry is so passionate about analytics, as you’ll see from his  backstory, if anyone can articulate the business value of analytics, it’s him. 

After completing a Bachelor of Science from The University of Manchester and studying at the University of Cambridge as a Doctoral Candidate, our guest worked in the UK analytics practice of a global Management Consultancy.  Due for a change after 6 years of that, he moved to Ottawa Canada and founded his own consultancy so he could offer a more independent approach. A while later started the firm he’s been leading for nearly 15 years, Bronson Analytics. 

In 2018 he began a recurring event in Ottawa called Beer & Analytics, which draws hundreds from the field together for learning and socializing. In 2022, the event went outside of Ottawa for the first time, being held in Toronto. 

People/Products/Concepts Mentioned in Show

Martin’s LinkedIn profile

Machine Learning Expert Andiy Burkov

The Hundred-Page ML Book

Synthetic data vendors like DataRobot

Simulation running, via tools like Simul8

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:

Chapter	Starts at	Speaker (mentioning only first time they appear)
INTRO	3:00	Jim Sterne
GA	5:56	Sheena Green Sara Hoffman Kelly Anne Wortham Kenya Gillette Jenn Kunz
UX/Testing	11:58	Geddy van Elburg Deborah O’Malley Anna Smolina
Process	17:53	June Dershewitz Brianna Mersey
People	20:19	Rachel Heseltine Ali Groepper Lina Mikolajczyk
AI’s impact	23:50	Ryan Levander Mary Owusu
Facing Change	28:48	Anil 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.

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 

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?

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.

People/Products/Concepts Mentioned in Show

• JJ’s agency, Mediauthentic
• JJ’s LookerStudio.VIP
• JJ’s cohort group, BetterThanData
• Google Looker Studio
• Criteo
• NextRoll (formerly AdRoll)

You may want to check out these related episodes:

Episode 9: How Dashboards Make the Whole Funnel Work

Episode 93: Visualizing & Making Data Valuable, with Eric Boissonneault