Jeff Sauer is the founder of Data Driven U, GA4 educator and digital nomad. Travelling across the globe, he helps marketers everywhere become more data-informed; live streaming invaluable courses from digital marketing platforms, marketing strategies and the importance of analytics. Preparing marketers worldwide for a cookie-less future, Jeff has played many roles in his career from building websites, agency-owner, business coach to lecturer.
Jeff is fiercely passionate about helping marketers get smarter about how they use data to improve their performance and decision-making. His practical knowledge and insights about Digital Marketing makes him a Master in his field. Crunching statistics and leading strategies to help businesses achieve their KPI’s and company goals, using everything from AI to your own first-party data.
Read along or watch below to learn from a master’s experience and philosophy of data, and what you should be doing to future-proof yourself including setting up Google Analytics 4.
Jump to highlights
- Tell me about your journey?
- Why is data-driven marketing so important ?
- What’s the biggest challenge for marketers right now? And in 12 months’ time?
- How can marketers convince stakeholders to take a greater interest in their data?
- Has machine learning and AI improved or challenged marketers to get results?
- What should people be aware of about the GA4 cut-off dates?
- What content do you teach in your new GA4 course?
- Where do you see the future of data-informed marketing?
- What’s your definition of digital empathy
Tell me a bit about your journey from an agency owner to world traveller to digital trainer.
Jeff: I first got started in the industry as a general business owner, doing really rinky-dink websites, before WordPress was well-known. I charged a couple of thousand dollars to build a website, which was enough for me to quit my day job. I realised I didn’t know how to get beyond that first contract, so I had to figure out what else I could do. Eventually, I offered internet marketing services – specifically SEO, and pay-per-click ads.
From my humble beginnings, to then becoming a partner in an Inc. 5000 5X firm, I rode the wave of Google’s ‘big thing’, during the time when everybody spent their money digitally instead of offline. Eventually, we had so much work that I hired and built out a whole team of people to work on it with me. Once I moved away from the hands-on everyday tasks, I became less and less satisfied with what I was doing. I think this was because I was selling a product which I thought was an obvious next step.
I got burnt out trying to convince people of the obvious. So I thought, “Screw this. I’m gonna start my own company, with my own product and marketing.” So I did just that. This meant I needed to have a product as opposed to a client list. So, my transition was more of dissatisfaction with client work because I wanted to travel and I didn’t want to work on somebody else’s timeline.
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What are your favourite places to live and work remotely?
Jeff: To me, this is like saying, “Who’s your favourite member of Metallica?” They all have strengths and weaknesses but sometimes my favourite member might be James, sometimes it may be Lars. It depends, sometimes I’m in a drum mood, other times I’m in a guitar mood.
Right now, the places that I want to go back to the most are Italy, Portugal, and Buenos Aires, Argentina.
Woj: Australia is not on the list?
Jeff: This is why it’s so hard because I can’t satisfy everybody with this answer. But I definitely would like to take my family and drive a campervan across the Great Ocean Road, and just circumnavigate the entire Australia.
How has travel impacted your daily life? And why did you decide to settle in Washington, D.C.?
Jeff: When my wife got pregnant while we were nomading, it was pretty clear that we needed a home base. We tried it for the first time in California. We bought a house, lived there for exactly a year, and then we sold it because that wasn’t the life we wanted. Honestly, the best place to live is Northern Virginia. It’s funny, a lot of people grew up here or came here and people either love it or hate it. But I found a lot of people are reminiscent of it. It’s a weird spot mostly for transient people but it’s the most liveable spot I’ve visited or been to in the United States.
How much has being a father changed your perspective on work and life?
Jeff: Pretty significantly. It makes me better at delivering and appreciating work. For example, today I have a lot of work to do, but I know that once it’s done, he’ll always be there waiting for me. Usually when you work hard the reward is money, but in my case, my reward is I get to go home to my kid who doesn’t really care about any of that stuff, he just wants to be around me and it feels really good. So, it allows me to work hard then spend time with him when I need a break.
You don’t really have a lot of opportunities to completely detach yourself from work. It’s hard with devices but when I’m with him, I try to completely detach myself from whatever the rest of the day was. It’s as refreshing as meditating or taking a nap.
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Why is data-driven marketing so important to you personally, but also, holistically?
Jeff: My company is called datadrivenu.com. I went through a whole branding-process and bought a book called “Hello, My Name Is Awesome.” Then I came up with Data Driven U, registered it, and I was like, “This is it.” One of my team members, said, “Isn’t data-informed a better way to put what we do than data-driven?” And I was like, “One hundred percent, because ‘driven’ means that you’re driven to something without considering reality. Informed is a better way to describe us.
The reality is you should make decisions with the right amount of data.
I’ve seen both sides of having too little or too much data when informing decisions. For example. HiPPO’s (the highest paid person’s opinion), who make decisions without any data at all – only their instincts. Or they’re interns who make a conclusion that we made big revenue on the site because the analytics goal states $17 million, but not considering that the data was misconfigured.
Neither of these is right, you have to be somewhere in the middle. It’s a philosophy. Often you need to make decisions based on faith. That’s how businesses start. You have faith that you will be successful in it. You also want to make sure you data as a waypoint to say if it’s working or not. That’s really what it means to be data-informed – to use a certain amount of data to make a decision, not too much or too little.
The reason why you can base your entire career interpreting data is because you’ll never really comfortably know the right amount of data until you have it. That’s why I’m glad to be committed to it because what I do today around data is different than what it will be 10 years, 20 years from now. The techniques and technology will be different but having that instinct and the ability to weigh up qualitative versus quantitative, is an art form that is never fully perfected.
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How important is it to tell a story with your data?
Jeff: It’s the whole point. If you don’t tell a story with your data, then you’re just collecting. Usually, you want just enough information to make the decision and to tell a story. Ultimately, data is the story of how somebody came to your site.
Data is the story of someone’s relationship with you.
So, if you’re collecting data of somebody’s clickstream on a long enough timeline, you can start to piece together the issues your website might have. Data will help you quantify how often that happens.
Woj: Everyone’s an individual so people’s stories are different. It needs to be a communal story, or at least a snapshot where you can gauge and make decisions from.
Jeff: Yeah. When people ask questions about your product, it can be the equivalent of 10 to 100 times of others who think that way. Sometimes you extrapolate from the qualitative story and make it quantitative. Look at how many people went to that page, and how many of those people bought it. That’s a story as well. It works both ways – you can use an individual event to extrapolate up, or an aggregate of people to extrapolate down.
Woj: This is where it starts getting a little bit philosophical. To your earlier point you could pick one from a sample set and go completely the wrong way, and make bad decisions, or it might be a good representative of a whole cohort.
Jeff: A lot of people who are very good at data science lack the common sense to help put that together and tell that story as a real one. Is it feasible or not? And so, that’s usually almost every time that somebody comes at me with a really technical question or a really obscure thing, I apply a common sense filter, and it stops them in their tracks.
Because the reality is, is this real for real people?
What’s your advice to resolve attribution discrepancies across platforms and create a single source of truth?
Jeff: Attribution is only an issue when you have a big business with millions of dollars being spent on media, where you want to optimise the media to choose which one will give you the best media mix.
Back in the old school days, when I first got started it was called a media mix analysis. You’re probably not gonna save much money unless you’re spending $10 million a year on your ads. When you have ads across all media, like TV, print, and so on, you can do a media mix analysis and save millions of dollars doing it that way. You get what you put into it.
In a digital-only world, my biggest problem with attribution is that oftentimes it is more complicated and harder than the money you save.
These platforms change so much that it gives you false conclusions.
For example, if you’re running a Google Ads campaign, and you run a model from data in 2020, and then you compare that to 2021 data, that model is already flawed because there’s so many changes that happened in the ad world that would screw you over. There was the COVID bump and the COVID loss. There was iOS 14 that came out and screwed over everybody. There were all these different things that are going to tell you the issue is something you wouldn’t be able to fix anyway.
If you have a long-term view, or if you’re in the world of TV, that really does make a difference because those placements are a more proven platform. So attribution on an immature platform or an ever-changing platform, makes it even less valuable. So that’s why I’ve always considered that attribution is really a specific problem for a specific business. Probably 1% of businesses would benefit from it, at most.
Woj: Every ad platform has different attribution timing e.g. when the said click takes place or the view takes place. So, comparing Facebook metrics to Google Ads metrics are very, very different. We tend to use Google Analytics as a single source of truth, because at least you’ve got some kind of relative apples-to-apples comparison on the data that’s coming through.
Jeff: Yeah, and I guess I went into the bigger picture. I would trust Google Analytics over Facebook, because Facebook will mislead you, they take more credit compared to what truly ended up happening. It comes through something like a view-through, or they have an attribution window that’s totally different that would never be measurable by Google Analytics.
What’s the biggest challenge for marketers right now and in 12 months’ time?
Jeff: Generally speaking, everybody should be in charge of at least one KPI as a marketer. Usually, the challenge is making sure that you hit your one KPI. If your KPI is search traffic, then your biggest challenge is the algorithmic changes of Google versus the budget you have to build content and links. If your KPI is growing leads from paid search for a local company, then your challenge is rising ad costs on Google’s platform, or saturation versus a low-search demand. Competition is usually the biggest problem with advertisers. If you’re a Facebook advertiser, the biggest challenge you have is Facebook does not give you the same value anymore. They charge more for the privilege of using their algorithms honed in a kleptocracy, as opposed to a meritocracy. Now you’re the one who bears the brunt of it, is that you get worse results for more money because of Apple.
So I mean, let’s just say the biggest challenge for all of us, the common thread is Apple.
The importance of developing first-party data is widely advocated at the moment – what’s your advice for smaller marketing teams for whom this is a daunting prospect?
Jeff: You always want to own as much data as possible. The only thing that you can own is the customer’s email addresses. Even if your audience doesn’t necessarily use emails or doesn’t use messaging in that way, I would suggest having data that you own, or a platform where you can communicate to your customers without having to pay for the privilege. Otherwise, you’re more vulnerable to a platform change – which you can bet happens often. Even if you have a million subscribers, are those million people gonna see your content? I’ve subscribed to a ton of YouTube channels and I never see that content. Why is that? It’s because I’m at the mercy of what the platform chooses to do and how they choose to present it.
Woj: That’s right, but it’s daunting, from the perspective of the implementation, to get the first-party data into the platforms which may be a technical challenge for smaller marketing teams.
Jeff: There’s ways to automate it, Google has Customer Match, Facebook lets you upload a list of customers or you can use conversions API where there’s a little bit stronger signal. But ultimately, these platforms are asking you to provide your first-party data to a third-party system.
Woj: Yeah, straight into their database from yours.
Jeff: Yeah. So what line is crossed when you use your first-party data into a third-party system? There’s no way around it. Because how can you grow your email list? You need third-party platforms.
What can marketers do to connect data, website, ad platforms, email marketing platforms, and broader business KPIs?
Jeff: It depends on how your marketing is structured and the systems you have in place to support your marketing goals. If you looked only at the broader business KPIs, there’s really only two things – Revenue versus expenses. When it’s all said and done, you want a profit, an excess of revenue over expenses. Marketing is basically the Chief Revenue Officer.
Almost no companies work in a way where marketing is purely a profit centre, and they treat it that way. Most of the time you have a sales team that sells stuff and a marketing team which is really more for leads. Part of the reason why these teams clash is because there is a disconnect between leads and sales. Sales says the customer is not qualified and Marketing says you don’t know how to close the sale. It’s part of the reason why a marketing KPI would be different from a company’s KPI.
Marketing KPIs that are not aligned with the company’s KPIs are the reason why marketing teams get laid off all the time.
It’s an expense centre then, not a profit centre.
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How can marketers convince stakeholders to take a greater interest in their data?
Jeff: Marketing is very important. If you don’t have it, then nothing else really happens.
Marketing exists to get other people interested in your product or service. And therefore marketing is creating a market for what you do.
If you create a market, it’s really expensive oftentimes, even creating it ourselves with somebody else’s money like venture capital, we’re best off piggybacking on an existing market. Which is why Google, Facebook, and TikTok, and other platforms are so valuable.
If you were to tell a CFO, “Hey, I wanna create a market, it’s gonna cost me a million dollars.” The way you get him interested in that and giving you that million dollars if you say, “This million dollars will act like $10 million over the lifetime of this thing.” So you have to convince them that it is a return on the investment. Marketers usually look at budget as an entitlement, not as a thing predicted to get a return.
Now, the hard part about return on investment is that the timeline is usually longer than anybody wants to accept. Now, most marketing aims to have an ROI, but most of it doesn’t. And that’s not a bad thing. That’s like the faith part.
Sometimes you just plant seeds, you put yourself out there, and then years later, it comes up and becomes revenue for you.
That happens to me all the time in my business. I don’t charge per minute to talk to people or to help people or stuff. I’ll just solve problems, then eventually it will pay off. The more problems you solve, the more interviews you do, the more time you talk, the better off you’re gonna be, and the more that’s gonna come back to you. You have to realise that not everything is quantifiable. Because people give up faith – it’s a continuously renewed thing.
Woj: Rand Fishkin talked about the power of serendipity. It’s necessary and it’s not always gonna return ROI in an exact scientific manner.
Jeff: The other thing is, it can’t be like a blank check. A lot of marketers think that it should be a blank check with no accountability. They’re like, “Well, you can’t assign accountability to something that we can’t measure.” and they hide behind that. There’s definitely a happy medium between being too data-driven, and being too opinion-driven. Neither of those things are good.
Has machine learning and AI improved or challenged marketers to get results?
Jeff: AI and machine learning are very hungry systems, and they’re hungry for data. The more data they have the better chance they have of spitting out good results. The thing that people misunderstand or confuse about these systems is that they’re not sentient. They’re basically just statistical programs solving statistical problems. And so if you give somebody an input as to anything from a keyword to a bid to a platform to demographics, they feed all those things in there, and they try to spit out the best likelihood of success.
AI works better with big data. You shouldn’t trust a machine with too little data. You need to be at a certain point where it can crunch numbers and do an analysis. It’ll be better than anybody’s manual ability. This is how advertising will continue to evolve.
People will ask: “Well, my agency is gonna go out of business then, why do they need agencies?” The reality is you need somebody that understands how to feed it. So your job goes from being the one who feeds the monkey to being the one who runs the machine that feeds the monkey. You still need to do it. You still need to feed these things in order for them to be able to eat. And that’s the difference.
Let’s talk about the origins of Google Analytics, Urchin.
Jeff: In 2001, four surfers in Southern California were doing client work night and day. Their clients wanted to measure websites and they said, “Okay, let’s create software.” They created something called ‘Urchin’. The software was then bought by Google a couple of years later. Urchin became Google Analytics and evolved through adding on top of existing urchin.js. script, over and over again. Google soon realised that it was untenable that they kept building on this old architecture.
In the 2010s, Google then bought something called Firebase, which is a mobile database and added analytics on top of it. They realised it’s faster, more lightweight and modern than the existing platform. So they decided to rebrand their mobile analytics tool as Google Analytics App + Web. In October 2020, then rebranded again as Google Analytics 4. In many ways it is better, because it was started a decade and a half after Urchin started, but the rollout has not been great.
Google needed to improve on Universal Analytics but there were so many external factors with privacy like the GDPR and CCPA that pushed the live date closer. Instead of rolling out the program in a couple years, they rushed this because they’re getting sued in court every day, about privacy. Google Analytics is illegal in Austria. It’s like, “Okay, well, if this is illegal, how can we hold on to this old system? We can’t change Urchin. It’s built on 2001 technology. We kept on adding on to it and now we can’t.”
We’re all victims because we have to change over. Google Analytics is such a big platform with over 150 million sites using it, but they’re never going to be able to satisfy any of us by migrating. The fact that they’ve given it away for free means they spend somewhere in the hundreds of millions to billions of dollars a year to run Google Analytics. And what’s the payoff of it? The original intent of Google Analytics was to make your Google Ads data more transparent, which it does.
How can businesses migrate their data?
Jeff: BigQuery. It’s supported in GA4 and Universal Analytics 360 -although It’s not supported in GA Universal without paying for it. I’d recommend extracting your data out of Universal Analytics and into a data warehouse. You have access to the API so you can export data through the API. Getting data out right now is not super easy without a developer or a tool. There are some tools that allow you to just export your data and push it into BigQuery but it’s not as easy as a “click of a button” yet.
There’s ways around it but it depends on how much you want to invest in that. Either BigQuery, or another type of data storage, will be something where you can query that against your GA4 data in the future.
What should people be aware of about the GA4 cut-off dates?
Jeff: There’s a few different cut-offs. So June 30th, 2023, is the last day that it will collect data. On July 1, when you log in you’ll see data from June 30th, but then if you log in on July 2, you’ll see no data for July 1. Google will preserve your data leading up to June 30th for at least six months but we don’t know if that is the final date.
There’s other derivatives to be aware of as well. If you want to do yearly comparisons of 2023 conversions, you should have had GA4 on your site before the end of 2022. If you want four-quarterly comparisons in 2023, then you’ll want to have switched by October 1st 2022. Basically, the most crucial date has already passed. But at least you can start fresh and that’s why there’s an urgency to get GA4 in place.
What content do you teach in your new GA4 course?
Jeff: I call it the ‘Cover Your Assets’ (CYA) blueprint. The courses are a live version of GA4 so you can be updated with exactly what’s in there today. When you attend live, you’ll always get the latest version of it. We’re not doing pre-recorded videos or slide decks, we’ll be live in the GA4 interface. So if anybody wants to learn the platform inside out in real time, this is the best way to do it.
You will participate in a small group setting, learning through sessions and Q&A opportunities.The real value proposition is that all you need to do is show up and I’ll teach it to you. It’s only a maximum of 16 hours of your time over the course of a month, so less than 10% of your month and you will be GA4 certified with our program.
What do you enjoy most about teaching?
Jeff: My favourite part about teaching is when people have their ‘aha’ moment. I’ve been in rooms where there are a thousand eyeballs looking at me explaining something that they didn’t know before. Most of my students come from matured careers where they feel like it’s too late to attain proactive knowledge. The most common type of person that I’ve taught are marketing directors who got laid off when digital marketing was launched.
In my teachings, I talk about the language and what everybody cares about.
My ACEs model shows people the most common strategies. If you can get to the point where you are confident to set up strategies, interfaces and explain how analytics data is collected then you know enough to be dangerous. You don’t have to be the expert that does every button push. Very few people in this industry are technical experts. Most of the time it’s the strategy, planning, methodology and execution.
That’s why I love to teach so much because I’m talking to people who just didn’t have the time or didn’t keep up with the trend of digital. I help them rebuild careers. I do most of my teaching in the Twin Cities, so big corporations from Minnesota, where executives came to me without any understanding of digital marketing. And that’s the most rewarding part is helping them.
Where do you see the future of data-informed marketing?
Jeff: The decisions you make are going to be different and a lot of those things are informed by the platforms we use and our strategies. So the principles don’t change all that much. You need to collect an adequate amount of data, match it to the strategy of your company, and decide if it’s working or not. Ultimately that is how it’ll always work. Data should always lead your marketing decisions. That would have been that way 10 years ago, that will be that way 10 years from now. The technology stack will turn over at least once or twice but the principle will stay the same.
Woj: Do you think you’ll be left behind if you’re not using some level of data interpretation and data involvement in marketing?
Jeff: I mean, those who’ve followed that have already been left behind, a decade ago. If they don’t have a data component then they’re dying a slow death. If you just look at the platform adoption, digital advertising is over 50%.
If you have a hole in the side of your business where you can’t even account for 50% of the ad spend, you’re gonna bleed out.
Lastly: I have a podcast called ‘WojCast’, where we talk about the meaning of digital empathy. What would be your definition?
Jeff: Digital empathy to me would be trying to take authentic human conversations that you’d have in person, and to try to make it the equivalent in a digital world. You’re trying to take your authentic self and match it in the digital world.
To find out more about Jeff Sauer’s mastery courses on GA4, Google and other digital marketing platforms, sign up for his data driven courses.
Want to check out more about the Google Analytics switch? Read our blog on Everything you need to know about GA4. Or keep learning from the very best in the industry with some of our other interviews below: