In this episode of We Rock DM Amplified, we had the pleasure of learning from Mia Umanos, CEO of Clickvoyant. We delved into an array of interesting topics, including the nuances of GA4, which Mia charmingly refers to as the new ‘Dubai’ of Analytics.
We also navigated the captivating landscape of AI – discussing Process AI, LLM AI, and Generative AI – and their powerful roles in data and statistical analysis. Perhaps most importantly, we had an insightful conversation around empathy in marketing – a critical element in truly connecting with our audiences.
Tags: ai, business, chatGPT, digital marketing, entreprenuership, google analytics, women in business
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Daniel:
Welcome back to We Rock DM Amplified, the podcast that amplifies your digital marketing and web prowess. We, your hosts, Daniel Bisett and Tricia Ulberg are incredibly excited to welcome our special guests for today’s episode, the inspiring and innovative Mia Umanos. As the CEO of Clickvoyant, Mia is a recognized trailblazer in the digital realm, transforming the way businesses understand and interact with their online audience. Get ready to dive into an insightful conversation about web analytics, customer engagement, and the future of digital strategies. So sit back, tune in, and let’s uncover the digital magic with Mia Umanos. Mia, welcome to the show. How are you doing today?
Mia:
Thank you. I appreciate being here.
Tricia:
Nice to meet you.
Daniel:
We’re super excited to have you, and the format of this show, was intended to be small business owners come to us to have us kind of break down their current digital marketing strategy and maybe give them some golden nuggets for key takeaways that they could maybe go implement themselves future forward. But lately we’ve just been kind of going rogue and I’m loving the format. And today you do not fit that model Mia. I don’t think you need to come to us for digital marketing advice. I think rather we should be speaking to get advice from you. But, um, this is, this is really incredible. And so a couple of the topics that I hope we hit on today personally, um, are, well, the one that we’ve been talking about on LinkedIn, which is GA4 which we’ve got what seven days to integrate and roll out and say bye-bye to UA. So I want to focus on that, but I also want to hear what else, like how you’re implementing AI into maybe GA4 and how that’s going for you and what you see the future is anyway. I’m just, I’m ridiculously excited to have you on the show. I’m not terrified by GA4, but I really don’t like that damn thing. And I want to talk to you to maybe find some silver linings and maybe hopefully change up my opinion. So no pressure.
Mia:
Listen, there’s a lot of people who just migrated to a paid tool, um, that was like, I just need to get this like simple stuff. Um, like conversion rate by channel. Like where did that go? And it is, it is rough. I liken it to moving to a new country that is non-English speaking. I don’t know if you’ve ever done that, but you just like, suddenly you’re like, okay, well, that’s a store, this is where to get food. I recognize the components of this life, but I have no clue how to communicate in this world.
Mia:
You know, and that’s what the transition of Google Analytics 3 versus Google Analytics 4 is going to be like. And, you know, we’re talking about 70 million websites, 70 million websites globally that had Google Analytics Universal for the last under 12 years since they had first migrated to what was then called, it’s still called med, like the measurement protocol.
Mia:
So now we’ve got 12 years of something that we knew and now 70 million websites are having to move to a new country speaking a new language. It’s painful.
Daniel:
Right.
Tricia:
Yeah, I wasn’t scared before, but now I’m scared. That’s a good analogy.
Daniel:
I love that. I love that analogy, but I have moved to like five different non-English speaking countries and it is intimidating. And I think that’s where I sit right now is in the intimidation space, but it’s also beautiful. It’s also an opportunity to grow. I’m speaking about moving to a foreign country, right? It’s an opportunity to learn new culture and get out of your box. And I know that it may not be in GA4 where we’re finding all of these opportunities. It may be in a new tool, in fact, but. while I’m intimidated and that is the motivating force for the emotion of hatred that I’m feeling right now, I also am aware that there’s gotta be some benefits to this that I just don’t know about and so I can’t get excited about yet.
Tricia:
Yeah, hopefully where we’re moving is like Paris. Are we moving to Paris? Is that where we’re moving?
Mia:
If GA4 were a city, it would be Dubai. That city is like everything they thought of, everything you could possibly be. There was a time where I was flying back and forth from Europe to the Philippines, which my mother country all the time. And in the Dubai airport. They’ve got, you know, like you could take a shuttle into the city if you have a long layover and then there’s this underground like thing. There’s like snowboarding on the dunes and it’s just very technologically advanced. In addition to being technologically advanced, you do have, they’ve thought of every user experience. So they have like McAllen strollers for you to just pick up. You don’t need your stroller. You could take the stroller, you could check it out. You could take it to wherever you want to go. And so. Google Analytics 4 is a Dubai in that it can be that advanced, and it’s a free tool. But somebody has to think about the experience. Somebody has to think about what you’re going to need to design it. And so that’s why it feels complicated. I mean, when you’re in marketing, so you know like, User experience is what makes something great, whether it’s an e-commerce store, an advertisement, going from an ad to a landing page. Those are the kinds of things that are, when it’s executed well, you’re just like delighted by the experience and you just kind of don’t even know. But all the planning that it takes to make that marketing user experience that way, there’s a lot of talent behind it, right? It’s not just like… Like sometimes I’m like, I’m just going to throw out this like Facebook ad because I think that this is a great idea in my mind.
Mia:
Everybody wants to learn about my product. That’s usually what small business usually do. And I am no different. Everybody wants to know about, you know, AI on top of Google Analytics of course. When actually they want to know that you’re solving their pain. I can measure the hell out of a marketing campaign. I cannot create one for the life of me.
Daniel:
Well, you know, that’s the antithesis to maybe me. I can create the hell out of a marketing campaign, and I can I can unpack data. But I don’t like, love that. That’s not my happy. My happy is more in the strategy space, rather than the crunching space.
Daniel:
But I love that you’ve just called GA4 Dubai. I’ve never been. But now I’ve just gone from this, oh shit, space to, oh wow, space. You know, even if it were Paris, I’d be kinda like, well. Paris is all right, maybe a little overrated. It’s got some nice food. I love the language sometimes, you know, but it’s kind of got a quaint feeling to it. Dubai is like a whole other level. And I was not expecting that. So I’m really excited now.
Daniel:
I don’t know if you know about Tricia and me, but we’re instructors for a digital marketing boot camp for University of Texas Mcombs School of Business. That’s one of our side hustles. And if our students watch the show, they will definitely have questions. If they aren’t listening to it, they’re going to be in trouble.
Daniel:
But for someone that’s relatively new coming into digital marketing, or somebody that doesn’t have the lane of Google Analytics and they’re getting these ugly notifications, you need to integrate GA4. You’ve got seven days and counting. What advice would you give them as far as first steps? not just connecting it to your website. Okay, we’re going to assume that they can do that, but you know, building out events in GA4 is a different experience and it requires a bit of a bit of know-how and a lot of thought process. So do you have like a go-to list of events that beyond the default events that you recommend they build or, or what, what do you recommend for someone who’s just having to make this conversion?
Mia:
So this is an answer that no one likes. And that is you have to not start thinking about it in the events that you want to collect. You have to begin with thinking about the questions you have about people and behavior. And this is, you know, I don’t know why I’m in the minority of analytics professionals, Listening is a pretty critical skill to data in general. And I don’t just mean like listening to your manager or a marketing person’s going, let me know how many sessions and what the bounce rate is. Like, that’s not what I’m talking about. I’m talking about what are the business objectives of the company and what are the goals of your customer and all of the things that you build, whether it’s, you know, if you’re an e-commerce and you’re building. filters and a spinny wheel for coupons and you’re building all these things. Or if you’re in like a longer sales cycle, like a software, and you have to do a webinar and you do white paper downloads and all these things, does any of that matter? That’s your question. That’s your actual question. Does any of it matter? And then you go into, okay, well, that’s what I want to know. What are those different questions? Does this matter? It means like, are they mathematically correlated? So when I say, look at, what we normally do is go look at your customer’s website and see all of the bells and whistles that we’ve invested our money in spending on. Filters, coupons, checkouts, the payment platform, after pay, like we’re sharing money with them, we’re sharing money. So all of these things that people have built and invested digital marketing dollars in, start listing out what your questions are. And from then, like saying, okay, these are the things, these are the data pieces that I need to answer those questions. So I think it’s very easy to start out with like, we need data, but it’s like, you need to know what the questions are. That’s where you can help figure out the priority.
Daniel:
I love that. Yeah. Okay. Keep going.
Mia:
The second thing I would say is there are, you know, all the user experience stuff that happened usually on a website. So Clickvoyant’s really good at web analytics, really good at analyzing how people behave. But what we’re usually using it for is like counting. Do you know the term hippo? Like Avinash Kaushik was like, the godfather of Google Analytics. Like back in the day, he wrote a book called Web Analytics, An Hour a Day. And it’s still relevant to a more junior digital marketing student. But that is a, like almost like a round Y2K strategy for digital marketing data. The reality of the world is that we are creating more data like every hour than is in like the Library of Congress. So we have like, some people might have heard about this AI called chatGPT. That all these new AIs that are coming out of the woodwork are really based on complicated data sets. So that’s why GA4 exists is that now it’s trying to comport to this new universe. And so when we talk about like going to Dubai, like we’re, we’re getting into the space where we can know a lot more about our marketing than we ever knew. but we just need to get to a place that’s more futuristic thinking.
Mia:
These are changing around us really fast, right? I feel a little overwhelmed.
Tricia:
Oh, it’s definitely overwhelming. It is changing fast. It reminds me when I first started my first web design job. I showed up to this web design job and they handed me this HTML book. They’re like, you need to learn HTML so I can build this website in tables. Yes, this is aging me. But it was right during the the dotcom boom. Everything was going, you know, crazy. It kind of feels like that in a different way now with all the AI. And you touched on a question I had, which is why did Google Analytics need to change so dramatically? It sounds like it is because of all the technology. That’s what you’re saying? Is there’s so much new technology with the AI and everything that the old platform just couldn’t keep up and they had to completely reinvent it?
Mia:
Yeah, there’s really two reasons, two main reasons. One, the change in consumer expectation of data privacy. So there are components of Google Analytics 4 that allow them to easily delete data from somebody who might have requested it, whereas in the old systems, it wasn’t possible. Now, that’s partially consumer behavior, but also part like preparing for regulatory changes. We talk about these walled gardens going up. Yeah, GDPR, third party cookies, California has like their own CCPA. So the wind is blowing in a direction where we might lose a lot of data, data capability in terms of tracking. But I think that that’s not a bad thing, because what we were using analytics for vanity metrics, we increase conversions, but did we increase visits? What about bounce rate? You know what? None of that matters. What matters is that the data was created to actually give you a sense of empathy for your customers. Data is their conversation with you. You should be listening. You should be studying and hearing what they want versus using it to prove to your boss you did a good job.
Tricia:
That’s so true. Oh my goodness.
Daniel:
So I get the fact that a lot of it is privacy. And like you said, regulations coming down. They’re coming, right? And so I understand GA4 is trying to mitigate the PII that they were collecting, personally identifiable information for listeners who didn’t know that acronym. But how does that impact like re-marketing, retargeting? Is GA4 going to be able to do a better job of it by utilizing these cohorts? And maybe we need to unpack what a cohort is in GA4, because I only kind of understand that.
Daniel:
Is it going to improve our re-marketing strategy, or is it going to ruin it? Obviously, they’re betting on it improving it. Otherwise, they wouldn’t be pushing this tool. But how do we wrap our head around harnessing this more and anonymized data for a re-marketing campaign.
Mia:
Yeah, so some things are going to get easier, and some things are going to get harder, which is the… I mean, that’s actually true all the way around. But when you think about the Google ecosystem, that’s going to get easier, because the other benefits of Google Analytics 4 is that now it will track your consumers across multiple devices. Whereas in Google Analytics 3, it couldn’t do that. So I’m Mia. I came into this. I looked at that Surf Shop’s surfboards on my mobile while I was passing by the store. And then when I came back to my desk, I went to their website and checked out. That’s two different people in the Google Analytics 3 world. In the Google Analytics 4 world, it’s the same person. So that’s beneficial. Retargeting is going to get a lot better. across multiple sessions and across devices in the Google ecosystem. What’s going to get kind of tricky is when Facebook Pixel or like MetaPixels or TikTok pixels and these walled gardens go up, that’s going to be a little bit harder to do. But this is where statistics I think will start entering back into the picture. Because again, when we got into this place And I’m also come from the days where websites were like, that’s nice you have a website. Good for you to, this is the thing. This is the place where we make $10 million annual revenue. That progression of being able to measure digital marketing, and I’m an analytics person telling you this, has led us down a path where we think less creatively about how we reach our consumers. If you can’t measure it, it must not work. I’m sorry, that’s not how the world works, right? There’s a lot of dark social, there’s a lot of out of home social interactions between other people that can never be measured that are usually better. I think the statistics, use of statistics is going to start to become more prevalent because now we’re gonna have to do some things like what you used to do old school when the Super Bowl ad ran, you want to know, did the searches go up? Did the website visits go up? And then you can’t connect that data because it wasn’t a pixel, but I could see in a time series correlation that there was a relationship here. Now the number of people who can do that kind of work is very few.
Daniel:
Well, and that brings me to my next statement. Is it a question? Maybe it’s a question. It’s all questionable, right? Hashtag it depends. It depends.
Daniel:
Is this where AI comes in heavy for that statistical analysis, for the correlation, time-bound correlations that are conceivably arbitrary, but when you look at the numbers and you look at the data sets and you analyze it, there’s almost no doubt. Like there’s doubt, because there’s always doubt, but there’s almost no doubt because we just ran that ad on TikTok. It was set for this timeframe and then we had a spike and now we know it’s working. I mean, but is that where AI is gonna come in and help us? Because you’re right. I’m not… a statistician. I can look at stuff, I can understand, I can build stories, but I can’t do all that math. I don’t want to do all that math. But I can imagine connecting APIs to some AI tool like GPT and say, read this, read that, compare them and tell me the key takeaways.
Mia:
Yeah. I mean, I think that is where all of it should go because right now that is what big companies like Toyota, Salesforce, Levi’s, you know, they have that person to do that work. They’re big analytics teams. And I, you know, I was a director of analytics at Omnicom companies. That’s what we were paid like $300 an hour to do. for like the tip of the iceberg for 20 hours a month, 40 hours a month, you could do that. You can’t do anything in 40 hours a month of data, I’m sorry.
Daniel:
Right.
Mia:
Go search for marketing analytics jobs out there. It’s competitive, it’s like the hunger games to try to get to an analyst who can do this. Like I said, not everybody who has data skills wanna do it to help creep on consumers. For me, I consider this to be really important because the data-driven empathy that you can create for those customers is what makes the difference between for like a smaller merchant, for example, or a smaller customer. Like that’s the difference between making it. and creating like generational wealth, right? Or the difference between even six months runway and 18 months runway. And if they don’t have access to somebody like me, they’re gonna do what everybody else is doing, which is guess, I’m gonna guess. I don’t know. Like there’s no mathematic relationship between this. There’s no mathematic reasoning. I just gotta pick a lane and go. And so when I think about You know, all the AI opportunities. I’m really kind of bummed out actually that a lot of people are focused on large language model as like, that’s all the AI out there. It’s going to help us write this, do this, write that. There’s a difference between, there’s two things. There’s generative AI. So that’s like mid journey making, making creative stuff. Mid journey or GPT. And then there’s process AI, which is do all the repetitive stuff that I don’t want to do. Like, why aren’t we here? Why are we in, why are we focused on artificial intelligence and building artificial intelligence that is the very thing that humans are best at, which is creation. Humans suck at doing repetitive things over and over and over again, right? Why aren’t we building AIs that do that?
Daniel:
I want to put a mark down in the clip. I’m just I’m going to take that human suck and that’s going to go viral. It’s beautiful. But yes.
Tricia:
I love this description of AI. What I keep hearing is, “Am I gonna lose my job? How’s this gonna affect my job? What am I gonna have to change about my job?” And that’s what I keep hearing. It was hard enough, just like you said, to take what we had before–the UA analytics, and figure out how to make that work and how think about the empathy piece that you talk about and how that can help a marketing plan. Now it sounds like we have better tools, but we’re gonna have to learn how to use them! So what do you think about this? What do we need to be focused on? What should we be thinking about in terms of “how this is going to affect my job” and what we’re going to have to change or learn? What are your thoughts?
Mia:
I think everybody’s gonna start to have some vocabulary for artificial intelligence. I think that we, it’s been around, we’ve been talking to Alexa and Siri for forever. We’re just hot right now, we’re just like, oh my God, chat should be, chat should be taking right a blog post in 30 seconds. But we’re already starting to see like. what that looks like. It’s formulaic, it looks like a college paper. There’s no, you know. So I think that having a vocabulary for artificial intelligence and what they do is what we’re all gonna be required to learn. It’s like, okay, a large language model like chatGPT takes input from all the copy that it’s ever read evermore for like the last 20 years. And based on your question, it’s gonna guess. what you, what it thinks the answer is. Right. And sometimes it’s not right. Sometimes it’s not right. Sometimes it makes stuff up in that way. It’s kind of like a horoscope. Right. Like, Oh, it’s kind of hitting on it mostly. And then I believe it. Oh my God, it’s about me. This is true. Right. It’s answering, it’s pretty good guesser, but other things like, you know, Clickvoyant is an AI. It’s a process AI. It takes all that Google analytics data ingested into our system. It might feel like ChatGPT because you could say, I want to improve newsletter signups. And then it goes back and looks at all the data and it comes up with the answer for you. But its way of finding the answer is very different from ChatGPT. ChatGPT will say, well, here’s everything that anybody ever suggested on the internet. Click point’s like, well, here’s what all of the behavior is on your websites and why people, you know, read newsletter, sign up for newsletters. And if you were… work on these DMAs, these age groups, and you’ll get more people to sign up for that newsletter. Very different ways of artificial intelligence.
Daniel:
Something I say to my students a lot is you either have data or you build data, right? And if you have data, then we could use a tool for processing. But if you don’t have data, how do you get started? So that’s one part of it. But the other thing that I say is your data is only as good as your data is good. And so. Um, from a process AI type methodology, uh, are you not, um, potentially guilty of regurgitating the same good data and losing the creativity option because the data isn’t there currently to support it or is there? you know, an opportunity for the process AI to come out of its own box and say, but maybe this.
Mia:
I love this question. I think that this is where my future thinking like, there are no jobs that an AI can take over 100%. And this is again, like I get annoyed that we’re making generative AI because the generation by humans are always gonna be way better, but there are some efficiencies. I think that the AI plus the human and Kate Bradley from lately.ai, she says this, that’s where the rock meets the roll. Human plus AI. because the human is like guiding the conversation of what they’re looking to do or what they’re thinking about. And the AI can then kind of like jar some ideas, writer’s block, creative thinking. Oh, it’s interesting. I wasn’t thinking about an image of, you know, like a woman in Dubai looking like that, but that gave me an idea to do this other thing. Like that’s, I think. how it’s actually gonna work. And as a data person, when I say, I don’t like data for the purposes of measurement, but I do love data for the purposes of research. And so when you get into this like design mode and like design thinking, it’s like, what are the problems? Well, AI can help identify the problems in the data. It might not, it’s gonna be great at that actually, because you’re either. Your typical steps are like, what is a customer funnel? They came here, they look at the webinar, they watch this video, they subscribe to the podcast, and then they converted 60 days later. And across that whole happy path, here’s where all the fallouts were. Here’s who fell out, what DMAs, what language speaking. Computer’s great for that. Like AI is great for that. But the human is great for finding the solution to it.
Tricia:
I love this, especially from a creative perspective. I’m a graphic designer. In college I had an instructor who felt like we were going to be using the computer exclusively and creating all this digital art, and we were going to lose the creativity behind it. And we were going to lose, you know, like the artistic spirit. And then everybody had to adjust. We all use Adobe products now. We’re all on the computer. But I do think having that foundation, the creativity is still there. That’s how I see AI working in the creative space. It’s not going to take human creativity away, it’s going to help us build something better, but we have to know what looks good in the first place to know if what we’re seeing on AI is any good. Same with writing, right? We can have AI write something for us, but you need to be a good writer and have that background to understand if what you’re reading in AI is any good. Do you agree?
Mia:
Yeah, I do. And I’ve heard this, that people say, well, yeah, but the more we train it, the more we tell it, this isn’t good, that’s not good, the more it will get smarter. The more it will get smarter. You know what I’m trying to say. But I do think that things that it’s so my chief operating officer, he has conversations with it all the time. Like he’s constantly asking it like, what do you think about the relationship between like, you know, robust and humans? Like, what do you think is going to happen here? Like, are you getting smarter? Do you feel like you’re getting smart? Do you feel like you’re getting more empathetic? And the response always from GPT is, well, you know, I can’t see faces. I can’t hear voices. You know, my humanness is not possible. Like the thing that makes you human is not possible. Which I’m like, this is a scary conversation. But I think that, like, again, you know, my beef with it, my beef with artificial intelligence focus right now is that we are, you know, using all of our best resources to, you know, try to get it to be creative, when maybe the most important thing for you, Tricia, is as you’re creating, there’s an AI that says, oh, actually, this is gonna create an accessibility issue. Right? Wouldn’t that be nice?
Tricia:
Yes.
Mia:
Wouldn’t it be nice to have an artificial intelligence? So you could spend more time creating versus checking.
Tricia:
I like what you said, how AI can take out the repetitive things, right? And also it can put things together that maybe we don’t, if we don’t think that way, especially as a creative person, sometimes I have a hard time looking at the data and putting that together. But if I could use AI help with that, maybe it can help me focus on the creative. And it’ll make me a more creative person overall, having that taken care of for me.
Daniel:
It might be able to analyze the data and identify a segment in your marketing that is missing from a marketing strategy, but it’s hitting from a conversion strategy. And then you can now go and build creative around that segment that’s more geared to that demographic, that whatever.
Daniel:
And so you can utilize your creative juices. Now it’s evidence-based because you’re like, there’s an opportunity here that we’re kind of missing. But what I was gonna say is we’ve got a client that integrates AI into biotechnology, right? And they’ve got a tool called Pria. And that tool is actually an AI, but it’s a different AI. It’s not artificial intelligence. It’s augmented intelligence. It’s AI combo HI. So it’s AI with human interface overseeing and injecting. And so I feel like. from generative AI, that’s where we’re going to have to land, is augmented intelligence, where there’s a human component helping guide it. Now you said something about generative AI is not your happy because, you know, a human will always be more creative or whatnot. That’s true, but not this human. Not when it comes to like me and my five minute Photoshop. I can go in now to the Photoshop. Is it still in beta and use their generative AI tool and, and create a background in about five minutes. So I could never, ever come up with. And I don’t want to hire someone to come up with it for me because I to keep that cash in my back pocket. So I appreciate generative AI from an end user perspective. But as a creative, to your point, I don’t think it can replace humans. But so back to process AI, I’m really curious. I really like process AI. And today’s conversation has been really eye opening because I don’t, I mean, I’ve known about it, but you don’t know what you don’t know until you know that you didn’t know it and then you know it sort of. And that’s where I feel like I’m at right now. I don’t think I knew. that process AI existed in a way that could be utilized, like you and Clickvoyant, like you all are using it. And now I’m really super intrigued, and I need to go do some more research about your product in particular, and also just kind of how it’s all integrated and working. But for me, process AI, it’s like I’ve seen a lot of things that I’ve never seen before. advertisements and people talking about it. Oh, speed up how you’re doing things in your office and your business. And then I go back and I’m like, well, I don’t do I have repetitive tasks? Do I have a single repetitive task or is every email unique? Is every conversation that I have with my clients unique? Is every task I do unique to that client? Is there anything that is repetitive that I could ever utilized to harness process AI for. And at first, I’m like, I don’t really think so. I don’t know. But maybe that’s just because I don’t know what I don’t know. You know?
Mia:
Yeah, I mean, one of the easiest ways to think about it, especially if you’re a marketing agency or a student thinking about starting your own marketing agency, is the concept of the billable hour, right?
Mia:
And so the concept of the billable hour is like, I mean, and you know, lots of agency models are changing, but it’s like, okay, well, it takes us roughly, you know, 100 hours to deliver this type of work. And that 100 hours is broken up by the project manager, all these different things. Well, if you… could reduce the amount of time. And the agency thing that is always just like, well, margins, that’s our always, we’re chasing margins all the time.
Daniel:
Yeah, absolutely.
Mia:
Also marketing teams and clients are always wanting to be like, can we do this for less time? Like, you’re like, well, okay, human capital plus the billable hour plus thing, it’s a rough game. But if you are able to find process AIs that help you in any parts, project management, emailing. meetings, making those things more efficient, then you reduce the amount of hours, human hours, it takes to deliver the thing, and that’s where the agency margin is. So those are some of the things that I think about. It’s like, if we’re really good at tracking time, which is a pain in the butt for most marketing agencies, and really detailed. And this is where metadata comes in. And I’m just going to say one thing about this in like one minute. The other thing about Google Analytics 4, because we started talking about this, is you can collect so much robust data in there now. I was just talking about product detail page, you’re looking at a product detail page, everybody collects page, price, and product name or something like that. Well now you can make your own thing to say, was the size seven available? Which colors were available at that time? And that can help you understand why people might have fallen out. Right now, the metric is like, oh, for cart to detail. How many product details, page views were there, and what percentage of them added to cart? Well, so much nuance in there that you can start collecting about why, in the user experience, to help inform why this could happen. Google Analytics 3 could not do that. And also, when you get that robust level of data in there, like having a robust level of data in your project plan, like what were they? They were emailing? They were emailing what? To a client? To a customer? to a vendor to what? That metadata is the thing that’s going to unlock AI’s value. You put garbage in, garbage out, but also good stuff in, good stuff out.
Daniel:
Right.
Tricia:
That’s awesome. I just got a question about GA4 from my client yesterday, and can I ask you my question? She is worried, and I think a lot of people might be worried about this, about all the older dat that was collected for years and years in UA going away? Is that something that we need to worry about? Do we need to start downloading reports and saving things or should we look at this as starting from scratch, starting fresh? What would you say to that?
Mia:
Well, no business doesn’t want to know how they did last year compared to this year. But what I would say that there’s varying degrees of complexity in this answer, one is if you were a very data-driven company who was anthropologic about how consumers behave on your websites, then you might want to consider the emergency button putting everything into BigQuery. There is a bit of a cost, but you can find offshore data sciences. scientists in fiber to do it, which is basically taking maybe the last three years of data and dumping it in there. And that means every click swipe, everything that you had previously collected. I would say for the vast majority of companies though, they’re probably fine with exporting just like the last 24 months of data sessions, conversions, conversion rates, like just get the very basic thing, like I just want to know how I did last year in terms of channel. country sessions and conversions. Do that in a Google Sheet and they’ll have it. That’s pretty simple.
Tricia:
So just the basic metrics, because it’s going to change so much, and we’re going to be looking at data in so many different new ways. Yeah, okay. Yeah, that makes sense.
Mia:
Yeah, it’s really just like the complexity. Like some signals for like the BigQuery solution is like, I have an analytics department that has more than three people. I have my businesses more than, you know, $10 million in annual revenue. Like that might be that option. Most others will suffice with Google Sheet downloads.
Daniel:
Right. There’s not an import feature, is there, in GA4, where we could import that Google Sheet, the basics.
Daniel:
You’ve mentioned empathy a lot, Mia, and I’m guessing that that’s one of your key differentiators from your value proposition or how you sell your company or… just you and your brand, personal or otherwise. And that resonates. I really like that you are in that space. When the social dilemma came out a couple of years ago, as a digital marketer, I had a C to J moment, a come to Jesus moment, right? With like, am I okay? morally, ethically, myself, personal me, am I okay working in this space? And then extrapolate that even further, am I okay teaching others to do this? Right? There was a real big question mark that show, because I mean, I kind of already knew, but I didn’t really know until it was in my face. Um, and one of the things that empowered me to, to feel confident and staying and continue to teach was that, well, now maybe I’m in a space to guide others towards ethical marketing strategies. And while empathy is not necessarily ethical, right? That they’re not mutually. exclusive. They’re not the same. They are mutually exclusive. Whatever. They’re not one in the same. I do feel like there’s a symbiosis with the two. And that’s why I’m not big on, or rather I’m anti using time constraints for marketing purposes like get it today before uh, x hour or you’re gonna lose this 20% off. I really am anti that strategy unless there’s a genuine urgency. There’s a plane that’s leaving in 65 minutes, there are three seats available, you buy them for $20 now and you go on that journey or you don’t and you miss it. That’s a real sense of urgency. It’s like, it’s gonna go, right? Empty or not. But fabricated urgency model strategy, I find problematic. So how do you tie in the GA4 to empathy? I mean, you said listen. I get that. How do you incorporate GA4 with empathy? Because I want to do that, whatever that is, you tell me.
Mia:
I love this question. Thank you. Thank you for being a marketer that you are and for asking that question, because this is the difference between measurement and research. This is the difference how you use it. Space comes down to how you use it. Are you trying to measure yourself, measure people, measure likes, measure clicks? I mean, we all know what that does to teenagers. Think of business as any different? No. then you get motivated by the clicks. You get motivated by the visits. You get motivated by, yeah, maybe a business should be motivated by money. But when you’re going it to the point of like, I say this a lot, the root of the word data means to give in Latin. And when a customer is giving you their clicks, their swipes, their video views, their form fills, they’re giving you an opportunity to listen to them and why they’re doing what they’re doing. And you, marketer, have a responsibility to listen, to make right time, right place, to be relevant. And that’s the value exchange between leaving your data behind and trying to receive a message. So if you wanna bombard me with coupons for, buy now, buy now, this sandal’s on sale. It’s like, hmm. You know, are you really listening? You’re really listening to me? You’re really getting to know who I am? That was the promise of big data. The promise of big data was to do that, but we just got into these habits of using big data to exploit versus then to learn.
Daniel:
And help.
Mia:
So yeah, you could use GA4 to do both, frankly, but I’m in camp empathy.
Tricia:
When Daniel was talking about The Social Dilemma Documentary, what I remembered about that documentary was that it had a lot to do with social media, right? And I am wondering how social media might change given AI and the way things are going. Do you have any opinions? It feels like things are already changing a little bit. I’m just wondering what the future of social media looks like. What are your thoughts?
Mia:
Oh, well, if you’re asking me that, your question is actually, what do I think Web 3 is going to do for social and digital?
Tricia:
Yeah, yes, that is it.
Mia:
I really believe that there is a lot of, you know, I mean, the gaming industry is so, you know, if you’re not part of it, it feels like a subculture, but the reality is it’s like one of the big, I mean, it could be the biggest economy in the, in the world. Gaming. Um, and you know, the virtual, virtual natives, virtual natives, um, people who like put on an Oculus and actually like, now you’re talking about not just clicking in and seeing like filters and swipes of, you know, this type of shoe online. Now you’re talking about like, let me go there and like, try to pick it up and look at it this way and that way. And. Let me interact with LeBron James talking about, you know, like that to me is going to be a new future of what social will look like. But I do think that it will be something that pushes a lot of people to interact in IRL because I just talked to somebody who said, oh yeah, I turned off all my dating apps, you know, 24 year olds. It’s like, it’s just not conducive. I actually turned it all off. And I said, I’m committing to meeting. meeting people in real life and trying to find dates that way. Because all of my friends say that the dating apps make me feel more lonely.
Tricia:
I hope things are going that way. That is interesting for sure. I have teenage kids and especially during the pandemic, all they were doing were communicating online and they weren’t having that face-to-face interaction. And I saw what it did to their social life for sure. And that I think that is the biggest concern, right? And so that is interesting. Hopefully it is pushing us to value, maybe that’s what you’re saying, value face-to-face interaction more.
Mia:
Right, and I think that also when you get into a virtual space, I don’t know if you have an Oculus, but you know, we have one. I have kids who like to play an Oculus, and I go in there and I’m like, oh my God, you know, this rock climbing thing, it’s beautiful. Like, I do want to go there. You know, when you can go experience something in a visual space.
Daniel:
You can go to Jurassic Park.
Mia:
You could go to Jurassic Park, but you also feel like, you know what? Let’s go to Hawaii. Let’s go see that. Like I could, I could, how I saw and felt in this environment makes me, gives me more impetus to try to like strive for that IRL experience. I think that that, you know, could be the way that it is going.
Tricia:
I hope so. I hope you’re right.
Daniel:
So back to GA4 for just a minute, and then we probably need to wrap this up here, because I’m sure you’re very busy. So thank you for taking your time out. With GA4 and empathy in particular, what metrics… would you say what two, three, five metrics? Would you say help us best empathize with our customers? And how do we harness that NGA for?
Mia:
Yeah, I mean, we have to get hyper focused on conversions. OK, start there. It’s always like bounce rate, content, page views, sessions, users, how many? I mean, it doesn’t matter. Start with the conversions. Who does it? Why do they do it? Where do they do it? If it’s like, Oh, a lead gen, you know, like, where was the button clicked to go to that form? Was it on your blog post about digital marketing analytics, or was it from your home page where you have a video on how to use the tool? This will start to help people understand why people convert. That’s the number one question you should be asking. Why do people convert? So look at the conversions metric, and then what I call metadata. So there’s metric and dimensions. A metric is a count of thing, and a dimension is a thing that describes that count. So it’s like, okay, my count is the conversions. Now, channels is a dimension, what channels are converting, what states, our cities are converting. Think about why, you know, those lead to other questions like, well, let me look at the demographics in that city. Look at the ages of people who are converting. Starting from there, conversions only and then the dimensions is great. But the other thing is, you got some of those dimensions you’re going to have to collect. So things like, was that size available on the product detail page? Did somebody download that particular white paper and the name of it? So those are the things that GA4 is a little tricky to architect. If you guys have a leave behind, we have sort of a base implementation guide for GA4 that we just kind of give everybody out for free. So you can download it from our website. I can give it to you to email out to your audience. But that’s a good way to think about collection. But the metric, conversions, and it’s just get anthropologic about all of the dimensions you can study about that.
Daniel:
So something I really like to do…yes, I like to focus on who’s converting and why. I really like to focus on the low value data because I wanna know why aren’t they converting? Like, what is the key differentiator? Is it because we had something that was compelling that drove them to our site? Something resonated. and then crickets. Why? What happened? Was it miscommunication? Did we offer something that we’re not really actually offering and was that intentional or unintentional?
Daniel:
Because those are all of the lost opportunities. the ones that are converting, yes, we want more of those. We want to focus on those because money and whatnot. But I feel like if we pay attention to the low value visitors, they can also tell us a lot about. how to be better and maybe not to be in their space because it’s a miss and we don’t want to have that negative brand equity because they’re like, yeah, WTF is this, why are you in my space? I don’t need to be here.
Mia:
Yeah, yeah. Where we see that a lot is the Clickvoyant blog, for example. Like I can tell you all about my data, like the Clickvoyant blog. It’s like people are coming in to sort of check things out. The, our number one blog post is how to sell in analytic services to your client as an agency. It is like the number one blog post. Like it’s, it’s actually like the top landing page next to the homepage. What do they need? How do I get so used by value? And you know, they don’t, it doesn’t convert, but it is definitely, yeah, the answers that the non-converters provide you are things like. this is a problem and a pain point for agencies. And they’re not quite ready for Clickvoyant right now because they can’t sell it to their client yet. They haven’t figured that out. And so all of the things that you could do to help them on that path. So like, you know. We’re an early stage startup, so I don’t really have time to build that more. But I was like, oh man, we could do like an agency training bootcamp. And so it’s like, actually from that spun out an agency partnership. So it’s like, oh, well we have an agency partnership where like you, you know, you’re a reseller and that we teach you how to sell it. And that’s, you know, those are some interesting things because it might not, you’re right. Like when you study conversions, you know, why you’re getting customers and you can kind of find more of them. But the non-converters present the opportunities for like upper funnel type stuff.
Tricia:
And maybe we will have more insight into that with GA4, right? Maybe that’s what that’s going to help us with. It’s exciting.
Daniel:
Mia, before we close out this podcast, first and foremost, I want to thank you for agreeing to come on our show, knowing really nothing about us, and for the very, very many golden nuggets that you have presented primarily with GA4 and empathy and process AI. I mean, they’re innumerable. We’re gonna have a fun time unpacking this conversation. But before we split off, I’d like to ask you, is there anything like one key takeaway that you can offer? Let’s pitch it around GA4 because that’s kind of where we started. So it’s a good place to end. For small to medium-sized businesses or new digital marketers coming into this space, or actually, I guess we’re all in this together now because we’re all having to come across…so maybe even the old-school UA users who were very happy. Thank you very much over there and now they’re being forced to migrate. Is there one key takeaway or piece of advice that you might be willing to offer us?
Mia:
Yes, I think you started out at the very beginning, Daniel, talking about how hopeful you feel when you’re in a new country, how excited you are about the possibilities and how you’re in a unique place to grow. It’s where we all are right now. And if we can approach it with that positivity that you express of moving to a new country, then we can really start to imagine the possibilities of what GA4 will do for us, not try to get GA4 to comport to what we already knew. That’s the worst American vacation, by the way. And you can see Americans in Europe saying oh, there’s no parking. Why do I have to walk so far? Where’s the air conditioning?
Mia:
You don’t want to be that American in Paris, right? You want to be the one in the country embracing it, thinking of the possibilities. And so GA4 is that way. Don’t try to compare it to what you already knew. Get in there. Speak the language. Think of the possibilities, get excited, because that’s the world that Google is actually giving you, for free, for free. If you just take the time, put in the reps, put in the hours.
Tricia:
I love it. It’s a good perspective. And these are exciting times. They really are. Well, we might be nervous, but we’re going to look back on this and realize we are lucky to be living during these times as digital marketers, right? It’s exciting.
Mia:
Yeah, it’s exciting. It’s overwhelming. And take a break sometimes.
Daniel:
I tell my students is because of this transition, Google has leveled the playing field for new-to-market digital marketers, because all of us are now on the same. landscape having to learn the new product. So it is truly an exciting opportunity.
Daniel:
Mia, thank you so much genuinely for coming on this show and being part of this and filling me with excitement and enthusiasm. I really appreciate you and what you do and how you do it.
Tricia:
Yes, Mia, it’s been so great talking with you. Thank you so much for being our guest.
Mia:
Thank you both. Bye.