Dan Antonson: Data Analytics

IVAN STEGIC: Hey, everyone. You're listening to the TEN7 podcast where we get together every fortnight to talk about technology, business and the humans in it. I'm your host Ivan Stegic. In this episode of the podcast, I'm talking to my colleague and fellow Internet of Things Enthusiast Dan Antonson. By day he is a marketing technology manager at Collegis Education, and by night he works with Google Analytics, SEO black magic while outfitting his dog with the Fitbit designed especially for canines, a Fitbark. Dan, welcome to the podcast.

DAN ANTONSON: Thanks for having me.

IVAN: It's going to be a great episode. I am so looking forward to talking to you.

DAN: That makes two of us. I'm really excited to be here. Thanks for having me.

IVAN: When I think of you, I think of all the things you do during the day, the things you're busy with in the evenings, your interest in the internet of things just like I am. And I see a lot of overlaps, but I want to give you the chance of describing who Dan Antonson really is.

DAN: So by day. I am a marketing technology manager, which means I get to play with a ton of really cool tools from Google Analytics to Tag Manager to business intelligence tools. And and by night I come home to my office where I play with all of my internet-connected devices, things that I find interesting and just data and just I am definitely a geek when it comes to those things. But what I love about it is I get to do it during the day and the night.

IVAN: So it sounds like you're actually not working during the day. You're kind of playing.

DAN: I definitely like to think so. I have a couple of colleagues, I just had a one-on-one with one of my co-workers today, and one of the questions I asked her is I just want to make sure you're having fun because in marketing with all the different tools and with all the different technology, I mean not everything has to be fun, but you definitely want the majority to be fun. So yes. I am definitely during the day having fun and at night having fun. Just a lot of fun in general.

IVAN: That sounds like a great place to be. So you do you spend your day looking at data then, or are you spending your time in other ways as well?

DAN: So I definitely am looking at data. I'm definitely looking at the output, but I would say the larger chunk of my days is really in the world of what I'll call data collection, and I think so often we think of you know the tools that are generating data. Whether it's the website. Whether it's Google Analytics. Whether it's I mean data's everywhere. There's no shortage of it. I spend a lot of time on the data collection where you know are we collecting the right data from the tools? Are we pulling in making the right connections and are we answering the the right questions? And a lot of times the questions that you can answer really comes down to collection. I think data collection is is underrated so data collection data connection. Those are really where I spend my my time, and then you know of course looking at the output. There's a lot of satisfaction there, but I definitely consider myself as somebody more behind the scenes, operationalizing data that way, then I am as a true analyst. I love insights and analysis, but I get so much satisfaction on the collection side.

IVAN: Can you remember the first set of data you ever collected?

DAN:Yeah, so I got my start in analytics about almost 10 years now, which is it sounds crazy to me when I say it out loud. But I got my start in web development, and I actually consider myself an accidental analyst so throughout college and throughout my education I really put myself through school through doing websites for small businesses in the Twin Cities area. So my brother and I we had a little web development shop, and I learned a ton. It was you know the early Wild West days before content management systems were you know what they are today. And I remember having a small business was like almost like the construction space I built this website and of course it turned into you know, I want to make this button bigger, I want to redo the navigation and then those days you know those things were all done by hand. There was no content management system to make those changes, and so in almost in frustration and actually think the best ideas come out of when somebody is frustrated, but what I ended up doing was installing Google Analytics. I had no experience with it. It was actually was Google Analytics was just coming out of Urchin. I really got hooked. You know I used data. Not as a weapon not as a shield, but you know I wanted to make the websites I was making better and as soon as I saw what was possibleI fell in love. I got more satisfaction. I was having more fun looking at that data than I was building websites, and I kind of made a conscious decision to try to move my career that direction, and it was one of the best decisions I ever made.

IVAN: Why do you think data is more interesting to you rather than development?

DAN: Development to me, and I have so much respect for web developers and programmers, and you know I don't consider myself either one of those. But for me what I what I loved about data was the combination of things. Don't get me wrong. I definitely take satisfaction in beautiful websites and being part of that that production, but for me data is a symphony. It's all of the pieces coming together. You know there would be no web analytics without digital analytics without the website or without media or without strategy or campaigns and so for me data was was all of those things coming together and kind of at the intersection of technology and marketing. I'm just fascinated when those things come together in a meaningful way. I love being part of the catalyst then I guess that the infrastructure all those things are important, but I just I just love when they come together.

IVAN: And part of them coming together is doing not just the collection but doing the analysis and the strategy before, and after and then making sure you collaborate with your fellow teammates. When it comes to data, though, I often used to think, and I don't know if you know Dan my background is in physics, and so I spent a fair amount of time in a lab actually taking data, and then trying to come up with what that data meant. And so the question I think is, when you've collected all this data, you would expect that there is maybe one truth or maybe not. So the question is of all the data that you you've collected on a project for example, do you expect to get one truth out of that data, or do you think it's dependent on who the analyst is and what that data is saying dependent on the person who's analyzing it.

DAN: I absolutely love that question. So firstly I didn't know you had a background in physics. That's super cool. We'll have to geek out on that on another podcast.

IVAN: I’d love to.

DAN: I'm sure you would. Back to your question. I think that's actually what makes marketing and digital analytics data, so hard, but also so interesting at the same time. I heard your question. Is there a right answer when it comes to digital analytics data, or is there a truth? Is there an ultimate answer? There are absolutely are answers there, but you're absolutely right it completely comes down to the individuals making the observations and their experiences and their biases and there you know initiatives or prerogative. And it's actually funny because I didn't grow up wanting to be an analyst. That was not what second grade Daniel thought he was going to be doing you know when he got older, but actually my mom is an analyst. She's a senior analyst with with a major airline, and she's bounced all over that space and that company in that industry. You know airlines being an airline kid you know they go up and down there laying off they're hiring they're laying off, and I'm at one point my mom was at a transitional phase. You know she of course knew what I was doing and we she's actually my Excel Guru. I reach out to her when I need something for with Excel.

IVAN: That's cool.

DAN: Right so it's really funny at work when I have a challenging Excel problem, or somebody comes to me, and I'm like I don't know the answer, but I bet my mom does. So I ended up giving her like a little onboarding session and showed her what I was working on and what I what I was doing. And you know giving her some tools and some resources for her to get started if she if this was a path that she wanted to go down. And it was really interesting to me. We got done, and she's like, ok, let's go back to this and I was showing her you know conversion rates, and you know optimization strategy, and she's like, but how do you get the right answer? How do I check my math? I know my work is right, and I think to physics right like that's what you were I'm assuming you were doing with the data is looking for ways to validate it. I don't want to suggest it's all binary. But I'm sure a lot of it is and and when it comes to web data and customer data, it's so much more fluid than that. Just the collection mechanisms are just so different and the objectives in what you do with it really depends on who you are, but I do believe that data giving you an answer at the very least it should at least be shining a light in a direction that you should go. Doesn't necessarily have to be right or wrong, but hopefully at the very least it's giving you direction on where to go next what to prioritize next.

IVAN: I think there is a parallel between kind of scientific data collection at least ones that I've experienced in a lab and the data that you've been talking about. You kind of use the analogy of a light shining a direction, and when I think of lab data I actually don't think of a single absolute answer in any measurement I've ever taken. I always think of them as points on a curve, and I think of the most likely measurement being the one that is in the middle with error bars on the side. I think the analogy to what you just described is the you know the ultimate answer is maybe that light that's shining and the error bars are the kind of the variation that depends on the analyst who's looking at the data, and what their experience and opinion maybe is.

DAN: Absolutely. I think a lot of well, I look at them. I look at conversion rate optimization. Conversion rate optimization is a really good example of how that like scientific method in marketing can be applied right? It's a true experiment, and I think that's a good example where that that happens, but I think a lot of where you do get the you know margin of error confidence interval like you know that type of experiment that type of data, but when you look at data like Google Analytics where you know a lot of Google Analytics data that's collected in just because you can, right? You don't really know what you're going to do with it later, but you're hoping that you know when the time arises or when you have a question or you want to know how to prioritize your marketing dollars, you can rest or find at least some sort of direction there. So I do think there's definitely different types of data in marketing and it's an important distinction. But yeah, I mean absolute answers and checking your math sometimes and analytics it's hard and especially when you start thinking about the inherent flaws of the collection system where you're dealing with cookies you're dealing with browsers. You're telling with IE8 right? You probably weren't worried about that in the lab at least. I hope you weren't.

IVAN: No, no we weren’t. So your experience has been as a developer you have some experience being doing some work in SEO, and that's obviously informed the work you do today in your job as a digital analyst. If there's someone out there who's doing a similar job than what you are that maybe just started doing that and doesn't have you know 1990s and early aughts experience of development and SEO to rely on, how do you think your experience informs of the decisions you make in the analyses you come up with differently compared to someone who doesn't have that?

DAN: You know I think of the experience has has definitely taught me a few things and I think the biggest learner the biggest thing that I'm thinking about especially recently is just a recognition of just the whirlwind that is technology and that is marketing. There are so many tools out there. There are so many email platforms, website content management systems, advertising platforms, tag management systems, pixels and personalization, and there are just so many widgets, and you know whether you're a large organization, or a small one, there are all of these questions just around just general prioritization, and so you know if anything somebody getting started, what I would encourage them to really do is like step takes that back sometimes and really look to see how your work fits into the bigger picture and really try to assess and prioritize where where you fit in the project or where you fit in the initiative and then thinking about just like what what is the real priority here. When I first got started and web analytics and a lot of the conversations I had when it whether it was like web development, or you know even SEO, should we be there should we add keyword should we rebuild this page should we create a new website? How about a subdomain, what about ecommerce? And I think something you know one of the most important questions that you can help your help answer whether it's in analytics or just in life or in general is just to recognize that whirlwind is real and figuring out and helping others around you prioritize what is important. That's what I think data especially today does a really good job at and it's not a I think a lot of people want data to be web analytics to be really sexy and sophisticated, but a lot of times just knowing where to prioritize your efforts is just half the battle and don't lose sight of that because trust me when you get into a into the weeds with a tool which I love the weeds. I love going into the weeds on a tool, but don't get sucked into the rabbit hole no matter what it is, and that's something that I think comes with time too, but just recognizing the whirlwind having empathy for the people around you in the projects they're working on and just figuring out where do you steer the ship because this ship often moves slower than you think it does and starting to prioritize now will only pay dividends in the future.

IVAN: I want to take a step back. We've been talking about in a data collection most of it is focused around the things that we as humans do on the internet and our interaction with technology during the day, maybe a device maybe a door open in the home and our home automation is tracking it, I want to look a little bigger than that and think about the data that we have in the world that maybe we don't have a whole lot of experience with on a daily basis and ask you the question, how do you think data has affected us in the last year or year and a half compared to the last to a year the same set of days so it may be over the last year compared to at the turn of the millennium? How’s data different, and how is it affected us differently, or has it affected us differently?

DAN: Yeah, I think your question is really centered around like, data and technology really coming together, and how is that connection different than what it was before and I think they're thinking a couple observations I have and then I can give you an example of where it's real. Number one, I think when digital analytics and web analytics started and when I when I talk about data collection in the early days, it was really truly all you know how do I measure a browser? How do I measure activity on a website? How do I understand how people are using my website, and then how do I use the data to optimize that experience. Regardless of what it was for or whether it was trying to get people to fill out more forms or buy more stuff. You know digital analytics was all about measuring activity on a screen and then over time we got more screens. We got phones and tablets and then digital analytics turned into you know measuring those interactions. And tying those together, then it was a cross-device problem right where how do I know this is the same person across these devices and those are still challenges that we we have today, but I think where things really feel different to me now, and it's exciting to me, but it's also terrifying, it's not just screens anymore. It's what are we doing in the real world and how do we connect our actions offline with the actions that were doing online? Now I'm not just tracking an ecommerce store, I'm tracking and connecting digital behavior to offline behavior. And that's something I've been I've been working on for a few years. But an example of where this is really truly coming to life is Amazon's new Go Store. Is that what they're calling it? Have you heard of that the Go like where you're able to walk into this store and take stuff off the shelf. Do they call it the Go? I don't even know what they're calling those.

IVAN: Yeah, I think it's called Amazon Go, and they had it, actually a friend of mine works at HQ in Seattle, and he's used it, and he just was beaming about it loved it. It was just really freaky to be able to walk into a store and get what you need and walk out, and I believe I think you were going to allude to the fact that they just opened it up for general use outside of just Amazon employees.

DAN: Yeah, exactly. Think of the opportunity for Amazon here, you know not only are they tracking. Of course they're tracking what you're purchasing and online and they're recommending products, and they're delivering them super fast. I mean that's actually a pretty easy measurement experience. You know to measure the Amazon website. You've got a product page. There's a cart. You can add stuff to the cart. You can either buy the stuff or remove it from the cart. I mean, that's that's very cut and dry. Something we've had figured out for a while and then with the signing into an account, you know I can tie your multiple devices together, and I can learn a lot about you, and I can optimize around that. But now Amazon has now that same account that you're using online is being applied in a physical environment and in a way, that's so convenient it doesn't feel creepy. So you know your colleague who goes into the store think about it, their data collection is so good and so robust that they're so confident in it that they allow you to just grab whatever you want and walk out the door. Well, don't think that they're not measuring the product that you pick up and and sat down. Think about it so so and then think about what that that profile would look like. Now, I'm probably on the other spectrum for privacy. I mean privacy is important it always will be and so don't get me wrong. I'm not an anti-privacy person, but you know at the same time Amazon is using this data in such a such a way that that feels so convenient that you're willing to give up that privacy. Amazon's going to know every person who steps foot into that store whether they buy something or not. So that's what I think is really different today, is that that online and offline world is coming. It's all going to be one experience, one data set. It isn't just about websites anymore.

IVAN: And so it should be right. I mean we live in the real world. We use these devices online which are effectively the real world. Why shouldn't those things be connected? And I would I would guess that Amazon rolls it out to Whole Foods next, that Go is just a first step for them to test it, and then it goes to Whole Foods, and then and when that happens boy Target and Best Buy and all the other large corporations and companies that are are selling things in the grocery stores there going to be behind.

DAN: Absolutely. I mean and that's what I think is really I think Amazon is really showing the practical application around data. Their Amazon Go store is really just truly in all purposes just a, we're gonna use our data analytics processing to allow people just to come in and get what they want and leave, and we're not even going to look at that data. Well you know it has nothing to do with insights. It has nothing to do with you know this amazing epiphany of like consumer behavior. It's just using pure processing power and image recognition and AI and data all of these things just to make an amazing customer experience. There's only going to be more of that in the future. There's only going to be more. There's it's only going to be more of that. And as a consumer that sounds amazing to me like that the future is now.

IVAN: I know we're living in the future Dan. It's just amazing to me as well. I think I feel the same kind of excitement that you do.

DAN: And Amazon is the big is the big player naturally, but a lot of these a lot of these technologies will I guarantee you they will find their way into you know smaller venues, and and the technology will be not fully democratized. I don't envision Amazon selling this technology or maybe they will. But you know that I think that's the story with marketing technology in general and when you look at that marketing technology bubble chart of all the different vendors who are offering email and content management systems, and so you know it's like I said when I first started in web development you know content management systems were a luxury, you had to build those things yourself. They just didn't exist and then. Slowly an open source technology kind of paved the way and got bigger and bigger and bigger and you know pretty soon you know WordPress dominates an open source virtually free technology. Google Analytics a virtually free technology, run by even another company becomes cheaper and more accessible to to everybody. So as much as it feels like Amazon has a monopoly and even Google it feels like they have a monopoly on search. I mean think about what Google did with that. They took their search engine and then turned it around and gave people an embeddable search bar for their own website, so it's only a matter of time before this technology leaks out to everybody else. It's exciting to see the first iteration of this come to life in a very real way.

IVAN: Isn’t it great? I just love it.

DAN: Me, too.

IVAN: So in the intro I mentioned that you outfitted your dog with a canine Fitbit called Fitbark. I want to kind of pick your brain about what first what made you what made you consider doing that you mean you effectively have an internet-connected dog. But before I before I ask that question, do you think your dog is going to be able to walk into an Amazon Go store and pick up its own food for you? You send it off over to the store and it can come back with what you need him to have?

DAN: Prime for Dogs is like the perfect like April Fools gag that for Amazon. Amazon if you're listening please give us credit for that one. So the Fitbark. I will fully admit I'm a complete gadget guy. I just love gadgets. I've got Roombas, I've got you know door sensors. I've got window sensors. Raspberry Pi's and routers and just I love it. I love to tinker and the Fitbark was somebody had passed along to me is like check this out, and as soon as I saw it I'm like I have to have this. I just can't resist, so I bought this Fitbark for the dog, and actually it's what's really interesting to me is I care more about the Fitbark than I do about my own step counter. I know when I don't walk at the oh my Fitbit or my watch buzzes. Ya my watch buzzes and tells me. I haven't got up for an hour, and I'm like yep I know. Exactly mute and and with the Fitbark, it's so interesting to see the dog being like restless at night like and so they actually have shown like with Fitbark it's they've done a really good job of like crowdsourcing this data to figure out like how active are breeds. You know, what's a normal activity level for this breed at this age? They’ve done a lot of really cool stuff, but one of the things that they found was that one of the biggest indicators that your canine pal is not feeling well is if it doesn't sleep, and if it's restless sleep, and one morning I ended up getting a little alert that my dog Miko you know had a rough night of sleep, yeah, she was having allergy problems, and then that's when prompted our vet visit, and there's countless stories of that online because you know your dog can't speak. So why not trap a Fitbark to her to figure out what she wants.

IVAN: That's craziness. It's also great that you can intervene on your dog's behalf earlier, and then I guess you would have otherwise been able to.

DAN: Exactly. I have a ton of respect for I love what they're doing and I think I that when I was first telling you about my Fitbark you know it's a lot easier to give your dog’s data away than your than your own. One of the applications that Fitbark is doing which I really admire is that they've teaming up with veterinary clinics and as a service, or as a bonus for working or being a customer with this vet, you feed your pet’s Fitbark data to them, and then they monitor it, and then they will automatically alert you, schedule appointments, they feed that data into a marketing automation tool, and hey as a customer of that, now I didn't get my Fitbark through my vet, but if I did, what an awesome service. I mean that to me is not about web analytics or trying to reverse engineer this goal path, or just you know trying to get people to do something they otherwise wouldn't have, it's just using data using technology using the tools at hand to create a marvelous experience whether that's with your with the with dog data or with Amazon Go or with you know a Google search bar embedded on your website. I mean this technology is all about convenience, and it's just going to be more of that in the future and that makes me pretty excited.

IVAN: It makes me excited as well, really. Dan, thank you so much for spending a time with me and for sharing your thoughts and you experiences on the podcast. It's really been a pleasure to speak with you. I really appreciate having you on.

DAN: My pleasure. Thanks for having me.

IVAN: And I hope that we can get a chance to maybe do a deep dive in one of your new shiny pet projects at some point in the near future

DAN: Count me in.

IVAN: That brings us to the end of this episode you can find us online at ten7.com/podcast. This is Ivan Stegic. Thank you for listening.