[Music] welcome to sincast powered by commerci I'm Heath mcnight joining me today is Kevin Hartman Kevin thank you so much for joining me yeah Heath so happy to be here thank you so much for this time I'm really looking forward to this conversation absolutely Kevin you're a professor neutr Dame an author and you were the chief analytic strategist at Google that is super impressive but no one knows it more than you so Kevin please tell us a little bit about your journey yeah oh it's been a long one I um you know I am a data analyst like at heart that's that's really who I am and who I've always been I also uh I consider myself a teacher and instructor now and I'm really one of those people who uh numbers came pretty easy to me I was just blessed in that way but I thought that uh that that move in numbers for a long time because I wanted to be that artist right I wanted to be that Dynamic kind of Storyteller and I thought that uh uh the numbers thing was just boring right and and it wasn't you know finally I woke up to the fact that I could do both of those things I could lean into the numbers that come pretty easy for me and I could do it in a way that allows me to tell some pretty interesting elegant stories uh and so once I kind of made that that connection I think my career really changed um but it's been a long winding one I've done a lot of things throughout my years excellent excellent and how did you get started at Google it's um you know uh I was at an advertising agency for a long time where I led analytics um I had my previous boss from the agency moved to Google uh and I was talking to her for a long time saying hey I really like to come to Google and this was this was in the early days um and uh uh Google was just the the biggest and best thing happening in Chicago um and eventually I did eventually you know they she found a role and I joined in 2012 I think it was so this was still very much the early days and a very different Google um I came in on the marketing and sales side at Google you're either on the engine ing side or on the marketing and sales side and the marketing and sales side that I joined somewhat unbelievably um didn't use data that often we didn't have to when you're selling Google search it just it's what everyone bought there wasn't a lot that went into convincing an Advertiser that they needed to invest there so uh over time that changed pretty dramatically as competition increased and people got more Savvy and there was more of a demand to have of our input to a marketing plan measured and so I got to be the part a part of all that um I actually led the first and what became the largest analytics team on the sales side they were always analysts but they kind of reported up to salespeople who didn't really know analytics well most of them so I got to build this team that was purely focused on analytics and it was all analytics professionals and we got to grow and develop each other and uh it was really a wonderful wonderful experience and eventually I went on to become that Chief analytic strategist which um the the official title was uh Chief analytics evangelist which is just a ridiculous West Coast Title that no one ever understood what that meant um so I got some advice um from someone to say hey when you talk about it externally just call yourself a strategist uh but it really meant that I was Google's thought leader globally on all things analytics and it was a it was just a wonderful 12 years that I was there I guess somewhere in between there I was the executive sponsor for Google's um grow with Google data an analyst certification through corsera so I got I got that teaching thing that I like to do I was able to do it at Google so it I really saw the the the role and the value of analytics and specifically data analysis uh come to fruition at Google and it was a wonderful wonderful place to be in a wonderful time to to see that growth amazing excellent and I think that's a pretty good segue um what you were saying about the work that went into getting those certifications through corera and I'm very familiar with corsera I think it's a pretty good educational platform what led you to the world of teaching while you were working in analytics at Google you know what I think what what led me with Serendipity um uh with a healthy mix of just not saying no you know I think I learned early that um it doesn't make a lot of sense to say no to Opportunities right even if it's something that is uncomfortable for you or something that you don't think is a really good match I remember pretty distinctly getting out of undergrad uh taking my final final and thinking that's the last time I ever need to crack a textbook and when you know a few years later I I'm picking up a couple master's degrees and I also knew that early I was like never going to get into teaching why would I ever do that and um it just so happened that a friend of mine uh who was teaching a class at the UN University of Chicago was having a conversation with her Dean and they wanted to add in an analytics class and this was again back in 2011 maybe 2010 early on Wow Wow and there wasn't a lot of data analytics so I you know literally I think a few weeks later I was in front of 30 students and it just kind of went from there I I loved it um I learned that uh it was something that I had a passion for uh it was something that I was not very good at and you know here I am at that time in my 40s and pretty late in career and feeling pretty good at what I did and suddenly comes along something that is like learning how to write left-handed right like I it's just a completely new challenge and um uh luckily for me I said yes and I jumped in and it just you know it's it just kind of evolved from there and as I said there was a great deal of serendipity because it was early in the data analytics days next thing I knew Illinois was calling asking if I would teach a class Notre Dame called asked if I would teach a class North Eastern and so I was kind of juggling my day job at Google with this night job of teaching at a number of universities as an adjunct uh and having really for me the Best of Both Worlds excellent excellent and full disclosure uh while getting my MBA Kevin was uh was my teacher in I believe it was digital marketing analytics and business analytics which was almost like a a shorten version of of that class and and um and full disclosure you were a fantastic student well thank you say that yeah I appreciate it yeah it was um you know I we chatted earlier I I my background um before I came into commerci um and and actually for a while I was also writing I was a technology writer um but prior to that I was uh Mr Arts and Humanities film student you know got a couple of film degrees in Associates level and then a bachelor level and did that for years so being kind of on that right side of the brain and then you know kind of starting to train this side with the with uh you know learning everything from like accounting and stuff when it said digital marketing analytics I you know I got a little worried because yes I I do look at Google analytics and and you know for my job and and I try to look at other different you know Facebooks analytics Etc and you know for for kind of I guess an artsy guy like myself I I got a little nervous but when I was taking the corsera um and going through it with with your instruction all of a sudden I was like I don't I don't need to be afraid of it that and I don't need to um say oh my goodness what are these numbers and everything I can I can look at it I can see and kind of decipher what that means and then use that for marketing purposes or our sales team for sales purposes and uh and and I just found it a lot more approachable than than I realize and I think when people think sometimes with data analytics they they think big numbers and all this stuff and and it's true but there's that art component to it as well which which blew me away when when I took that took your courses yeah and I'll tell you what what we're seeing in the reason I mean look this has always been my motivation is to get people turned on to that idea that it is right brain left brain that it not isn't just numbers numbers numbers because um uh this is right in line with the transition we are really seeing in the industry where the differentiator is not your technical skills forever it always was you were a good analyst if you had very good technical skills and that was because data was difficult to come by it's hard to work with that's not the case any longer uh and it's just getting easier frankly so the differentiator now is I can tell stories with data I can interpret I can draw conclusions I can understand what that means and I can use those inputs to solve problems for my business not because I've got the technical skills and the technical capability it's because I know what the business needs and I'm the strategist that can recommend uh Solutions based off based off the data yeah absolutely and and I do want to talk about um about your move into Notre Damon I remember um years ago I I was at a at a company and and I was writing I was actually um one of one of the top writers there senior level and they said hey you need to go look at all this data and they're kind of throwing a bunch of us artsy people looking at it and we're all like and one thing that that you taught us in class and I think what what you were just alluding to is you don't and this will always forever stick with me and not just in data analytics but how you present anything you want to take it distill it down and present it as simple as possible so that way not only somebody like me who is like you know horror movie what are these numbers and I'm I'm kidding of course but so the people that they're presenting it to and then the people who are the managers they need to know and as you would say you don't want their brains sitting there you know getting active and trying to figure out what you're showing them so then became what do all these numbers mean to okay present this in a way that makes sense that's very clear and then you can make those important decisions and I know I I'm probably kind of repeating myself but it it it is something that I think that's where that artistic side comes in and then in the two years since I took your class and and ai's been there a long but AI has really kind of exploded yeah and so I know I'm jumping around a little a little bit but maybe you could talk about the presentation of data but then the importance of AI and how that will help yeah yeah yeah and and look like to your point Heath right the the idea I mean there's some science to this and some physiology our our brains are these wonderful wonderful tools and instruments um we have a part of our brain crop called the prefrontal cortex which is what separates us from the rest of the animal Worlds how we do all of our higher level thinking your objective as someone presented a story to an audience is to ensure that they never have to use their prefrontal cortex because the problem is when our audience sees something very complicated that is a higher level thinking exercise their prefrontal cortex gets going they're working on figuring out what the data is saying what the visualization is they're not going to hear a thing you're saying that's the one thing that we don't always understand and recognize is that when that prefrontal cortex is engaged everything shuts off so you don't want that with your audience right you want to present things just as simply as possible so that that prefrontal cect stays nice and quiet and they're able to hear you and listen to you and understand the story that you looking to tell so that's the physiological reason that we do it beyond that uh it's just it's just it just makes for easier stories and a simple easy story is always better than one that introduces complexity right like if you ever are looking at a chart and thinking should I break this into two charts yeah you should right every time um if you are ever looking at a chart and you're thinking man I'm not sure that they that're that they're going to understand this yeah they probably won't right I'm looking at a chart and I'm thinking there might be some distracting elements Yep they're probably distracting right these are the things that if you are thinking it as the analyst putting the story together you uh uh certainly your audience will and and the way I mean Illinois does a great job of it the way you learn how to do that is you teach it you teach the proper way and I just don't see that taught enough which is kind of connecting back to why I am doing what I'm doing now and all the projects that I've got going but uh you asked another interesting question about the influence of AI yeah and it it's having already dramatic effect on data analytics and it will just continue to right right data is so vitally important we talked about that every every company needs to use data if you are not using data effectively you are falling behind if you as a professional aren't comfortable with data you're going to fall behind the good thing for everyone is that the advancement of AI particularly the use of natural language processing inside of artificial intelligence and machine learning is creating a situation where I frankly don't need the technical skills I needed yesterday to do the same job today um let me just give you an example I mean I love R I love to code an R I love SQL I love to use SQL to pull queries to pull data from from large data sets in the future I don't really need to know how to do that um I'm simply going to ask a machine to pull the cut of the data that I want or conduct the kind of analysis that I want and it's going to do all the work um and that's probably in the very near future to be honest now look there will always be a need for people who know how to code it's kind of Ain to driving a car if you own a car you don't need to know how the engine works but if you do it's probably you're probably going to be a better operator of that car right um but if that car breaks down you're still going to take it to mechanic right it's just like the same thing if if the query breaks down the algorithm breaks down you still need someone that can understand that but just as you know almost all of us could operate a car without having to understand how it works this is what AI is going to do for some of the heavy programming languages allow you to get what you need without really understanding why yeah and and you made a I think an important point about about data and if you're not if you're not using it you're falling behind um I I'm still you know a tech geek and but I'm also kind of an inside baseball geek so like if I'm reading different Tech websites and wow why did this website crash what you know why why did their readership drop and and you can't always say it's an algorithm update I think it's not paying attention to the trends that are presented in data a as you get new audience members perhaps they want to see more video and and Le read less blogs I'm more of a Blog reader I'm just giving some some examples but as you said the data it it and for one thing it really doesn't lie it's going to tell you okay this is where this is going this these are the things that are doing well whatever it is it could be a a product that's selling really well and uh and I don't want to jump around too much because I could probably give a million examples but um you know for the people watching today if they're they have something like a company that sells certain amount of products how can data help them with something as simple as marketing campaigns oh and just a you know a variety of ways um and even if you just look very narrow narrowly at marketing campaigns there's so much value that can be created there and primarily around just increasing Roi the money that you are investing in your marketing campaigns you can use data to do that more efficiently to do that more effectively to reach the right consumers to move funds that you would have spent trying to reach out to the wrong consumers to those right consumers right as long as you know who they are and that's all data challenge um you can position your product better through better marketing and measure um through better uh better uh messaging right and that's through data collection that helps you understand which messages they resonate resonate with your customers and which ones don't and at the end you can you can bring greater accountability to your partners to your uh campaign managers by just measuring better and that's data as well so yeah from upfront all the way through the campaign to the measurement at the end data plays a role and those companies who are able to use it effectively will see better Roi at the end of the day yeah absolutely and um I spoke with one of our customers and we were kind of talking about the importance of data analytics and she's head of marketing and and she said it best I hadn't heard the same but I knew the the whole whole you know throw throw spaghetti a while see what sticks but hers was spray and prey so you're trying to throw it out there and hope that one of those sticks whereas a good example would be you know we have customers using HubSpot or Zoho or Salesforce they can look at the products that are selling well and in in the region and then Market based on that so they're not just throwing money away on a product that may not work in this other region and but they're promoting and wasting money and everything yeah and let me give you can I just give you a really simple example of this is just a simple this is exactly where every company in my opinion should begin take a look at your customers and take a look at two really important components of value which is how recently did they buy from you and how frequently do they buy and then simply construct quintiles or quartiles based on recency and frequency and put that together in what we call recency frequency Matrix and when you see top quartile or quintile customers in recency so they bought from you recently and in frequency they buy from you a lot those are your those are your your Champions do everything you can to maintain those customers work really hard and then you'll find rings of customers who are uh possibly in that that area where they may be a trting and so you can work to retain those customers and then importantly you're going to find these lower quartile customers who don't buy from you very much who haven't bought in a long time and frankly they're probably gone so why you continue to throw money at them doesn't make any sense you should take that money and reallocate it towards these customers who are really driving your value right that's just a simple simple set of analyses that you that any company can do using data and you don't need fancy Ai and you don't need uh you don't need fancy tools to do that um but what you do need is the next step which is all right now that I've got my strategy I know whom I'm talking to how do I talk to them what's the data story that I tell them what's the what's the story that I'm using to convince them to continue as my customer or deepen uh how important my relationship is with them uh that's the trick in and but but but that kind of really straightforward marketing challenge of building deeper customer relationships is aided by that simple analysis with just some simple data right up front excellent excellent and um you know when I was kind of talking about the looking at data sometimes it can be overwhelming and everything and and and complicated but what what are some of your tips and tricks that you use when analyzing data to make it easy to understand and and presentable as you talked about that keep it keep this quiet so that way they can hear the message and everything well it begins very much upfront right and that is ensuring that the question that I'm answering is clear and concise and exactly what my client or my stakeholder needs so there's a lot it's not the work just doesn't come at the end when you have the data it becomes it it starts at the very beginning to ensure that you are tackling the right question um and it's not always the question you've been given but it's it's your job to get to that real question that you need to you need to to answer the motivation there the thing that we call the ask behind the ask then once you have those data um you know I teach really three principles uh and you can think of it as the acronym score s uh CR uh and that is sophisticated use of contrast clear meaning and refined execution um and so you follow the principles that we talk about and you use contrast in a way that grabs attention uh you include all of the elements that uh are really pretty common elements headlines labeling things like that but you do that in the right way and that's going to clearly communicate the meaning that you want your audience to walk away with and then you put some Polish on it the refined execution minimizes distractions it makes it pleasing to the eye you know we we've done studies and I've seen research um that says that yeah the message is what is most memorable uh by the audience but the visual aesthetic contributes tremendously to whether or not they remember what you said or or or forget it right so yeah um yeah so that those are that's kind of the combination of not to get too deep into the theory but that's those are the ideas that we communicate and teach uh when we talk about this excellent and I think like one of the the things that I also took away was always keep it simple and I think in in I don't care the industry I don't care um you know the the department or division sometimes we want to over complicate it and you always you you really kind of pass it along to us keep it simple because it's always better um what you had mentioned some tools earlier like R and SQL and um I was wondering what what are some of your favorite tools now again like anything in technology two years fly by and all of a sudden everything changed but what are some of your favorite tools maybe some of the old standbys that you love the old you know and then what are some of your new favorite tools yeah I mean the the basing boring the boring basic ones are still really important to me I love to do analysis in spreadsheets and whether that's Google Sheets or if that's Excel um doing pivot tables and other kind of uh functional work in my data I I I enjoy I I love using SQL when my data gets a little bigger I love R I just I always have loved R um and so I love to to get in there with data and make conduct analysis there and then you know Tableau or powerbi and the cases that I've I've had access to that are tools that I've really enjoyed as well um the the old and the but goodie um program which I used to love was something called Microsoft Access which I think kind of disappeared but I met I've managed to replace that with r and the other tools there but I'll tell you there's a whole crop of new analysis tools coming out much of it based on AI and and rooted in large language models so beyond just using chat GPT to help with analysis uh there's a tool called polymer you'll find at polymer search.com I know the the CEO over there uh yeser and it's a really interesting product that is growing and developing but it basically allows you through the use of natural language processing to take in prompts and then generate visuals for you on your data it's also smart enough to kind of look at your data and say well here's some interesting views here's some questions that we can answer are these questions interesting to you right and I think that that kind of tool Leed analysis is really where we're moving and polymer is a good example of that there's another one that I've Had The Good Fortune of working with this company for a while called EMA em a ww uh and what that is is an AI driven algorithm that um based on how consumers are moving through your website scrolling through a mobile or using their cursor on your desktop website it is deducing the emotional experience that they're having what they're feeling and they've broken this out into a number of emotions and it is just a GameChanger wow for marketers to understand not only how my whatever they're seeing if it's an ad they're interacting with or if it's my we website proper what sort of emotion is being generated and that can be used through remarketing it can be used to discern consumer value it can be used to segment and Target like there's a lot to that and it's again just another one of these analysis capabilities that are being opened up to us because of AI That's it's just so amazing to be able to think about the emotions and of course it's like well how would I feel if I'm going through the Apple website and looking at all the great new products but it's not just the I hate to say like that the candy you know all the treats in the candy store but it it could be for any company yeah a company that selling um software company selling a manufacturer uh selling I'll just say widgets you know they can see that's that's pretty big because if if their if their homepage suddenly has a a huge bounce when they're scrolling down something something's going on and this could kind of show it a I I would think a little bit more clearly and then they can make adjustments and then kind of start marketing remarketing our you know try to improve it so they don't lose all of those potential customers and everything I'm I'm Blown Away here wow well and what I love about it is the kind of accountability that it can bring for agencies who are producing these ads or the platforms that are hosting them because the only way we've had a chance to measure has been Impressions who saw it yeah click-throughs who clicked on it right that's not a lot to go on and in fact like just because I saw an ad doesn't mean that it meant anything to me um you know if this allows us to Simply pay for the consumers who had a positive emotional response to my ad wow like suddenly that changes now you as my agency you've got to make better ads right or I'm not paying for it uh you Facebook you need to place my ads with the right people from whom these messages will resonate or I'm not paying for it right yeah and so it it kind of changes it can in in in very real ways change the change the dynamic between advertisers and platforms wow I mean the first thing that comes to mind is if I'm you know just chilling out after work and I'm like oh what's going on on Instagram and suddenly I'm seeing I'm seeing really great targeted ads you know I'm I mentioned I'm a I'm a big triathlete and Runner hey all right I'm looking at some new bikes or whatever I doubt I'd buy a $110,000 bike but then I'll see something that just I'm like really I don't you know I'm not sure if that really and I would feel so bad for the person paying and getting that ad where it it it goes back to to what our client said the the spray and prey at that point now you're just like here everybody can look at this ad yeah but in reality only a small segment really needs to see that ad yeah yeah amazing so let's let's talk a little bit about Notre Dame um how did you become the associate teaching Professor there well it and again it's um a little bit of serendipity I mean I I started adjuncting 10 years ago or so when they were starting a business analytics master's degree they knew that I was teaching analytics courses they asked if I'd be willing to adjunct in their program I jumped at the opportunity I I went to Notre Dame undergrad my son uh my dad graduated from Notre Dame my brother did my brother and my sister wow I have a son that just graduated from Notre Dame and we're going down to the commencement this weekend which is really wonderful so it has a special place in my life right and it it's just something I knew I wanted to do it and I I had you know uh reached the the the point uh at at Google where it was time for a change and that was the perfect change and now I get to do exactly what I love I get to work with a new generation of business people and data analysts um teaching them the things that I learned over my career um while uh while still uh affording me the opportunity to do some things on the side that I really enjoy as well so it's it's just a it's a wonderful uh career for where I am in my career and I I really hope that this is this is probably I really hope that this is the last job that that I'll ever have to be honest that's that's incredible and that Legacy with your with your family and I think I think everybody knows Notre Dame just that Legacy uh of uh you know PE people would go uh I mean more I mean this is like a 80s 990s in in Miami the hurricanes and I think more people would go just because it's Notre Dame playing so I I just that's that's amazing and um you also just recently launched a new uh company art science analytics Institute and I was wondering if you could tell me a little bit about it yeah that's a project that we're working on that um uh is kind of a a passion project of mine our objective what I really want to do with art science is prepare anyone but specifically data analysts with the data skills and knowledge that they need to earn greater professional opportunities I want to take all these things that I've learned in my career and build out um a series of newsletters and YouTube videos and um uh blog posts but then also online courses that people can take to to learn the skills that I think are important and really our focus is to create this analyst of Tomorrow someone who can tell stories from data someone who can blend both sides of their brains yeah we'll talk about and we instruct on technical capabilities and the technical expertise that is needed but the focus of that project is for is to have Learners who join us kind of come out with a very well-rounded ex uh understanding of analytics and a great Keen ability to tell stories so it's something that I'm really excited for um uh you know it's the my noted aim teaching I is my my primary job and noted aim to your point is is a very traditional um Traditional School where I am in a classro with live students working with them um it it it just limited limits the number of people that I get to I get to help and contribute to so we're hoping that this art science project which will be online uh and digital is much more scalable and distributed and just lets me just lets me give back to the analytics career uh Community all the things that I've I've earned and and had uh been given uh by it that that's that's phenomenal to hear um if somebody's interested in pursuing a career as a data analyst what would be top two three four tips to get started yeah yeah and I'll tell you and and we didn't uh I don't think I've mentioned this but I we have developed through ART science a six-month guide for anyone who wants to get involved in a career in data analytics these are the first uh kind of maps out the first six months for them and I'll be happy to to link that in the in the show notes or or give that give a link to you there that that anyone can access but really that that boils down to taking a couple concrete steps it's it's really um working on gaining the technical Foundation that you need understanding statistics understanding probability understanding those things that really form and underpin the analysis that we do learning those analysis techniques just becoming comfortable with data building some of the technical skills I would start with spreadsheets you just have to know spreadsheets backward and forward then move into some of the heavier tools with the aid of a large language model really in AI if you want to learn coding um and and then you know really lean into your ability to tell stories from data learn how to do that learn how to visualize and build a nice portfolio that you can show perspective employers that hey here's a challenge here's a case study that I took on here's the output of my work and the uh the the recommendations that I gave right um so that's all that is captured I think with with pretty good detail in that six-month guide that we'll be happy to share but but it's it's it should not be to your point from the beginning it should not be an intimidating Journey for anyone it it is a data is the way of the future it's what everyone needs to be doing I'd say anyone who has a pinch for curiosity and creativity will find a u a path a career in data analytics really really rewarding excellent excellent and how can our viewers learn more about you Kevin yeah so so I'm I'm on LinkedIn in pretty active so you can find me there for sure reach out there you can also find me at uh um art science it's art science onew word. um also feel free to email me at Notre Dame if you uh want to reach me there that is just kartman nd.edu and so there's many many ways to get hold of me and uh I try to make myself pretty accessible awesome and and this is true and and I got to say I I love uh popping into LinkedIn and you're you're sharing some really excellent tidbits and I I hate to use that but they're just it's it's great it's it's perfect for just kind of like starting to learn um you're definitely passing along a lot of this knowledge and making it so accessible and and if a guy like me who has you know three Arts and Humanities degrees and I'm not dissing it I I loved I loved learning I I I went to a community college to get my film degree I went to Florida Atlantic and I I you know for me that's like you know my love in Illinois for for the for the NBA but it just to be able to take you know start diving into some of what you were teaching and immediately you know I B I bought your book and and I just started to really embrace it and I couldn't even believe it my wife who's a graphic designer is like really are you sure and I go yeah he makes it so approachable and and I I just can't you know thank you enough for that so um and thanks for joining us today I really appreciated the conversation my pleasure it was great great conversation always great to see you Heath and uh looking forward to seeing you again soon thank you for watching and listening to sinkcast powered by commerci if you'd like to learn more about sync Erp and CRM data integration please visit our website commercient dcom thank you [Music]