On this episode, we spoke with Jon Tesser who is the VP of Research and Insights at NYC & Company, the destination marketing organization of the five boroughs of New York City. Jon explains how marketers and analytics professionals can work more effectively together, some unique ways that he has leveraged various sources of digital data to enrich his audience segmentation, and what he's most excited about when it comes to the future of research and insights.
Here's a full transcript of my conversation with Jon:
Charlie Grinnell: On this episode, I'm joined by Jon Tesser, VP of Research and Insights at NYC & Co. Thanks for joining me today, Jon.
Jon Tesser: Pleasure to be here, Charlie.
Charlie Grinnell: I want to go back to the beginning with you. You've had a pretty remarkable career in data analytics and insights. You've worked at organizations like BET, Sprinkler, New York Magazine, and ABC to name a few. How did you get into working in analytics and insights?
Jon Tesser: Well, Charlie, let's go back to before for my work life to a time in high school that will illustrate how I got into data and analytics and how I chose the right career. I think back to... I would have to take the train, the subway to go places. I grew up in New York City and as you know there's a lot of different types of ethnicity, so people from Mexicans and Chinese specifically in the borough of Brooklyn, which is a borough of about 3 million people. I use the power of observation. I always wanted to get seat, but I could never get a seat when I would take the train.
Jon Tesser: What I would do is I'd actually watch people and figure out, oh, okay, well judging based on their ethnicity and what they look like and who they are and the bags they're carrying, which train stop are they going to get off? 80 to 90% of the time I'm using that power of observation, they would get off at the stop that I think they would, and so this actually illustrates how I have, essentially I spent my career using data analysis observation to drive outcomes.
Jon Tesser: It wasn't sitting there with an Excel spreadsheet, but it was looking at somebody, taking in their profile, understanding who they were and expecting them to take a certain action based on that, so this was done in high school and then carried through my social science college degree that I got from undergrad and then carried through the rest of my career where I would essentially used the power of deduction and analysis.
Jon Tesser: Obviously getting much more advanced than using data, behavioral data. But yeah, that's actually how I got started with this, and it's a really great way for people to think about careers, which is, hey what did I do when I was in high school? Or what did I do when I was in college? Or what did naturally gravitate towards? So just an interesting way to start the conversation and to talk about the fact that I didn't just start in data, I was always in data.
Charlie Grinnell: Yeah, that's... I mean when you were in high school at the time, obviously looking back now you remember when you did that, when you were doing that, did you feel like, oh yeah, this is something that I want to do, or is that just the way your brain kind of worked?
Jon Tesser: No, it was never something I wanted to do. I mean, you have to think about this, right? There was no field of data when I was in high school. You basically had that patience, right. Who I guess new statistics, you had market research, you didn't have this proliferation of data that we have now, particularly in digital. Digital was at its nascence. So I mean, I think what you're asking is actually a really great question, Charlie, which is the fact that we don't know where careers are going to go because as I said, the career of data really has only taken off in the last five years.
Jon Tesser: I had no idea where I wanted to go. Studying people, that's something that I always figure out. Okay, yeah. I'm really interested in people's behaviors and why they do what they do. Adding the data part in that, that came a lot later.
Charlie Grinnell: That's probably been driven by the rise of the internet, so to speak.
Jon Tesser: Well, I mean I think it's driven by the fact that we have data that we can collect on people's behaviors now and the internet is the place where you can track the most information, right? So essentially, with web analytics, which was really the first way to collect data, you're able to basically watch somebody footprints as they go from one page to another. That to me is actually revolutionary, right? You never had this ability to track someone doing something, and so that's why digital becomes the mechanism to understand people's behavior.
Charlie Grinnell: I always joke around with some of our clients or friends of mine who work in marketing being like, we actually have it so good compared to 10 years ago, 15 years ago. To your point, how revolutionary it's been to be able to see the things that we're able to see and pull meaning from things. It's just not even comparable to 10, 15, 20 years ago, right?
Jon Tesser: Well it's really funny that you mentioned marketing, right? So marketing and I think we're going to talk about this probably a lot later, but marketing's always been I think there's a famous phrase like, you spend 50% of your budget, you just don't know which half is effective, right? You've come into this world of ROI, but that's actually really dangerous. It doesn't work as well as we would like to, and again, I think it's something we're going to touch on as we go through this podcasts, which is, oh my God, infinite amounts of data, but a lot of the data, remember if you go back to my story about what you're doing on that train, a lot of the data's not answering that question about that person. It's answering questions that are easier to answer because you're just gathering a lot of data, so you have to be really careful in the world of marketing with data and how are you using it and the kinds of questions that you're trying to answer.
Charlie Grinnell: That makes a ton of sense, and that actually segues nicely into the next question I wanted to ask you. You've obviously worked at a lot of different companies across different industries. What do you think is the most misunderstood piece of analytics and insights work?
Jon Tesser: Oh, you know I think that people just expect you to whip up insights in about 30 seconds.
Charlie Grinnell: So it's not done yesterday?
Jon Tesser: Right. So I think that non data people have a huge misconception of what goes into and analysis. This is really the biggest problem, right? Here's a funny story to illustrate this, but it's not really funny. It's kind of depressing. The City of New York comes to the tourism bureau and says, I want a real time dashboard of all the tourists activity in New York city.
Jon Tesser: I'm just going to leave it at that because if you work in data, it's so great to want something but actually delivering that literally what they were asking for is impossible and I could spend the rest of the podcasts talking through why it's impossible to collect literally a realtime dashboard of all tourism activity in New York City, and it comes down to understanding things like methodology, how data's collected, sampling issues, when the data's collected, how you get it, how you process it. There's all of this data engineering stuff and there's all this data cleansing stuff and there's all of this stuff around data and how difficult it is to answer questions, but I think there's just a lot of misconceptions like I'm just going to provide insights in 30 seconds.
Jon Tesser: It's never liked that and so the most difficult thing with the proliferation of data that we have is to explain to non data people, well, you may not get exactly what you want, but we can try and move in the direction of what you need, right. So that conversation, it's almost like a constant battle of yes, here's what I want and as a data person, well here's what you can actually get.
Charlie Grinnell: Yeah, I guess a follow up question that I just have to that is it feels like marketing analytics and insights and data and all these things kind of that have traditionally fallen under marketing, they've gotten really, really popular over the last few years with the rise of digital and there's a lot of buzz around it. Data-driven decision making, that sort of thing. Data-driven decision making has become like a buzz word or over hyped. Is there anything that sticks out to you that's over hyped?
Jon Tesser: What does that mean data-driven decision making? I mean, let's talk about that for a second and good I'm hoping there's a lot of red flags here. People just start calling up and saying, "I hate you Jon," but I'm cool with that.
Jon Tesser: The problem is that data in a lot of places and a lot of companies, data departments actually live within the marketing department. So let's talk about why that's a problem and this is very philosophical, right? Yes. Data-driven decision making. Really what data-driven decision making means to marketers is support my shit or else. Excuse me I just curse, but support my initiative, right. Support what I'm trying to do or you're fired, right?
Jon Tesser: Otherwise the data organization actually needs to live outside of marketing to provide that voice of data-driven decision making to actually say, well actually you guys are not doing the right thing. When it's your boss who needs to hold on to their job and you're reporting to them and you're doing the marketing within the organization, you have major issues, and I think this is a fairly common problem.
Charlie Grinnell: It's interesting to hear you point out like there are definitely kind of two sides of the fence. I feel like a lot of the best data people that I've worked with or analytics folks are the ones who really understand business and or marketing or the subject matter expertise where they're being deployed. I feel like that's such a unique thing. Do you have any advice for people who are on either side of that? How can data folks better work with business folks like such in marketing? Or how can marketing folks better work with data folks?
Jon Tesser: That's a really great question and I think you've basically come up with the crux of why data-driven decision making is such a problem. I mean, you essentially have, one team speaking Swahili and the other one team speaking Swedish and they're talking at each other and no one's listening because they're speaking different languages, right? You are 100% dead on. Charlie, I come from a marketing background, right? I'm not an analytics guy. I use data. I'm good at it, I'm good at finding insights, but I'm always marketing first, and so the mindset is always in the marketer like where customer segmentation audience, how do you reach people, what are they supposed to do?
Jon Tesser: Data people don't come from a marketing and business background. Particularly what I'm finding more happening now is there's a proliferation of data people coming from computer science, from statistical and mathematical backgrounds and this is making the goal even worse.
Jon Tesser: When I first got into this, I'm like a grandfather of data. I've been doing this shit for far too long. Everyone had my backgrounds. They heard like a sociology degree or some sort of political science and they were cool. I like data to understand people and I like business and it was a lot of us kinds of web analytics? So web analytics analysts was the name of my title, my first data title and once you had this hippie crew of like yeah man, we're going to use data, we're going to really find insights and help businesses and over time you're actually getting a lot less of that.
Jon Tesser: You're getting a lot more people who are entering this world from computer science and these are not people who are used to having to communicate findings and understand business and we have a real problem.
Charlie Grinnell: One of the things that I've talked about on another episode is this balance between art and science within marketing. There was kind of the two camps and it's fascinating to hear you talk about the golf so to speak and the differentiation on the... It almost sounds like there's a golf within the analytics side of things where you have the data science folks and then like the more business-y folks who are still sitting on that side of the fence and then there's the creative side.
Charlie Grinnell: So it's interesting to kind of hear you say that because I've always thought of the gap between art and science, but then within the science side, it sounds like there's almost another kind of gap there that you're explaining. Do you agree or disagree with that?
Jon Tesser: Yeah, 100% agree with that and I'm glad you brought us there. I mean, there's even a gap between the people who are really good at data engineering, right? Which is like creating the database so that you can hold all of this big data and the data science people who are supposed to create algorithms and use predictive technologies to understand things and then you've got the data analysts who were the ones who were supposed to speak to the business and have those communication skills and those business skills, and so how did these three sides together. That's a big part of where we are in data as well.
Charlie Grinnell: That's probably why it's been so difficult for marketers, right? Because that's a big part of influencing decision making, helping steer the business where it needs to go, but also there's a whole can of worms in there that needs to get figured out as well as all of the other areas of marketing that needs to kind of come together to market effectively.
Jon Tesser: Yeah. I mean there's just so many issues to becoming a data driven organization. Right? I think what I just said about three roles, and this was my first viral post ever on LinkedIn and I was just doing jumps for joy, but I essentially define these three roles, right? I was like, you got these data wranglers. They're the ones who are bringing all the data together and usually come from a software engineering background and our experts at creating databases.
Jon Tesser: You've got these data productizers who use data to create products that recommendation engines or predictive algorithms and stuff like that, and then you've got your data strategists to use data to help companies figure out strategy and even this concept is difficult for organizations to understand that these are three different disciplines within data, so how are you then going to effectively talk to marketers who are like, "I just need my data."
Jon Tesser: It's a lot to deal with and I don't know, I'm not sure where it is going, but then as I said, you also have marketers to want to operate by the gut and who say, "I'm creative and I don't want to listen to the data people," and you've got the data people who either can't fight back because A, they don't have the communication skills or B, they're not empowered within their organization to fight back and say, "No, you better listen to the data." So again, I don't want to spend an entire hour about the problems in the data industry, but it is really an interesting topic.
Charlie Grinnell: I feel like we should have another episode where we talk specifically about this, but let's change gears a little bit here.
Jon Tesser: Move on.
Charlie Grinnell: I want to talk about audience segmentation, which is kind of what this episode is about. This has been obviously a popular topic and in marketing specific, and I want to go back to the basics first, and so what is audience segmentation and why is it valuable?
Jon Tesser: We have a world of 8 billion people or 7 billion or whatever, right? We can put them into men and women, right? So now, okay, great. Now you have four smaller groups, that's cool and we can go further and we can flip them into age ranges, right? So you've got, 18 to 34 or 55 and you keep breaking these groups down to... Why do you do that? That's really the crux of it. When you're a marketer, you can't satisfy all 8 billion people in the world. Somebody living in outer Mongolia probably doesn't want to buy your product, so you have to think of, right? I'm just doing a really obvious example.
Charlie Grinnell: Yeah.
Jon Tesser: If you as a marketer, you need to understand your audience. The best way to do that is to create different groups of people who want to buy your product or consume your media. So, a way to think about this and I know I'm supposed to bring up my LinkedIn, but I think it's actually a really great way to illustrate this idea of audience segmentation. I create content on LinkedIn and I have very specifically created two distinct audiences so that when I create that content, I know what's going to resonate with them and they're going to buy my content and they're going to buy it by looking at it, engaging, commenting, sharing, whatever.
Jon Tesser: For me, that's my win as a marketer, as a content creator. I've specifically said, okay, young professionals in college, who are graduating or need some help and guidance on how do we emotionally deal with being a college student about to go into the working world.
Jon Tesser: Okay, cool. One segment, other segment is data people and understanding data topics and more data strategy. More conversations like, hey, what's audience segmentation? Or how are you using social data? Stuff like that, right? Not going... And again, we just talked about audience segmentation. It's not the data scientist I'm interested in. It's not the data engineers I'm interested in, the data strategist. Then how do you use business and how do you find insights? So marketers, the more they understand the identity of who they're going after, which I just told you my identity as a content creator, the better they can target their marketing and their messaging and the more they can say, Oh okay, I understand what you need for my product because you are who you are, you have your identity.
Charlie Grinnell: That makes a ton of sense and so I want to take that a step further now that we've talked about, what it is, why it's valuable. Can you walk us through how you've approached this stuff in the past? I know you're doing some really cool stuff presently, which we're going to get into, but yeah how have you approached this in the past?
Jon Tesser: So let's talk about typical, how audience segmentation has been done, not by me. I think that there's... and again, I'm not as okay statistician or an expert on any of those, but I think there's something called cluster analysis where you essentially take a whole bunch of group of people and you say, okay, they all seem to have these similar types of characteristics. I have no idea how to do this, but what I have done in the past is I've used the power of social analytics. This is a cool example.
Jon Tesser: This was specifically when I was at BET use the power of a clustering tool called Affinio, shout out to Affinio, and what that did for me is it actually created these clusters for me of audiences and you did this by essentially putting in a Twitter handle. So when I worked at BET, we would put in the BET Twitter handle.
Jon Tesser: One of our competitors was Complex Networks, so we put them in as well to understand their audiences and this cool things spit a whole bunch of different audiences. Some of them had cool names like celebrity moms and basketball players and video gamers. Now I'm like, "Oh my God, I have a really deep insight into the type of people who are following BET conference," and I essentially took this and created six or seven of my own segments and I was like, okay, this is what I'm going to get from Affinio but I'm going to combine this all and I think out of all of this, this is all of the African-American people who consume content, and this was all done through, as I said, the proliferation. We're going back to the beginning of the conversation, proliferation of digital data.
Jon Tesser: That's what allowed us to do this because we're collecting all of these fingerprints of what people are posting on Twitter and you know what they're putting in their profiles about themselves and we're saying, here you are a basketball player, here you are celebrity mom, here you are reality TV lover. That was the first step in creating those audience segmentation essentially through Twitter, through putting these people into groups together.
Jon Tesser: I don't know how Affinio does it, they're just really cool. That was only the first part. The identity part is cool. That's done. We know who they are, but we don't know what they're consuming and why and that's where things got really, really fun, so what I essentially did from there is I would take those groups, let's say the basketball players and I'd create what I call a virtual focus group.
Jon Tesser: I would take 30,000 of them and I take all their Twitter handles and I would put them into a social listening tool and for those who aren't familiar, social listening tools essentially can take every single tweet out there in Twitter and allow you to ask questions, which is about it and so what I did and what the segmentation allowed me to do was I took those 30,000 people and I put them into the social listening tool and I asked the tool to tell me what are they talking about? What are these 30,000 people having conversations about? It was really, really incredible some of the insights I was able to find based on this. I could query about anything. We would work with advertisers and they want us to know, Hey, what does our audience think of Mother's Day.
Jon Tesser: We were trying to come up with Mother's Day content at BET and so we plugged in one of the audiences and this was a legitimate insight, Charlie. It was really cool. I asked like I think the celebrity moms, right? What do you think of Mother's Day? What comes up? There was this idea of the mom is the queen, right? Just kept coming up. Mom is queen, mom needs to be celebrated, mom needs to go to Cheesecake Factory and we need to worship her.
Jon Tesser: That kind of insight. That's why you do audience segmentation work. You can now work with that on a creative sense in a marketing sense and say, "Wow, that's a really powerful concept." This idea that mom is the head of the household is somebody who needs to be worshiped. We can take that idea and creatively work with that.
Charlie Grinnell: Whoa. That's a crazy example. The fact that you were able to unearth that is gangster. I love that.
Jon Tesser: But you can see the process of how you do that, right? Because you're querying the social data. You're looking for the themes of how people talk about things. You're coming up with the example and bingo, the insight kind of just screams at you. This is powerful, powerful stuff. I'm going to toot my own horn here. I'm probably the only person who has done any of it.
Jon Tesser: Yeah, I mean it does speak to the power of what brands can do if they want to use the power of social and audience segmentation to understand their different audiences and how they speak about that.
Charlie Grinnell: Yeah, I totally agree. Was that the first time you kind of dove into "alternative data sources or external sources playing into your segmentation work"?
Jon Tesser: Yeah, it was. That's actually a great question, Charlie. Yeah, most of my segmentation work in the past had been done through Adobe Analytics and Omniture. I'm an Omniture guy. Like I'm a web analytics guy. That was my tool and so audience segmentation was always done through web analytics behavior. So, hey what the difference between somebody who visited the site five plus times in the last month versus somebody who's a new user and then figuring out those different audience segmentations. It's powerful stuff, but not to the same degree is what I'm talking about with the proliferation of the social data that you're getting and the ability to segment through that.
Charlie Grinnell: Yeah, it's one of those things that, and I guess it goes back to the title of this is this idea of hiding in plain sight and using stuff-
Jon Tesser: Oh, my God. Yeah.
Charlie Grinnell: ... that's all around you and just a matter of harnessing it in the right way.
Jon Tesser: I think that's a brilliant way to frame it, Charlie. This is all available for all of us to do. All it takes, it's there. It's hiding in plain sight. What I'm describing to you, it's just a technique to mold the data into something that's useful and that's really all it is. I love this idea of hiding in plain sight, because if you want to do it, you can. You just aren't doing it. There's no excuse not to. You're just not necessarily thinking of it in the right way.
Charlie Grinnell: Yeah. One of the things that I've been thinking about a lot in talking to people a lot about and trying to post about to marketers is that there's this idea that for the past however many years we've kind of had one eye closed so to speak and by looking at the external data sources, you're uncovering that eyes, so now you can see the complete picture, internal and external and then by doing that, that's going to give you much more information that you can then use to make a better, more informed decision.
Jon Tesser: Yeah, but the problem here, not to start a debate, but the problem here is that marketers really only care about ROI and direct relevance, right?
Charlie Grinnell: Fair.
Jon Tesser: I'm talking about somebody that's brand building, right? Identity, the messaging and the really important stuff of marketers and marketers are like, okay, fine, just tell me who's converting the most. You know you have that problem of trying to take the stuff that's hiding in plain sight, the stuff that's interesting. The stuff that can really move your business and convince marketers that they can keep their job even more if they go into the brand side and understand how that works rather than just saying, "Okay, which group converted more on the red or yellow."
Charlie Grinnell: You know what? I mean, you nailed it. I have a followup question. So how have you in the past, obviously you work with marketing folks and you said you're a marketer, but now you kind of on more of the research and analytics and data side, what advice do you have for people to work closer together? When you go to a marketer and the marketers like, just tell me what converts.
Jon Tesser: Mm-mm (negative). You got to speak their language. You have to speak their language, you have to build their cross. You have to go in and talk to marketers like you know who they are, right? It comes back to the Swahili and Swedish thing I said. You can't be a data person. You have to go and use what are your objections because right now, where are you trying to go? What's your high level strategy? How are you trying to move your Titanic marketing shift right now? You've got a giant shift and you can go in 500 different directions and I want to know what direction you're heading in at this moment. That's the question that you add. You stop them from jumping right into the campaign and you say back up. What are we really trying to do here?
Jon Tesser: You keep asking the questions until they give you an answer, because they're going to keep jumping back into the tasks pickle and you as the analyst person can't go there with them. You have to go up to the strategy and you have to say, no, no, no, no, no. As a business, let's fundamentally talk about you as a marketer right now, the problem that you're solving for, I don't care about the campaign right now. I care about what you want. What do you want people to do and how do you want our business to help them do that? You have to drill this question until they come back to you with an answer and they're like, "Well actually like in the case of New York City, we're just trying the New York under focus now with COVID and in a positive way in combat to some of the negative stuff going on, right? Okay, cool. So as a data person I can work with that.
Charlie Grinnell: It references like what is the overarching thing that you're trying to achieve, right? I feel like even getting clear on that, sometimes I feel like marketers and I've sat on marketing seats where I don't necessarily have clear direction of what are the objectives that I'm accountable for? Then that makes it harder to go downstream, so to speak, to understand what data should we be looking at to help us understand what we need to accomplish? So, it's unique to... Well, it's not unique. I guess it doesn't surprise me to hear that, that's the case as well.
Jon Tesser: Yeah. But I mean, your entire data project is going to fail if you don't start at that top level. If you don't have an objective of what are we trying to accomplish here and how are we trying to do it? You're done. You failed. You're not going anywhere. You're not going to get anything out of it. You're going to have a bunch of numbers and you're going to say this is up and down and then people are going to go, so what? And everybody is going to say, "Data doesn't serve any purpose." So you're doomed from the start if you don't have those objectives.
Charlie Grinnell: So it's objectives and then asking the right questions to get really clear on those.
Jon Tesser: Yeah. It's being relentless then what are we trying to do here? If you don't get those questions, I'm sorry, I don't mean to be cynical, but you're just not going to be an effective data department, because it really does start with that, and so the relationship with the marketer needs to be speaking at that strategic level and then diving into the tactics right after.
Jon Tesser: I've had some really good examples of doing that with marketing team at NYC & Company. I don't have too much time to get into it, but we started at the top, this was pretty COVID and we were trying to figure out what are we trying to really accomplish with international visitors? It took two to three hours, but I would work with the marketing team.
Jon Tesser: We essentially said, oh, we need to get them out of Times Square, which is the most popular part of New York City and we need to move them around the rest of New York City. Okay, as a researcher, as a data person, now I have something to work with, right? Because once you have that objective of okay we need to get them out of here and go over there, great. We have an objective with our campaign. We can measure to see how effective we are doing that and we can... It all sort of cascades and water falls from there.
Charlie Grinnell: Yeah, that's a good segue. I want to talk about the work that you're currently starting to do with around audience segmentation. You alluded to some fascinating stuff. I want to pry a little bit more and kind of dig into that. Talk to us about what you're working on.
Jon Tesser: Yeah, oh man. I'm really proud of the work we've done at NYC & Company. I feel like this is the culmination of what I've done in my very very long data career, but essentially we have at NYC & Company, and this is for audience profile from different countries, right? So British or Brazilian or Chinese or Italians, whoever you want to think of. Essentially what we've done is we've mashed together eight different data sources to come up with these audience profile, who these people are, and the way I like to talk about it is each of these data sources is it different part of the puzzle?
Jon Tesser: They answer a different question. They help us figure out something that the other data sources don't. I don't know if your audience is too interested in this, but we can talk about what some of those data sources are. We have credit card data that we actually collect by different categories where the spend is coming from each individual country and we can break that down by quarter in the year and we can see what's up and down.
Jon Tesser: We created some mega, mega cool wicked dashboards out of that and then so we also look at Google search data which to me is one of my favorite data sources. So we collect that and it's the impression data, not necessarily the click data. What are people searching for and how is it differing by each country? For our six top markets, we did a major survey study where we learned information about how they make decisions about travel and so we put that information there and what's the differences between these markets and how they travel.
Jon Tesser: Then we actually broke out the market and the rich people because we wanted to see what was the luxury travel from each of those markets and then website data, like what kind of content are they consuming and how is that different from everybody else? Social media data, I talk about it a lot and I am a huge fan of social listening data. I don't think it's used very well, but I liked how we did it, which was to sort of... We did something really cool. We use Twitter to find Instagram posts and we just did this very, very qualitative analysis of hey, if you're Brazilian and you're traveling, like what are you trying say about yourself when you travel?
Jon Tesser: That was the question that we were answering through Instagram and looking at the Instagram photos and collecting hundreds of them and coming up with these themes and we came up again. I love sharing insights. One of my favorites themes is about Brazilians and Brazilians want to be seen doing something all the time. This was actually an insight. Again, you take that insight and you can use that for marketing, but I tested this on the Brazilians that I knew and they were like, "Oh my God, yeah, we have to go to a city. We have to be in front of something and show that we're doing it."
Charlie Grinnell: That's hilarious.
Jon Tesser: These kinds of insights. So again, you're like, you're like literally, this is just an amalgamation thing. They all serve a different purpose and you're mashing it together and now you've got a real in depth understanding of who these people are. We haven't even talked to any of them.
Charlie Grinnell: Yeah.
Jon Tesser: That's the best part. We're just taking little thumbprints or breadcrumbs and collecting them and throwing them together and understanding who are these people.
Charlie Grinnell: I want to dig a little bit deeper into this idea of mashing that stuff together. Can you talk about why that's valuable to look at all these different sources and kind of mash them together?
Jon Tesser: Because none of these sources buy themselves tells you the whole picture, right? So if I'm looking at let's say the search data, that's going to tell me that they're interested in Broadway or they're interested in certain types of restaurants or for the British, we learned through that data that they love to go to school sporting events, but that's not going to tell me how they make decisions. So the search data is not going to tell me, what's the booking process? How long does that take? I don't know. You know, not through the search data. The spend data is going to tell me are they more interested in restaurants or shopping or attraction, but it's not going to tell me why, right. So if I'm going to, if I want to find the Y, I'm going to have to go into the social data. The social data is not going to tell me what those other data sources are telling, so you really have to throw them all together in order to get this full picture of these audiences where you're missing a certain part of who they are.
Charlie Grinnell: Yeah. That makes a ton of sense. I think that kind of ties into my next question about the future. What are you excited for when it comes to analytics and insights and marketing in the future? What gets you fired up? Because you're someone who has obviously had a long career but also have worked in some really cool forward thinking applications in this. What fires you up?
Jon Tesser: I'm most excited about, and this is just for the travel industry, because that's where I'm working right now. This idea of mobile location data. I mean a lot of people get sketched out from it, right? Oh no, we're tracking people and they know where we are and when we're going to the bathroom and all that. No. Okay, fine. But what it really allows us do, it's for the time who's outside of the digital world and into the physical world and understand people's movements what they're doing and who they are to a degree that we've never been able to do before and I know it's really sketchy to people and it's scary, but I mean, look, it's already happening on websites people.
Jon Tesser: If you're going to a website, they're tracking all you're doing. So this idea that we can understand and use segmentation and audience segments by understanding things like census track to understand who people are and what they do when they are someone or whether it's at a retail or... For the tourism industry, this is revolutionary.
Jon Tesser: This is information that was never available and is now at our fingertips to use to understand pattern. Actually we have a really cool example of how we just did this for COVID tracking in New York, which was we wanted to understand the effects of social distancing policies in New York City. What we did was we took the mobile location data and we tracked all of the parks across New York City and we said, hey, over time are we seeing fewer devices or more devices in each of these parks and around bridges and tunnels? We could actually, with pinpoint accuracy, kind of understand where the most social thing was happening and how much lack of traffic there was, et cetera. This is exciting stuff and it's useful for so many different areas that have never really been involved in data before.
Charlie Grinnell: I think the privacy conversation is obviously something that I feel like pre-COVID was like a big conversation and what I find ironic is with everybody kind of at home now, nobody's really talking about the privacy thing it appears, and I think about this idea of, there's privacy and then there's convenience, right? How funny it is, how we talk a big game when it comes to privacy, yet here we are on all of our devices, on all of our sites, consuming away, living our daily life because it's convenient and so it is interesting to see what we say versus what we do.
Jon Tesser: Yeah. People are lazy and they're going to take the least course of action and then they're just going to complain that they have privacy and all of this stuff, but at the end of the day, I think that this is the future of data and analytics. There's this data source to move out side of digital and this also helps marketers, not just in the travel industry, but I mean it really helps understand things like, offline attribution. I don't even want to start talking about this kind of stuff, but when you know that somebody has a device and they're moving and they use a certain website, you now have a better understanding of their full customer journey and what they're doing.
Jon Tesser: I know it scares people, but it is to me the most revolutionary and interesting thing in analytics. Notice how I didn't say anything about predictions or algorithms or machine learning. Those are just areas that I don't know much about and I don't know what business value they serve, so I don't even want to start talking about it until somebody can tell me, this is how this stuff is helping businesses. I'm not going to be skeptical but I'm not going to pay it as much attention as everybody else is.
Charlie Grinnell: Totally fair. So as we start to wrap this up a little bit, is there any piece of advice that you want to share for marketers or data and insights folks that they should be keeping top of mind?
Jon Tesser: Marketers need to really care about their customers and who they are. I don't know how to make this any clearer. If they're not upset with getting into the mind of their customer and getting into the mind of who they are. Getting into the mind of why they do things, thinking about it constantly, obsessing about it constantly. Don't get into the marketing game. Do something else, because we need marketers who really are just so okay on that, on who the customer is, and then everything cascades from there.
Jon Tesser: Then you can do tactics and you can do strategy, but if you're not constantly thinking about who they are, what they're doing, where the spending patterns are and keeping up with it, don't go into marketing, do something else because that obsession with the customer and who they are and what they do and why they do it, that's with the great marketers do, right?
Jon Tesser: But we tend to think of marketing as tactics, but the tactic has to come from somewhere and they come from this understanding of the identity of the customer and the great marketers that I've worked with have always had this obsession with the customer and it's always the thing they talk about the most and if anybody tries to move away from it, they bring it right back. I don't know if you've had the same experience, Charlie, but when I do talk to really good marketers, that's what they do.
Jon Tesser: They always bring it back to who that person is. They never let go of that. Somebody will try and move them into a tactical conversation and there'll be like, well, certain segments of our company [inaudible 00:40:39] this kind of stuff. They always have rooted language in that it makes me really happy, but I don't know. I just feel like... And then they can speak to the research teams in better ways and say, "Here's what I need to know about the customer. Can you deliver on that?" So it's not just up to the data person to ask the question. The marketer is there as well.
Charlie Grinnell: I completely agree. What's the best place for people to find you online? I think I know what the answer is going to be.
Jon Tesser: You can find me on LinkedIn. The funny thing is about my LinkedIn is I'm some sort of like a spiritual guru in types things about like modern-day Buddhism and psychoanalysis and acceptance of feelings and all of that, which we didn't talk about at all here, but if you want to follow me for that kind of thing and get your daily dose of Eastern wisdom, you can find me on LinkedIn.
Jon Tesser: If you want to find more of my data stuff, I have some articles that I read on Medium, but I'm really leaving it up to these blogs. Thank you to these podcasts. Thank you Charlie. To talk more about the data side of what I do, because quite frankly, I just don't think there's that much interest.
Charlie Grinnell: Well, Jon, thanks so much for joining me today. I really appreciate you taking the time to share your knowledge and wisdom with us. I learned a lot and I'm sure others did as well.
Jon Tesser: This was a pleasure, Charlie had a lot of fun. Thanks for listening to my ramblings.