Mining Your Own Business Podcast

Episode 18 - Behind the Scenes of Hotel Analytics at STR with Isaac Collazo

Behind the Scenes of Hotel Analytics at STR

On the show today, Evan sits down with Isaac Collazo, Vice President of Analytics at STR.

Isaac shares how he got started in the travel and hotel industry, and how he’s seen data analytics in the hotel space take off and advance over time.

He discusses what type of data STR works with and how they strategize delivering key insights to their clients.

Isaac and Evan also discuss what it takes to be a successful data analyst on these types of projects, highlighting crucial characteristics such as creativity, play, and drive.

Finally, Isaac speaks on opportunities he sees in the hospitality industry and in his current role at STR.

In this episode you will learn:

  • How STR provides insights from data to inform hotel progress and strategy
  • Opportunities for increased consumer understanding via hotel data
  • The importance of creativity and perseverance as a data analyst
  • How increased time and resources allow for long-term high-level analysis

Learn more about why we created the Mining Your Own Business podcast.

About This Episode's Participants

Isaac Collazo | Guest

As a seasoned analytics professional, Isaac Collazo believes that data is not everything and understands the value of relationships when immersing himself in an industry to truly understand its people and experiences.

He is the VP of Analytics at STR where he solidifies the company’s analytical methodology, assists with integration into CoStar’s digital platform, and unifies products and services to provide a single, reliable source of knowledge for the Hotel Industry. He is an expert in delivering meticulously curated insights based on industry knowledge and encourages others to make a personal investment in the insights they uncover. His easy-to-digest knowledge ensures recipients can apply it to their own business performance for an informed and successful future.

Follow Isaac on LinkedIn

Evan Wimpey | Host

Evan Wimpey is the Director of Analytics Strategy at Elder Research where he works with organizations to transform deficient data into tangible business value that advances their mission.

He is uniquely suited for this challenge by pairing his professional experience in management and economics at high-functioning organizations like the Marine Corps and Goldman Sachs with his technical prowess in data science. His analytics skillset was strengthened while earning his MS in Analytics from the Institute for Advanced Analytics at NC State University.

Evan almost always has a smile on his face, which is at its widest when he is helping organizations use data in innovative ways to solve complex problems. He is also, in a strictly technical sense, a “professional” comedian.

Follow Evan on LinkedIn


Key Moments From This Episode

00:00 Introduction
00:57 Isaac’s background in the travel & hotel industries
02:52 How Isaac got started in data collection for hotel decision-making
05:35 The type of data and benchmarking that STR provides
11:55 What it takes to be successful on an analytics team
16:54 Insights from consumer data: seeking to learn more
20:05 Working with data in the hotel industry: the importance of time & resources
21:18 A new mindset

Show Transcript

Evan: Hello and welcome to the Mining Your Own Business podcast. I’m your host, Evan Wimpey, and today I’m excited to introduce our guest who’s Isaac Collazo. Isaac is the VP of Analytics at STR. Super excited to have you on the show today, Isaac. Thanks for coming.

Isaac: Thanks Evan. I’m really excited to be.

Evan: All right, fantastic. Hey, to get started, can you give us a brief introduction about yourself and your role there at STR?

Isaac: Yeah, I’ll start with STR. Obviously benchmarks the hotel industry since 1987, so we’ve been doing this on a hotel-level basis, so lots of great data. Both in terms of depth and width, and so that’s really exciting for my role being in analytics. I started in analytics back when analytics and data wasn’t a thing. When, you know, when you used to have to go down to the – what was it called? The – it wasn’t called the database department, whatever you called it, and asked them for reports so that we could figure out who our customers. And so fast forward then started working with data when it all became available through both you know, PCs and then obviously laptops and databases that are accessible by normal people versus just IT folks.

Evan: Fantastic. And Isaac, you’ve got a background in the hotel, the travel industry, well before STR here. So you really, they’re, I think we’re more of a consumer. You like to use this data. Can you –

Isaac: Yeah, I should have mentioned that. Yeah. I started out in the hospitality business, really in the marketing side with a company called LaQuinta Inns. At the time, it was a publicly held company, so it’s gone through multiple iterations now, but at the time, it was truly publicly held. And then we went to work for Promise Hotels, which was acquired by Hilton. From Hilton. I went to Marriott Hotels and then to IHG. And again, from the time I left LaQuinta through, until I got here at STR, it’s always been on the data. Actually began on the marketing side, but ended up in data because it was the right time to really get, you know, start understanding who our customers were. It’s really how it all began.

Evan: Can you, can you talk about, so I think that probably resonate more with a lot of people where you’re at the hotel, you’re at the team that needs to use the decision to make some difference, to change the way you market or who you market to, or whatever decision you’re trying to make.

Isaac: Yeah. It became, it started very innocently, right? So it began with, say a friend of mine was in reservations and we learned about this new software package, all of you gonna laugh, called Access, Microsoft Access. But it allowed us to get into the reservation data side and it really start understanding who are our customers. And that’s how it began. And we really started playing with data and literally we had no agenda at that. But quickly we became known that we understood how to use the data and how to actually mine data per se. And we had a group of people that were doing some kind of protests that were gonna boycott the hotel, our brand, and we need to understand what the impact of that would be.

Literally, that was the first time I ever used data to understand the size and quantify the impact. Do we need to be worried? Do we need to do something? And that was really, and it just, because we played with the data, we had no agenda when we started this. We just wanted to understand and, you know, being young kids at the time, like, this is fun. This is like, no one else is doing this. We can do this. And that’s how I got started and then after that, yeah, it’s become more complicated. Since then, obviously data is a, there’s a lot more data than ever before, but back then it was pretty innocent. Just learning and exploring and those principles I think, still apply today. People who are on the data side have to be creative and have to just love to play with data because if you don’t, then it’s a pretty boring job.

Evan: Yeah. Yeah. I certainly think so. Yeah. There maybe there’s not as much low-hanging fruit, but there’s still plenty of places to explore that folks haven’t.

Isaac: Yeah. And now we are using data to make to actually make decisions, right? Not only quantifying potential boycotts or whatever, but you really are trying to be informed. It’s no longer gut feelings. Back then a lot of decisions were made just on financial data cause that was available right? Through accounting systems. But you couldn’t really understand the business. I mean, it was just very, you know, just, it was just a different time. And this what’s amazing is not that long ago, right? We’re talking just the nineties when I really, I started probably the late eighties, probably around 89 nineties, started playing with data.

But since then, it’s just been a revolution, right? I mean, it’s just so different. But we had back then, and the access versus what we have access to today.

Evan: Certainly, yeah, very fast-moving space for, you know, a lot of the audience, you know, certainly some hoteliers in here we hope, but a lot of folks maybe not as familiar with the hotel industry. I think writ large data has gotten more complex in the level of granularity that’s collected. Can you just speak a little bit on sort of what type of data and what type of benchmarking STR provides?

Isaac: Yeah, we are, you know, our data set tends to be more on the true benchmarking on the hotel level. Right? So, and we’re looking at three really big pieces of data supply demanded revenue, so very, in some ways very simple. But again, it’s the bedrock of everything at the hotel level, understanding and creating their own strategies based on what they’re seeing from competitors.

And so we collect it on a weekly and monthly basis. So that’s our primary data set. And again, we’re getting it. We get in the US alone, we have 35,000 plus hotels that give us data on a monthly basis. So it’s deep. It’s really, it’s awesome because you can get down to hotel level, you can build great models with it.

Obviously we protect that data, so we do not give our subscribers the ability to get down to a hotel level because no, that would be violating privacy and everything about and confidentiality. But what we do is we aggregate it. So we provide industry-level metrics. We provide market-level metrics, but more importantly, we create a cop set.

And so a hotel. Or whoever operates the hotel can create their competitive set. It has all kinds of restrictions. You have to have a minimum four properties, no one brand can be 60% of that, no one company and things like that. Again, to provide, to provide a level of confidentiality. But thereafter, you can really see and track how you’re doing. And again, four is the minimum. You can have more if you’d like, but we provide you with rankings, we provide you with all kinds of data diagnostic tools that allow you to understand how you’re doing. So the way to think about it is, theoretically the comp set is like if you run, it’s your cohort, right?

Your running group, your age group, and you’re seeing if you’re running at the same pace as they are. And essentially, that’s how I always think about benchmarking. It really is. is your pace as good as theirs? And it makes it simple if you think that way. And then as long as you have the right age group, like if you’re comparing yourself, you know, my age to a 20-year-old, yeah, probably not gonna be, probably not gonna win that race. But if I’m comparing it to other folks my age, I have a chance. At least I have a chance to win.

Evan: Okay. That’s a great analogy. And I suspect, Isaac, that you’re outrunning plenty of 20-year-olds.

Isaac: I used to run with some 20-year-olds. I’m kind of, I’ve gained weight. Can’t do it right now.

Evan: So maybe it’s just, maybe it’s as simple as, you know, there’s supply demand and there’s revenue, but is there anything, do the hoteliers have an appetite for more? Do they come to you and say, Hey, could you get us this? Can you get us –

Isaac: Yeah. We’re in the middle of a massive change within STR and I should have mentioned some other products we have, but right now we are changing. We were purchased by CoStar back in October of 2019, so essentially we’re moving onto their platform. So really our focus since then has been lift and shift, take what we have to, what we’ve had in the past and put it into the CoStar platform, which essentially we wanna think about it in a more marketing terms. STR has always been a push kind of strategy where you push the data to you. Well, CoStar’s a pull strategy where you get a subscription, you can pull the data as you need it. So again, our focus has been on just lifting the shifting, moving everything over with the existing products. But in the future then we will be looking at other data points including channel, possibly rate codes, but even then we’re actually thinking bigger, so we still think there’s more out there, more exploration that can be done with the data set we have. That just hasn’t been done because again, just thinking about the forecasting side, we have data going back to 1987 on a hotel level basis. You can do a lot with that. The old legacy systems, you couldn’t because you really were just doing printed reports, but online systems. Yeah, we have a, we can do a lot and that’s our focus thinking of “how do we use the data we have to take it to the next level?”

So that’s the current data set, the benchmarking piece, the piece I didn’t mention was our P and L data. We’ve been also getting profit and loss statements from many hotels since – I’m trying to think of the year. It’s sometime, it’s before 2000, so let’s say 98. It may be later than that or earlier than that. But again, it’s P and L data. So we have GOP, we have margins, we have expense side that also – and again, it’s on a hotel level basis – that also gives us the ingredients to do something no one else has done. And so, because again, we have just, we have just the depth of that data and the breadth of it.

So yeah, we’re working on lots of things. I’m not a liberty to give all the things we’re working on, obviously, but again, it just gives you an idea when you have data, again, the data sets we have, yeah, you can do a lot more, and no one’s ever done it. So that’s why I am super excited about being here. I mean, every day I come in and go, this is great. It’s the biggest sandbox there is. Or if you want to think of it another way – in the past, we provided users with the ore and they, and they polished it, made rings with it, whatever they wanted to do. We just provided the ore. Now we’re looking at how do we use that ore? We have the mine. Why don’t we create things that people can use? And so that’s how we’re kind of thinking about it, and so we’re hoping to create lots of diamonds in the future.

Evan: Very awesome. Yeah, that, that’s very exciting. You know, big data maybe not as the term du jour like it was 10 years ago, but there’s so many teams that have challenges they wanna solve. Well, we’ve got historic data, but it only goes back 18 months. Or it’s granular now, but you know, only for the last 12 months has it been this granular.

Isaac: And they probably don’t, again, most people don’t even have the access to what we have, the resources. Again, the greatest thing about being with CoStar now is we also have access to all their real estate data. So you think of it from industrial to offices to shopping centers. There’s a way to marry all that and create, again, something that no one else has talked about or seen.

So again, we are trying to think that through and you know, how do you use that? How do you put it together? How do you do something again, how do you create a new dish that no one else has done? Because we have ingredients.

Evan: Yeah. Very, very exciting. It feels like a very exciting space to be in. You’re vice president there. You’ve got some, some folks on your team that are trying to make these diamonds with you. Can you talk about the composition of your team? What type of folks are there?

Isaac: And this is a question I’ve been asked, you know, multiple times. I think what’s interesting about the teams, I’ve always built both and most of what jobs I’ve taken is, you know, foremost – We know we’re looking for a skillset set. Someone who knows how to work with data. Got it. There’s lots of people who do that.

But what I’m actually looking for is someone who is very creative and who has more of a strategy mindset. Not only can they use data, but they understand that we’ve gotta get to a decision or an outcome. And not, and you cannot come back to me and say, well, we don’t have the data to do that. Okay? I need you to figure that out. There has to be a proxy. What would you do? Because we have the decision to make that’s, that’s a truth. And this is all we have. And there is no such thing as perfect data. I, in all the jobs, there is just no such thing as perfect data, right? So I look for someone who’s very creative and enthusiastic. I’m looking for someone, you know – it’s funny when I interview someone, it’s for those of you who ever interview with me in the future, now you know that you’ll know. But if someone says, data is fun. I like playing with data. You’re in, man. You’re in. Because I know that that’s, it’s a passion. It’s something that you wanted. You’re gonna dig and you’re gonna figure it out. And it’s not just gonna be limited by, oh, there’s no data. And I do find that in some analysts that we interviewed and some people have worked, it’s like they just, they don’t know what to do. Well think it through. What would you know, what could you use to get that proxy to get it close? And then again, for me, some data, some information’s better than no data.

And I’ve always, and even when I was talking with the executives that, the various companies and saying, well but you know, they’ll question it. And I said, well, this is all we have. This is how we thought about it. This is how we’ve come to the decision, you can either use this information or you have nothing. Well, I think this is, having something is better than nothing, right? And I think that’s all just people have to think it through. But again, advice people just to get away from that mantra that they need perfect data cuz it just doesn’t exist and we’re even, we are the closest to it, I think, in a hotel space. And it’s not perfect there either.

Evan: I hope that this resonates with a lot of folks of you. You just, you know, five minutes ago you were talking about how rich your data set was, and then at the same time, but don’t have perfect data. We need people who can be creative to try to find the right things.

Isaac: Yeah. Just, and again, you know, I’m thinking about algorithms all the time. How do we, how do we use what we have to get to what we don’t have? I mean, literally, that’s what I’m thinking about. And I actually we’re in the middle of doing some work right now, and that’s what I put down. I said, I think there’s a way to do this, even though we don’t have the data. Let’s figure it out and we can prove it out. Cuz we can do all kinds of testing. But I think that’s how you have to go to it. But again, to me, people, I want people that are enthusiastic, truly enthusiastic about data. And, you know, they don’t have to be extroverts like I am, but it just that they have that desire, that appetite and they’re just so engrossed with data that that’s all they think about and that’s what you know, as a leader, when in most of my jobs, my whiteboard here’s not great at the moment, but normally I just put up ideas and then let the team say, this is what I’m thinking about. How do we do that? And I love it when someone comes back, cause I figured it out. This is how we would do that. Because I have the idea, but I may not know how to do it either. But that’s why we bring people who just wanna think it through.

Evan: Yeah, and I think that’s a great point too. You know, with sort of a rich history in the space, you can really drill down the things that are important. You can think of good ideas, but staying on top of tools, techniques, ways to use a proxy or to approximate those change so fast and the tool, you know, if we would’ve had this interview two months ago, there are different tools that are, that are at the forefront.

Isaac: I’m less concerned about, again, I’m, you need to have some ability to use certain tools, obviously. Right. But yeah, they changed so fast given my career. I mean, we went from Microsoft Access, come on. You know. So, but then I’ve used everything under the sun, and some things I never even learned to use, I let others learn cause I said, okay, I don’t need – that’s, I don’t need to learn that, but you, I need to have some knowledge of it, but I don’t need to actually know how to program that. But it is, yeah, the tool thing is important, but it shouldn’t be, it should be the appetite and the desire. Again, the eagerness. I guess it goes back to anything. You want someone who’s passionate and eager and who’s just going to stick with it. You don’t want someone just because they can un- they can program, but you’ve gotta force feed them of what to program. It’s like, no. That, well, we can hire that, that’s a development team and we can certainly hire for that. And that’s different.

Evan: Yeah, spot on. I think you meet some threshold and you’re eager to learn. Well, you’ve shown that you can learn the newest tool or learn what you need to apply to this problem.

So, Isaac, you’ve got a lot of data. You don’t have everything, and it’s not perfect if you’ve got the, you know, the magic button for STR you guys find tomorrow you find that the brand new untapped data source at, if you’re allowed to mention it, like what? What’s the data you wish you could collect or you wish you could collect cleaner?

Isaac: You know what, actually it’s, it’s more the transactional, but the consumer side, right? So, and again, you know, a lot of consumer companies out there getting consumer data and it’s very, it’s hard. It’s not hard. It’s just a lot of data. But I’d like to know more about the consumer because we make a lot of hypothesis about the consumer. You’re hearing a lot about leisure, you know, I’d like to understand really? Could I see that again? No one has the magic answer. We’re looking at it by days. Is it more than one person in a room? Things like that. But God, if we get even deeper than that, what is the true hotel consumer? Could we, you know, could we do something more?

I’m, yeah, again, more transactional. I’d love to get married with trying to almost like a census, you know, could we get, could we give people a barcode? That’d be the easiest way. And really get the transactions and understand what an individual – could we then typecast a type of individual and really create segments that are richer than what they are today. And again, no one has that. Even at the hotel side, it’s such big data. No one else, no one’s really put it all together. Even with all the loyalty schemes, it’s still, they’re skimming the surface, right? So yeah, we can get all the loyalty data from all the companies. That’d be wonderful. But again, that would be, that’s a long time coming. I think that’s a, first of all, that’s, I don’t know if the companies would give it to us, right? Cause that’s their secret weapon.

Evan: Yeah. Absolutely. That makes perfect sense. And it makes sense that even if it’s, if it’s sort of skimming the surface for insights or decisions, the infrastructure’s there to collect that. I know when I’m staying at a hotel, the first thing I do is, do I have a rewards number? If not, okay, sign up for, for rewards program.

Isaac: Yeah, that would be the, again, that’s cuz again, that’s the piece that I’ve always thought in the hotel, even when I worked in the hotel side, we just haven’t minded as well. I mean, there, there’s some, it’s not saying it’s not being used, it is being used obviously, but I think there’s a lot more space, a lot more, not ability, but opportunity to do more with that data,

Evan: Sure, sure. Yeah, I think. Maybe, maybe this is one of the places where like retail consumer goods is a little ahead. They’ve been on that. Everybody knows you’re at the checkout line, at the grocery store, you’re scanning your card and then somebody knows, okay, here’s the purchase pattern. People who buy this, you know, here’s, here’s what to look forward to.

Isaac: It’s almost, it’d be almost like what Facebook does, lot of the social media where they target the ads, almost the same thing. I’d love to be able to like target my data analysis based on that, but it, that’s, again, I think that’s a while ago because that’s again, the companies, I can’t foresee them giving that to many people because that is their secret sauce.

Evan: Sure, sure. Yeah, that, that makes perfect sense. Yeah. You don’t have a, a general hotel rewards card. You have a Marriott –

Isaac: Marriott, Hilton, IHG, I mean, yeah, and they protect that pretty closely.

Evan: So I know some of the, a lot of the work we do, we’re working with data providers in this retail space and it’s always, well, why can’t they have this? I wish they would have this. Why are there all these caveats? You came from the hotel before you, before you’re here at the data provider. Do you have any, is there any like wide awakening, eye-opening moment that misconceptions that maybe you had or that people tend to have in the hotel space?

Isaac: Not really. I mean it all goes back to time and resources, right? And so all of us in the big companies, cuz again, I’ve worked for some very large companies, relatively speaking, STR is small, even CoStar’s relatively small. But It’s just time and resources. Right? And so you, and you know, with the roles I’ve been before is more on the finance and strategy side. So we’re using data to make decisions, more financial and strategy, you know, strategic decisions. And you just couldn’t, you didn’t have time to do the other fun stuff, right? And again, it gets, what happens I think in the big companies is everything becomes very tactical and at the moment, right? So even though you have this idea, I’m gonna work on this today. Well, we need the answer to this. We need to look at this. So it becomes just a very tactical process. And I think that’s why it feels a little tactical, right? Because it is just day to day and not taking that holistic view and they just don’t have the resources or the time to just let people wander and play with data.

And again, that’s what’s really cool with STR is that we do have that, because we are providing the reports, that’s pretty automated, everything to that. But my team on the other hand is more, Hey, we get to play with this and figure something. And that’s what I like about this role versus not previous roles.

Evan: Yeah, very much. Yeah. If you’ve, if you’ve automated, if most of the day-to-day on autopilot, there’s not the constant fires to be putting out where you can take that higher level look and viewpoint, and also hence the why creativity is such a valued asset for somebody working there.

Isaac: Yeah. And again, it’s an asset. Like it’s when I was at IHG as well. But again, we were more driven by than the immediate needs of the business at that point in time. Right. So we’ve gotta make this decision. We’re looking at this, we’re looking at that. What can you tell us about that? It’s just very different. It wasn’t pie in the sky. What, what kind of it is now here? It’s, we get just, we’re trying to, okay, how do we improve the product? It’s a very different kind of mindset. I don’t know if I explained that right, but it’s just different.

Evan: Yeah, it makes sense. And I think you know, I don’t know that I’ve ever thought about it this way, but it really is, it really is appetizing to be at a place, you know, to think of the data like that, where you’re not at the tactical putting out the fires on, you know, this report that’s coming out this month, it’s okay. We can think long term. We can think strategically.

Isaac: Yeah, in my previous job I was work, we do quarterly earnings, things like that. And I mean, that’s just very scheduled, very tactical. Just, you know, you are working on that to make certain that you had all that ready to go because you can’t miss your quarterly earning state. So it’s kind of important. So it’s very different.

Evan: Awesome, Isaac, thinking big, thinking strategically at STR. Isaac, thank you so much for joining us on the show today. Our guest has been Isaac Collazo, VP of Analytics at STR. Thanks so much, Isaac.

Isaac: Thanks Evan. It’s been great.

Evan: All right. If you enjoyed this, make sure to like and subscribe to Mining Your Own Business podcast. Take care.