2025, Digital Travel. CASE STUDY PRESENTATION: Data-Powered Decisions: Building a Future-Ready Portfolio of Decision-Centric Data Products

Announcer: Next up we have a case study, data Powered Decisions, building a Future Ready portfolio of Decision Centric Data products with Lauren and from Choice Hotels. Take it away, Lauren.

Lauren Byres, Senior Director, Data Product Strategy & Transformation, Choice Hotels (2): All right. Good afternoon. I don't think I can advance my slide. Hey, tech.

Okay,

great. So it looks like it's frozen up here.

Okay, good afternoon everyone. My name is Lauren Burns and I lead data and analytics strategy at Choice Hotels. I've been with Choice for a little over 11 years now. In that time, I've worked in marketing and loyalty and for the past several years in analytics, that's given me a bit of a unique perspective.

I've seen how data is used by teams across the organization and also how analytics can connect the dots between them. So that's also why I'm so excited to be here today. At Choice, we've been on a journey to transform how data and analytics are driving our business. And today I'm going to share how we're turning data into off the shelf data products that are driving real world decisions like portfolio optimization, personalizing the guest journey, all while preparing for an AI enabled future.

The past year, if not longer, has been a whirlwind of conversations about ai, and I'm obviously still gonna talk about AI today, but I wanna focus in on where we've actually been using to drive business impact. And before I tell you a little bit more about Choice Hotels, and I will for anyone not familiar with the brand.

One more thing about me. I used to lead consumer insights prior to moving into my current function. So naturally I come with survey questions. So let's see what you know about Choice Hotels. So the first question I have for you, and show of hands, how many hotels do you think Choice has worldwide? Do you think it's a about 3,500.

B, about 5,500 or C, about 7,500. Okay. Smart Room. That's correct. We have a little over 7,500 hotels across 46 countries, so not bad. That makes us one of the largest lodging companies in the world. And just one more, I won't drive us down here. Which brand do you think was the most recent addition to the Choice Hotels portfolio?

A Radisson Hotels. Be ever Home Suites, c Cambria Hotels or D Wood Spring Suites. Okay, I got you with that one. So the answer is Radisson Ho Hotels and all these brands are Choice hotels, brands, and do represent some of our latest brand launches of brand acquisitions. But in 2022, we acquired Radisson and brought them into our portfolio in the Americas.

So now we have 22 brands serving millions of guests and loyalty members each year. Comfort and quality are some of our most well known brands, but our portfolio actually spans from economy all the way up to upper upscale. So everything from a roadside budget friendly hotel to a design forward urban hotel location, serving everything from family vacations, road trips, business travel, and extended stays.

And most of those hotels are owned and operated by a diverse community of franchise owners. Our role is to empower those owners with the tools and the insights that they need to succeed. So when we talk about data and analytics, it's not just about the guest, it's also about enabling smarter decisions that allow our owners to succeed and drive that growth for our owners.

At the heart of this is our advanced analytics team, so we're not just some group of numbers people that have been shoved into the corner. We're a group of data scientists, building predictive models, researchers getting under the hood to understand what motivates guests engineers that keep data flowing reliably and strategists that are ensuring that those insights connect back to the business.

Our mission is to put analytics and AI into those core business decisions that matter most for choice hotels, and along the way, we've pushed ourselves to keep learning. So starting back in early 2023, we began building hands-on expertise with generative AI and large language models, and now we're getting to apply those tools in some cool ways.

For years, organizations including choice have talked about being data-driven, and that's been needed. It's allowed us to build better models, richer reports, better dashboards. But the reality is that data by itself doesn't drive value. Decisions do, and when analytics doesn't connect back to the decisions that need to be made, that's when things can get messy.

That's why at choice, we're moving to a decision centric approach. So rather than multiple reports, manual number, crunching, delays, and potentially suboptimal decisions with a decision centric approach, we are trying to start with the question rather than the data, what is the business decision that we need to answer?

And then our goal is to get the business as close to that final decision as possible. Rather than delivering a generic dashboard that still requires interpretation, let's deliver something that answers that question for them. And in some instances that might mean automating the recommendation and other instances that might mean the decision is fully automated with human oversight.

And it sounds so simple, but the reality is that this is a shift in how many analytics teams operate today, or it's a shift in how the business engages them. So let's start with one of the most critical decisions in hospitality portfolio optimization, where to build, where to invest, and how to maximize long-term value.

What you're looking at here is our hotspots tool overlaid part of the state of Florida. Think of it as a key map for new construction opportunity. It highlights the markets with strong indicators of where our hotels are most likely to perform, so that way our sales team can zero in on those markets where they're gonna see the greatest return.

But hotspots is just one piece of the puzzle. And when we're talking about conversions, so not hotels that we're building, but hotels that we have the opportunity to convert into the choice system. We've built targeted lists of prioritized hotels for our sales team, prioritized by modeled revenue performance, expected guest satisfaction, among other factors.

So our sales team can again, spend the time on the hotels that are most likely to perform well if they were to convert into the choice system. We've also built automated feasibility models that can quickly help to estimate the value of a new construction or conversion deal, providing reliable inputs for our leadership to allow them to make faster investment decisions.

And because retaining a good hotel is as important as adding new ones. We've built an owner retention model which flags which franchisees might be at most risk of leaving the system, so that way we can proactively engage them and provide the support that they need to stay into the system. And lastly, we're advancing a tool called dict.

This one looks further into the future and also keeps us better informed in the moment it pulls in climate risk data and infrastructure trends. Helping us understand where our hotels might be more vulnerable in the long term. The things like flooding, hurricanes or wildfires. And also where new opportunities like EV charging or solar might present opportunities for hotels, but it doesn't stop there.

Geo predict also allows us to monitor events like hurricanes and wildfires in real time so we can quickly assess which properties might need support and also, provide additional support for our guests or even adjust our forecast moving forward as well. So all of these products were built around business decisions that used to be manual and time consuming with our goal of trying to get the business as close to that final decision as possible.

But we're continuing to iterate and improve here, and I can see a world where this is all one product rather than five different products. Another big focus area for us is personalization. We've built hundreds of predictive features into our customer data platform. Things like lifetime value and passion points.

Are you a road tripper, a sports enthusiast, a theme park lover? All that information together helps give us the bigger picture of the guest and informs how we should engage them. Next time. It also, it starts to get pretty cool when we can use this across all of our channels. So email, app, website, loyalty, touchpoint.

So that experience feels connected for the customer no matter how they're interacting with us. We're launching this right now, so I'm really excited to see what analytics we introduce on top of this as well. And on top of that, we've created a realtime website sort order model so that when someone logs on to choice hotels.com, the results aren't static.

The hotels that they're seeing will shift based on their preferences and their behavior. And we're pushing a bit further. We're exploring how large language models can take guest feedback. So our post-day surveys, reviews, even information into the call center to suggest personalized property improvement plans for our hotels at scale.

That way our hotels can focus on the areas that are most important to guests and in the future, we're thinking about how we can use photos from our property inspections as well to take it to the next level. So all of these are aimed at delivering experiences that feel more personalized to our guests at every touch point.

And then the F third focus area I have today is revenue strategy and B2B sales. So just last year our testing and our optimization drove more than $15 million in incremental value that came from all kinds of experience or experiments, like tweaking member rates, a meta search, flash sales co-brand campaign.

We're also using network analysis to identify partnerships in a more modern and intelligent way. So take a coffee chain, for example, if we were to partner with a coffee chain, which has the best overlap with our hotel distribution, what about the best overlap with our customer's home addresses? When we start to look at it that way, that shows us where there's real value for our consumers rather than just something that looks good on paper.

We're also applying large language models in a couple of different areas in sales. So one is to automate group attribution, basically connecting all the group bookings that take place back to the corporate accounts. That one's not as exciting as some of the others, but it's a lot of manual work that happens for our sales team today and we're freeing up some time for them to focus on sales selling.

We're also applying it to our sales funnel itself. So consolidating all these different leads that we get from different sources down to one consolidated view, and then we can apply AI on top of that to score which leads have the highest opportunity for our sales team to go after.

So what are we working towards? I've shown a few different examples of what we've accomplished, but I still think we're at the beginning stages of moving towards our decision centric mindset. To get there, one of the first things that we need to be doing is working across the company to document and prioritize those critical business decisions.

Today we do a really great job of working on those business decisions that the business brings to us, but we realize that we don't have the full picture of all of those high impact decisions that happen around the company. We need to go out and start pulling them in rather than company or our departments pushing them to us.

So this is what we're going to be doing. And once we have that prioritized list of business decisions, then any analysis that we do and data products are gonna be personalized to that specific business decision, providing clear recommendations and actual insights. After that, we start to automate. So that's where, when our high impact.

Recurring business decisions can be automated. And again, that can mean automating the recommendation that a human then goes and acts upon. It might mean automating the full process with human oversight, but either way, we're freeing up time for the business to focus on strategy and bigger picture items rather than trying to get all this data together and make a manual decision.

And lastly, the hardest part decisions are tracked, measured, and continually refined. So there are some areas today where we're already doing this, like our website sort order model. There are other areas where it's much harder to track the decision, like the decision to retain or replace a hotel, for example.

But this is exactly what we're working towards. So our aim overall is to create a decision making environment where AI is a natural part of the process. All of this rests on a strong foundation. So over the past few years, we've put a lot of work into building a data culture. At Choice Hotels, making sure our data is governed, democratized, and discoverable in practice, that means that teams can find the data, trust it, and use it with confidence to keep that trust.

We built anomaly detection models on top of this data to flag any issues in real time. So instead of waiting for someone from the business to come to us and call it an issue, we can see things happening before the business actually gets that data and correct it. And while our infrastructure is already strong, the rise of generative AI has raised the bar.

So we do still have some systems that are siloed. We're looking at opportunities to bring that together and create centralized access to data. We're also enriching it with external data sets as well, and laying the groundwork for truly AI ready data. But it's not just about data. So as I've heard almost everyone talking about today, it's also content.

We're taking a look at our content ecosystem. We have stood up a working team that spans marketing, SEO, pr, digital technology, brand ops. It goes on and on so that as we're thinking about content, we're all approaching it together in one cohesive and consistent strategy. And finally, none of it matters if the people don't feel confident using the tools.

So that's why back in 2023, we invested heavily in data fluency. We rolled out a training program, we called data discovery. And this year we're expanding it to cover AI fluency as well for our associates. So they know how to use AI responsibly and feel comfortable using it.

But what excites us is also what's ahead. So Gartner describes this next stage as perceptive analytics, where AI doesn't just analyze data, but it interprets context, intent, and nuance. So think fraud detection, for example. Rather than having a specific list of rules that we're looking to see if they are violated.

AI can detect whether someone is acting strange and identify fraud just based on that change in behavior. Or imagine a world where we have a frequent business traveler that now is ch or acting differently because they're traveling with their family. If we can pick that up in real time, we can start to change the offers that we're providing to them and tailor that entire experience.

By 2027, Gartner predicts that half of all business decisions will be augmented or automated by ai. That kind of shift will change everything about how travel works, how guest search and book, how owners operate, and how all of us can compete in AI driven marketplace. So at Choice, we're trying to lay the groundwork now, so we're set up for success for that future.

So I'll just wrap up with this. At choice, we're not looking at data as just another asset that's sitting on the shelf. For us, it's about turning that data into decisions, the kind that create real value for our owners, for our guests, and for our business. Thank you,

Announcer: Lauren. Thank you so much, Lauren. Lauren, we actually have time for two questions, if you don't mind.

Lauren Byres, Senior Director, Data Product Strategy & Transformation, Choice Hotels (2): Okay, sure.

Announcer: Does anyone have any questions for Lauren in regards to the presentation of today? We have one mic over here and one mic over there as well.

Audience: Hi Lauren. Thank you for your presentation. You mentioned at the close about personalized offers. Is that something that Choice Hotels is able to do currently or is that something that you're working towards with your. Data structure and CDPI

Lauren Byres, Senior Director, Data Product Strategy & Transformation, Choice Hotels (2): didn't hear the first part. The what about personalized offers?

Is

Audience: that something that you're already putting into market?

Lauren Byres, Senior Director, Data Product Strategy & Transformation, Choice Hotels (2): We are. So we do use personalized offers today. Even with our creative as well, we personalize that down to the different persona of consumer that we have. But with our CDP, that's going to allow us to be even better. So right now, if we have different segments of consumers.

When we go and buy media, that is in a different system, right? And if we go and do a different campaign, it's in a different system and it's been really hard to have a cohesive strategy across all of these different teams. So our CDP will allow us to do that in real time.

Announcer: I. Great if no more questions. Thank you so much, Lauren.