In this episode, Whitnee Hawthorne, Global Head of Travel and Hospitality at Snowflake, sits down with Julia Morrison, VP of Data & Privacy Engineering at Marriott International and Dan MacDonald, VP of Data Platform Engineering at Marriott International where they talk about how Marriott harnesses the power of data and AI to elevate guest experiences across their global portfolio. They also discuss how Marriott is implementing industry-leading data analytics strategies to innovative AI-driven concierge services and ways their data platform is shaping the future of travel and hospitality.
In this episode, Whitnee Hawthorne, Global Head of Travel and Hospitality at Snowflake, sits down with Julia Morrison, VP of Data & Privacy Engineering at Marriott International and Dan MacDonald, VP of Data Platform Engineering at Marriott International where they talk about how Marriott harnesses the power of data and AI to elevate guest experiences across their global portfolio. They also discuss how Marriott is implementing industry-leading data analytics strategies to innovative AI-driven concierge services and ways their data platform is shaping the future of travel and hospitality.
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[00:00:00] Producer: Hello and welcome to the Data Cloud Podcast. Today's episode features an interview with Julia Morrison, VP of Data and Privacy Engineering at Marriott International, and Dan MacDonald, VP of Data Platform Engineering at Marriott International, hosted by Whitnee Hawthorne. Global Head of Travel and Hospitality at Snowflake.
In this episode, they talk about how Marriott harnesses the power of data and AI to elevate guest experiences across their global portfolio. They also discuss how Marriott is implementing industry leading data analytics strategies to innovate AI driven concierge services and ways their data platform is shaping the future of travel and hospitality. So please enjoy this interview between Julia Morrison, Dan MacDonald, and your host, Whitnee Hawthorne.
[00:00:47] Whitnee Hawthorne: Hi, everyone. Welcome back to the podcast. I'm Whitnee Hawthorne, Global Head of Travel and Hospitality at Snowflake, and today we are thrilled to have Julia Morrison and Dan MacDonald from Marriott with us to discuss their data journey. Julia is the VP of Data and Privacy Engineering, and Dan is the VP of Data Platform Engineering. Together, they oversee data strategy for Marriott's global brands. Julia and Dan, welcome. It's so great to have you here. Thank you.
[00:01:12] Dan MacDonald: Thank you. Great to be here.
[00:01:13] Whitnee Hawthorne: To kick things off, how do your positions contribute to managing data across Marriott's portfolio of over 30 brands and 9, 000 plus properties worldwide?
[00:01:22] Julia Morrison: Well, thank you, Whitnee. So, here's how you might roll. We're trying to implement the industry leading data analytics strategy where all the data is together in one place. And all of it is clean, governed, and available for analytics, be it a simple reporting or a sophisticated data science model, so that we can serve our three main stakeholders, our guests, our associates, and our owners and franchisees.
We have built our data platform in such a way that we can provide a variety of experiences for our customers. For example, we can surprise and delight our guests with a great experience of property. For our data scientists, if they need to build a complex data model, they can do that. For our owners and franchisees, if they have a report about their property reservation data, we can provide that. Our goal is to enable many, many scenarios with data across the internet.
[00:02:16] Dan MacDonald: My team and I are responsible for building and operating a world class data platform that supports and enables a married growth strategy. We're constantly watching for trends in the data space, tracking their maturity curve, deciding when and how to integrate them into our platform.
Typically we look for the intersection of maturity and business need. At the same time, I'm very diligent about our ability to support our platform by eliminating redundancy and critical failure points. Data is a precious commodity and needs to be treated as such. It is a lot to juggle, but I'm fortunate to have a great team and a tremendous set of partners who enjoy the work we do and the value that it brings.
[00:02:57] Whitnee Hawthorne: Marriott Bonvoy's program has over 200 million members. How does your focus on data engineering enhance this massive loyalty program?
[00:03:07] Julia Morrison: So first of all, a big shout out to all of our Worldwide members listening to it. We greatly appreciate your loyalty. Second, of course, to manage a large loyalty program like what we do, we want to use data that we have available to understand our customer better.
Understand what excites our customer, what passions they have. What trends we see with them and figure out how we can serve them better and create great experiences for them. So for example, I'm sure you've heard about Marriott Bonvoy and Starbucks partnership. And where we allow members to link accounts and then when they stay at Marriott hotels, they can earn triple stars.
When they order their Starbucks coffee. So in order to provide that experience, our data engineer had to build quite a few data pipelines, all of that while sipping Starbucks coffee, of course, and so that that data is connected in the experience is seamless to the customer. It all had to be scalable because we have millions and millions of customers.
They stay in our hotels every night and the data has to make it from point A to point B very fast. This is just only one of the examples of how data helps us enhance customer experience.
[00:04:19] Dan MacDonald: And the Bonvoy program is tremendous. And I never get tired of talking to our members and how much they really and truly enjoy the program and the loyalty that they have.
It's, it's really amazing. They wear, they wear it as a, as a badge. You can imagine our data platform and the role it plays. Behind the scenes of a loyalty program. Julia talked about the Starbucks partnership. We also have a, a comparable partnership with Uber. And it's really the, the data and analytics that drive these programs.
From the initial, analysis to determining the value of the programs to looking at the overlap of members that we have between the programs to the data pipelines that are constantly sending data back and forth to enable these additional partnerships for our members. And this is really one place where our data platform shines.
[00:05:19] Whitnee Hawthorne: As a Marriott Bonvoy member, thank you for the shout out, Julia, and also for creating these amazing programs. How do your teams collaborate to create a data strategy that spans Marriott's diverse range of brands from luxury to select service hotels?
[00:05:34] Dan MacDonald: It's amazing the diverse range of brands that Marriott offers. I have a personal goal to try to stay out of property in every brand, but when I get close, we just add more offerings. While the data needs to differ by brand, the fundamentals remain consistent. Holistic, integrated, timely data of high quality. www. marriott. com My team and I focus on delivering a consistent set of capabilities that are used to curate data for each and every brand.
[00:06:04] Julia Morrison: So, obviously, what will be different across brands is not only the level of service to the guests and guest expectation, but the amount of data that we have and collect for the guests. And while we try our solution to basically be brand agnostic, we sometimes need to have controls like data quality.
Quality controls that will be different by brand. And then the data monitoring needs will be different. So for example, you know, we work with reservation data and reservation data will be kind of standard across hotels. You have arrival date, departure date. You have the room type that guests is staying at, and you have a rate.
So all of that is collected. Pretty much together, regardless of what brand it is. However, when you talk about quality control, for example, you might want to say, well, I want to control and see if my rate per night is reasonable. Well, a thousand dollars in Fairfield Inn in rural United States, it's probably quite high and somebody needs to look at the data quality.
However, the same rate in New York City for St. Preach's, especially in New York City. It's kind of your typical rate. So that's how we, you know, differentiate between brands. A lot of it is in the data quality monitoring and similar controls.
[00:07:22] Whitnee Hawthorne: Can you share an example of how data driven insights have improved guest experiences or operational efficiency across Merit's global operation?
[00:07:30] Dan MacDonald: I recently attended a Merit leadership summit and had the pleasure of meeting some of our general managers. And these folks are just incredible. And it's amazing to understand all that goes into managing. It's really like managing a small city. And these teams live and die by a set of key performance indicators, ranging from guest satisfaction, to revenue per available room, to membership enrollments. All of these KPIs are sourced from the data platform, and they really help guide the GMs and their leadership staff in how to run and improve.
[00:08:11] Julia Morrison: So, I would like to add that from customer perspective, one of the ways we provide is the data to surprise and delight our customers across all of our portfolio brands, including premium luxury brands. So, remember a long time ago when you stayed maybe in a boutique hotel and you were greeted by the same person?
Oh, all the time, that person might know your pet's name. And if you like extra towels, well, now we want to strive to create the same kind of feeling and experience across global portfolio of properties. So of course, and we'll talk a little bit later, I'm sure about privacy, but for customers who opt out on that, for us to collect that data, we Can add their pet's name and the fact that they want extra towels to their profile.
So it's easier for them to manage it. And it's easier to manage it across our channels, whether they book a digital channel or they call our customer engagement center, or they chat to the property so that when you arrive on the property at that kind of greeting experience, the front desk agent will knows about your preferences and can deliver on them.
[00:09:23] Whitnee Hawthorne: So, how do you balance personalization efforts with guest privacy concerns, especially considering Marriott's global presence and very international data regulations?
[00:09:32] Julia Morrison: So, the privacy and protection of our guests is very important to us, and that's why we work very close with our Data Privacy Office and Chief Privacy Income Officer.
In our profile system, guests may opt in or opt out from how we use their data, and we abide by that preferences. But there is also privacy. Obviously, a default, a loss, depending on where you live, that we also abide by. I wanted to talk a little bit about some of the innovative functionality that we delivered, and one of them is, uh, what we call a privacy filter system.
It's actually kind of innovative concept, kind of cool. As you know, the proper data sharing, there are a lot of regulations that change all the time with data we can share and with data we cannot share. And as I said, a lot of it might depend on where the customer lives. In Europe, there would be different laws, in United States, it's also varies by state.
And they change all the time. So, one of the ways before, every time we had a data sharing relationship, and the laws would change, somebody would have to dive through the code, go talk to lawyers, and figure out, hey, you know, can I share this data, can I not share? Changed the code, tested, a lot, a lot of work.
We now created a system where all of that is configurable and is called Data Privacy Field. So we figure out the rules based on the data sharing relationship. And then if the laws change, the only thing you need to do is to change a small piece of code, configurable code that translates from the privacy rule into the code.
And by registering all of our data sharing feeds. Not only we know that we are staying compliant with the laws, we also know that we can quickly adapt to the laws as they change. So I'm very proud of how our team delivered the privacy.
[00:11:28] Whitnee Hawthorne: That's amazing. Could you explain how machine learning platforms are transforming decision making processes in hotel operations, particularly in areas like revenue management?
[00:11:38] Julia Morrison: Revenue management is one of the most age driven disciplines in travel and hospitality. And I can talk about it for hours because this is where I started my career decades ago. So traditionally, revenue management models have been implemented by basically extracting data from operational systems, putting them on a machine, In flat files, then data scientists creating some models in whatever modeling language they prefer, like SAS, Python, and whatnot, and then get the results and load them back into operational systems.
Well, cloud data platforms and warehouses are, allow us to be more nimble. Data has gravity, so bringing models to the data allows us to do things faster, cheaper, better, and most importantly, more accurate, and allows us quicker innovate in the area. We recently implemented some of the revenue management forecasting models in our Snowflake environment using native apps, and we see great results with them.
[00:12:37] Dan MacDonald: As Julia has said, machine learning has been a staple of revenue management for quite some time. And what's really, what's really changed are the volumes of data and the velocity of execution that we've been able to achieve. Really orders of magnitude in both data and execution, given platforms like Snowflake that allow us to bring processing to the data.
We've moved from monthly to weekly to daily executions of our revenue management models. Recently, we released a suite of approximately 2 million models that execute daily to predict occupancy at a day level, over a six month window, every day within that window for every rate plan at each of our 9, 000 properties. It's just astonishing today that we have the compute power in the environment to process this amount of data and make these inferences in a mere hour's time.
[00:13:36] Whitnee Hawthorne: It is astonishing and I love to hear that the Snowflake product is working for you. How does Merion overcome specific challenges in the hospitality industry such as managing real time data from multiple properties or integrating data from acquired brands?
[00:13:49] Dan MacDonald: So, we try to stay ahead of these challenges by staying close to our business strategy and ensuring we have the necessary capabilities that enable it. We focus a lot on creating a platform of core services that are highly scalable and are the building blocks of the products that we deliver. This year, we leaned into the data clean room, for example, and have built out some self service capabilities that allow our users to quickly perform overlap analysis with potential partners and sharply reduced the duration versus the traditional intermediary party clean. This is a great example of emerging technology capabilities that we were monitoring closely and balanced the maturity with the business value.
[00:14:35] Whitnee Hawthorne: As Marriott continues to expand globally and enhance personalized guest experiences, are there any future data or AI opportunities that you'd like to highlight?
[00:14:43] Dan MacDonald: So no data discussion would be complete without an AI question and you saved the best for last. www. Obviously, AI is a tremendous opportunity to enhance our guest experiences, and we're incubating many use cases. And while AI has great power, it also comes with great responsibility. So while we always want to enhance our guest experiences, we also want to do it in a meaningful way, and always want to be aligned with the trust that our members afford us.
We've recently delivered some concierge type services to help our guests plan their stays and make the most of their experiences. One example is the Gen AI powered search capability on our Homes and Villas site that lets the guests search for vacation experiences using natural language. If you get a chance to go out and try it, it's actually pretty amazing and may lead you to a great vacation.
[00:15:34] Julia Morrison: Awesome. So another example is to truly understand our customer voice. AI can help us summarize customer feedback and their interactions with us, whether it's through chat, with their phone calls, emails, and that allows us to find the areas where we can improve. For example, we got quite a few calls in our customer engagement center, and AI can help us understand the patterns of when in customer journey customers are more likely to call us, and if they're calling with an issue, how we can prevent that issue in the first place.
So, for example, customers even might not know that they're experiencing an issue, but the data can show us that they do. For example, they might just call Customer Engagement Center to make a reservation. But, we can understand that that could be a situation where because of edge case, they, for example, cannot make that reservation in the digital channel.
So, we can understand then, what prevents them from doing it. Go to our digital partners and solve for that edge case. So in next time, that particular experience can be delivered through the channel that may be more convenient to the customer and in this case can improve. It's a win win situation because we're improving the way we're serving customers and customers is actually much happier to engage through digital experience.
So we're just seeing the tip of the iceberg in terms of what opportunities we have with data and AI. There's a lot of things coming in the area of prescriptive analytics and cognitive analytics that can reveal things that we're not thinking about today, but we're sure we'll think about them tomorrow.
[00:17:17] Whitnee Hawthorne: Julia and Dan, thank you both for joining me today. This was a fantastic conversation and I truly appreciate you sharing your insights. I'm excited to see how Marriott continues to innovate and lead the way in the industry. Until next time, everybody take care.
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