Innovation Roadshow - FLYR Labs
Transcript
Dominic Matthews:So thank you very much, Marco. Thanks very much, CAPA, for inviting us again to this wonderful event. A little bit about FLYR for those of you who don't know us. We're a 500+ data science and software company with major offices in the US and Europe. It's great to be in Budapest. Actually, the last time I was here was probably around about 20 years ago, and I remember 2 things from that trip. Firstly, it's the most amazing, beautiful city, and that remains the case today. And secondly, I remember how I booked my trip, which was actually I called a travel agency, I paid for a ticket, and I flew here. And you might say, hey, Dom, what's— of course things have changed and we're— it's 20 years in the future now. But the thing that was amazing about that, it was really simple. As a customer, I had 2 decisions to make because there wasn't really much choice, was when do I want to fly and can I afford it? And when I think about the trip this time round, it was a completely different experience. You have metasearches, you have multiple different flight options, you have lots of competition, and then when you finally get to actually purchasing something, you're bombarded with lots of different offers and a vast variety of different products and services. And so today's traveling and travelers are much more dynamic, and the old-school methods really are not up to scratch. And I believe that customers are really bombarded with too much choice, and it can be quite overwhelming. And if I think of myself, I think I'm really in 2 categories. Either I know exactly what I want, and I want it quick, and I want it easy, and at a price that I can afford. Or I've got a vague idea of what I want and I want a recommendation. So for example, if I go to a cocktail bar, they'll say, what do you want? I'll say, I'd like something with gin. Can you make me a recommendation? And I trust that that bartender probably has experience, either knows me or knows other people like me. He'll make a recommendation that's gonna taste good. I don't wanna look through the cocktail menu and then the gin menu. It gets very complicated. So we need to improve the relevance of the offers. Recently I took a trip and I was shown 5 different fare families. And one of them, there was a recommendation. I thought, this is great, they're recommending something to me. They were recommending me a fare with a checked-in bag. Now I'm a frequent traveler, traveling for 2 days midweek on my own. I have no track record of ever buying a checked-in bag. And I proposed that. Was that really because that's what I wanted? No. Or because that fare was $30 more than, than the other fares. Now, as we all know, consumers, travelers, the next generation, they're engaging completely differently with, with the world. These brands, you all know them. BeReal, I only discovered 2 weeks ago when I wanted to understand what my kids were talking about. Um, there's one thing in common that all these brands have, is they were born on data. They're 100%, 200% data-driven, amazing data platforms behind them, and they've invested extremely heavily in artificial intelligence and machine learning. They use the most amazing technology to serve up content that is extremely relevant, extremely engaging, extremely addictive, which is quite scary when you've got, when you've got kids. And they drive adoption like you've never seen before. So let's talk a little bit about— let's step back and talk a little bit about artificial intelligence and the opportunity this can present. This is a McKinsey study from a couple of years ago. It's quite amazing that they believe AI can present— can represent half a trillion dollar opportunity in the travel industry, one of the largest opportunities amongst all, all industries. And 90% of that is is in marketing and sales-related use cases. And interestingly, within that, you have reducing customer churn, improving forecasting, improving pricing, improving or automating customer service. But a large part of that is simply working out which product, which service, which offer should I serve up to my customer next. There's a huge opportunity in this domain. So there's a lot of talk about Thinking like a retailer. And many of you will associate that with IATA's tagline for NDC, Offer Order Management. NDC, I believe, was actually— came about more than 10 years ago, I think. And still we're waiting to see the full mainstream adoption as some of the panelists have mentioned earlier. But thinking like a retailer is not only about having the technology standards to be able to distribute that content, it's also actually knowing what you actually want to sell to whom, when, how, et cetera. And we're still using these old-school segmentation-based segmentation techniques, business versus leisure versus advanced purchase, et cetera, when the world has changed and the amount of data at our fingertips is completely different than it was 20, 30, 40 years ago. There was a mention of some of the, I think the lady from FINRA was mentioning some of the systems still in use today born in the '60s. We believe that, we strongly believe that artificial intelligence is really the key to unlocking this value. And those brands that were mentioned, that I mentioned earlier, I think Meta has a strategy of re-engineering their entire platform every 5 years. That's how fast the technology changes is happening in those schemes. So we really need to move to this anticipation, predictive personalization, as some of these brands are doing extremely So in order to move forward, how do we do this? So we believe at FLYR, it's technology, of course, but not only technology. Technology, revisiting the commercial structure, breaking down the silos, and in the way that we engage and the way that we collaborate. So of course, as a technology company, I'm going to talk about technology, but really Our technology was born in the last 5 years, you know, in line with those, those other brands. We're really trying to help airlines to break away from, from that 30, 40, 50 years of legacy. Data underpins everything we do. We believe that's— that should underpin everything that you do. And having unified platform to manage multiple use cases. Some of you may know FLYR as the company that does AI-based revenue management. Actually, we're extending that. That's right. Into a much broader set of solutions to be the commercial intelligence platform for airlines. We also need to continue to invest in the customer experience. That's not just UX/UI, but also enabling airlines to not only unbundle content, but to serve up more relevant content to customers to drive adoption. And also to consistently learn, to have the ability to test and learn, et cetera, which is exactly what those other brands are doing. All the time. It's part of their DNA. And then with a focus on the total portfolio, as airlines you've got multiple different revenue streams. It's become more complex and there are clear synergies between ticket revenue, ancillary revenue, even cargo to some extent. So aligning these commercial decisions and breaking down the silos within the organization, and that can also be enabled by having a data-driven approach and a common data platform. As you may have seen towards the end of last year, we partnered with Avianca who were going through a digital transformation. They wanted to improve customer experience, optimize revenues, and also get our help as they transition towards offer and order management. So we're very proud to be working with them as a partner. And so if you're keen to maximize commercial outcome, enhance your team's effectiveness, acquire new customers, generate new revenue streams, and optimize customer experiences, all with a commercial model which is a commercial partnership model which is unique in the industry, well, my recommendation to you is please have a talk to me or the rest of the team from FLYR during lunch, dinner, this evening at the bar. I'll buy you a gin and tonic. Thanks very much.
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