Continuing with the theme of travel, the topic for this week is how the airline industry is going all in on the use of artificial intelligence, machine learning, and predictive analytics!
Today we cover the many areas of the industry where these new technologies are being employed as well as focusing on two specific use cases.
We’ve found that the airlines are fully investing in these technologies, and the results they are getting are significantly lowering their cost of operating as well as offering a better customer experience for all flyers!
To keep up with the podcast be sure to visit our website at datacouture.org, follow us on twitter @datacouturepod, and on instagram @datacouturepodcast. And, if you’d like to help support future episodes, then consider becoming a patron at patreon.com/datacouture!
Music for the show: Foolish Game / God Don’t Work On Commission by spinmeister (c) copyright 2014 Licensed under a Creative Commons Attribution (3.0) license. http://dig.ccmixter.org/files/spinmeister/46822 Ft: Snowflake
Welcome to data couture the podcast about data culture at work at home and on the go. I’m your host, Jordan Bohall. To stay up to date with everything data controller, be sure to like and subscribe down below. Furthermore, be sure to follow us around the internet at data to her pod on twitter at data couture podcast on Instagram and at data couture pod on Facebook. Of course, if you’d like to help keep the show going then consider becoming a patron at patreon. com forward slash data couture.
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welcome to data couture. I’m your host Jordan. And on today’s episode, we’re going to be continuing with the theme of automobile. Specifically, because I’ve been traveling so much, we’re going to be talking about various aspects of artificial intelligence and data used in the airline industry. That’s right. More travel talk. I’m going to be talking about travel just because this week I am at the driven ETFs conference down in Austin, Texas. I guess that’s what ETFs stands for. It’s sponsored and hosted by BP three global, which is a fabulous consulting company for all of your data and automation needs. Usually they help out the top fortune 100 but I’m sure they can make an exception for you. Now, we’re going to be talking about lots of areas that the airlines are using data, artificial intelligence, predictive analytics in their operation. Specifically, we’ll be talking about dynamic pricing, pricing optimization, flight delay prediction,
Flight route optimization techniques, avoiding various types of travel disruption, crew scheduling and even fraud detection. So the airlines are really going in heavy on the AI On the data front when it comes to running their business. So stay tuned.
Now today’s episode is going to only be split into two sections, this first section and a second section. And that’s because there is so much to get to as it comes to how the airline industries are using artificial intelligence and loads and loads of data in order to make all aspects of their business more profitable or better for the consumer. So let’s just dig right into it. The first area for playing AI in the travel industry is dynamic.
pricing. And so what this is, is an attempt to maximize maximize revenue by opting their base published fares. That’s what they agreed to as being the fair that takes into consideration various journey characteristics, say, if you have to go up and down over cliffs or over oceans or whatever,
as well as various types of broad segmentation as well as, you know, various facts about distance. So it takes that bass published fair, and then adjust that fair after evaluating various facts and details about the traveler as well as various current market conditions.
And so, in these sorts of things, it mimics very much ecommerce sites and how they can do dynamic pricing on items based on market fluctuations in real time and the airline companies are just now getting into this area, but it’s something that they will certainly be rolling out if not already, then certainly
down the line. In any case, on Wednesday’s episode, I’m going to be talking quite a bit more about how this dynamic pricing piece works. But the point is, airlines are using dynamic pricing to make the most profit at the optimal times for the buyers. Now a similar type of idea that’s being implemented is something known as pricing optimization. And so similar to dynamic pricing, these sorts of algorithms for pricing optimization, look for ways to optimize their sales revenue in the longer term to make sure that all flights are optimally booked. So for example, say airline only has, I don’t know three seats available ones and business class wants in first class and ones and economy class of course, the academy ticket will go cheaper, but in order for them to make sure that their flights booked and they have a full flight, they’re going to optimize that price for both business and first class in such a way that until those seats
filled, perhaps the price will come down and come down until they can convince potential client or customer to buy that ticket for their next flight.
Now, the next thing, and it’s something that I’m extraordinarily excited for once this particular bit of tech becomes more mainstream and as a bit more accurate, and that is flight delay prediction. Now, I don’t know how many of you have been an airport or maybe you’re at a connecting airport for part of your multistage journey, but you get there. And what happens, oh, your flights delayed. And usually, you know, it’s not so bad. If it’s an hour, two hours, I mean, even three hours, you can watch a couple episodes or something, or you could read a book or whatever it is that you do, maybe write some code. However, with the rise of AI as it comes to predicting flight delays, we might be notified in advance and perhaps up to 72 hours, whether or not our flights going to get delayed. And what does that mean?
That means you’re not going to have to spend nearly as much time in the airport waiting around for your flight to maybe come back online, maybe get booked again know, instead, you’ll know well ahead of time whether or not your flight will be on time. And for me, that will be amazing. That’ll be massive for my enjoyment of flying. Now another cool area the airlines are using AI is through Oh, and I should mention that the flight delay prediction is the piece we’re going to be talking about on Friday’s episode. And any case, for the next bit of AI they’re using flight route optimization. And so just like is being employed when it comes to shipping routes or drivers routes for people delivering cargo, even UPS and FedEx and all the various delivery people they use Route Optimization so that they get the most number of packages delivered to the most places and the least amount of time. Same idea
For the airlines by optimizing the route that certain flights take, for that matter, O flights take, the flights will be optimized so that they get the passenger there in the least amount of time, which of course saves the airline, lots of fuel, lots of payment of their employees, all that kind of thing. Now, the next piece goes right along with it, optimizing cruise scheduling. And so other than
sending packages or even the cost of fuel, the cost for flying their personal around the US and around the world is the second largest item for the total operating cost of all airline carriers. And so by optimizing the crew scheduling, so that one there’s not a breakdown in service for the passengers.
However, there are just the maximally efficient number of crew members on board. That will save I don’t know probably Hundreds of millions of dollars right now in the US alone, US carriers are spending about $1.3 billion a year just on flying their personnel around. So imagine if they knocked off, you know, 300 $400 billion, what that would mean for their bottom line. And now finally, they are getting into fraud detection. And so you might not think that flying on an airline would really constitute the need for fraud detection. However, one way that fraudsters spend people’s stolen credit card numbers is through buying flights. And so if the the airline can avoid that by detecting whether or not these are fraudulent purchases, then the airline will save money because they’ll actually get to book a ticket without being refunded the customer will feel safe and knowing that the airlines are looking out for them which leads to a better customer experience.
Speaking of customer experience, of course, they are
lands are going to be using various machine learning techniques to supplant and supplement all of their efforts. And so of course, they’re going to be using recommendation engines for tailored offers. So they’re going to be using various next best product for customers based on the behavior tracking that they find on their websites, the metadata that they can get out of it, as well as various purchase histories and purchase data that they get from other sources. And of course, with this sort of recommendation engine, and giving offers that might be below book value, they’ll be able to retain their customer and thereby create a longer customer lifetime value. Now pair that with the sentiment analysis they’re doing on social media sentiment analysis is just that analysis where you look at how people are talking about you online social media, through customer feedback, that kind of thing. And then you determine whether or not and given that it’s still in its infancy, whether or not the products and services you’re offering as an airliner anywhere else, for that matter are giving good experiences for your customers.
So the customers reactions are very valuable for improving overall customer experience. And given that the airlines are racing to the bottom, when it comes to the sort of services they offer on flights, I heard that they’re considering not offering alcohol on flights, which, if you’re 21 and older, you know, it’s basic necessity. I don’t know if it’s like, right that you should have for flying But nevertheless, they’re considering removing that and removing the free food as many of you have probably experienced already. All these little perks that you get for flying are quickly going away. And so they’re being being very careful with how they remove each one of these pieces by analyzing the sentiment of their customers and seeing what’s a hot button topic. What’s not.
And then of course, the final bit of customer experience either employing is through you can
Probably guests chatbots, customer service automation, that kind of thing. And so instead of reaching out to a travel agent or calling the airlines directly, I’m not sure how many people still do that. But nevertheless, if you are the sort of person that likes to have some sort of interaction with somebody from the company with what you’re doing business, well chatbots and Customer Service Automation becomes more and more ubiquitous, chances are, you’re not going to actually be chatting with an agent anytime soon with the airlines. And so of course, that makes processes much more fluent and it makes the experience more consistent and which makes for a better experience in the long run, which all leads to a better customer experience for the airlines.
Now, I’ve just covered a ton of different ways that the airlines are employing are about to employ artificial intelligence, machine learning, and various bits of data to improve their overall business model. So and the second piece of
This episode, we’re going to be doing a bit more of a deep dive on a couple of them before closing out. So I’ll see you soon.
All right, welcome to the second segment of data couture. Now we’re going to be focusing on two of the use cases, the use the case studies, I suppose, from the previous segment. And the first one is going to be flight route optimization. And so not only are the airlines using AI to figure out what’s the best route to get from some place to some other place, they’re also using AI to answer a very important key question. Namely, where are we going to fly? You see all the time that airlines are offering all sorts of new locations that you can get to for some unbelievably low Price.
And so how do they do that? Well, they analyze lots of data, lots of industry data, let’s see where their competitors are going. See where ultimately their own passengers are ending up. And then they analyze the data to make the decision, hey, we’re going to open up route from, say, Chicago to LA, which I’m sure that exists for almost every carrier, but let’s just say Chicago to Anchorage and say there are a bunch of business people who all of a sudden want to do a tech boom in Anchorage, Alaska. Well, when the airlines see that all of these people are eventually ending up in Anchorage. Guess what’s going to happen, you’re going to start to see direct flights from New York, Chicago, LA, San Francisco, Seattle, that kind of thing up to Anchorage.
Now, the next bit of room optimization is about something really necessary for airplanes, namely, fuel jet fuel. And one of the ways that they’re optimizing their routes is to optimize Their fuel efficiency. And of course, there are the ecological concerns. But I’m guessing that that’s not the driving force behind the industry using advanced tech to optimize their their fuel consumption instead, I’m guessing it’s because they want to get from point A to point B from one location fly to a different location using the least fuel possible because fuel is the number one cost to the organization.
And so what’s happening? Well, all the airlines are starting to deploy AI systems built using various machine learning algorithms to then collect and analyze various bits of flight data regarding each route. The distance traveled, various altitude used, the aircraft type itself, the way of the overall plane, the weather, the list goes on. And from those findings, they are then optimizing and estimating the least amount of fuel needed for each flight which makes the plane lighter which makes it go further.
Unless fuel, which of course is very interesting. And now the second way that I want to talk about for how our airlines are using AI to improve their business models is how they are avoiding travel disruption. Now this is very similar to being able to determine whether or not a flights going to get delayed. But there are lots of other ways that the airlines are using AI to plan for and then respond to travel disruptions. And so whenever say bad weather or other major events, whether political or otherwise, cause delays are forced delays and cancellations of flights depending on whether they’re arriving or departing a particular region. It creates a long downstream of fact that reaches far beyond that particular airport, that particular flight.
Why because an aircraft and its crew are just doing that one flight and then calling it a day. No, they’re typically scheduled to serve multiple destinations, which means that an individual delay a single airport or even a cancellation for that matter, can cause more delays and cancellations at others. And beyond that, turns out the federal rules governing tarmac times as well as the airline’s own commitment to keep us from waiting too long on planes can lead carriers to make preemptive cancellations. Now machine learning can help alleviate these particular issues.
So it can help to analyze real time data, as well as all the archive data that it uses to learn and train on for days or months in advance or predicting days or months in advance for which fruits will be able to avoid weather delays and what our roots going to be terrified or terrorized. I guess I shouldn’t say terrorized when I’m talking about airlines, but nevertheless terrorized by bad weather, it will become very clear and that kind of information can also All the airlines to plan in advance and very careful ways to avoid any sort of disruptions or cancellations. And in my mind, I’m all about it, please airlines please implement these kinds of things so that I can have just a normal travel it it’s already hard enough to be traveling for as long as we have to to get from some points to some other point.
So if you guys could do this for me personally, I’d be really appreciate it.
Oh, so you thought you’re going to get away with only two sections? Nope. I wanted to remind everyone that I will be at the driven conference in Austin, Texas from August six to the eighth where I will be speaking on a panel about
about digital literacy, and the data workforce if you’re interested in attending if you’re around the area or if you just happen to be coming through for whatever other reason, then hit me up on all of our socials and I will get you a discounted ticket, which would be awesome. And then you get to see me live in person. Talk about one of the very things I am extraordinarily passionate about. So until then, I will see you later.
That’s it for the show. Thank you for listening. And if you liked what you’ve heard, think consider leaving a comment or like down below. Stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod consider becoming a firstname.lastname@example.org forward slash data couture
music for the podcast. It’s called foolish game. God don’t work on commissioned by the artist spin Meister used under the Creative Commons Attribution 3.0
writing, editing and production of the podcast is by your host Jordan Bohall.