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Why hotel analytics is becoming critical (Altexsoft)

Updated: Jul 3, 2023

In this episode we speak with Alex Medovoi, CEO at AltexSoft about the importance of hotel analytics and the four key areas that it enables efficiencies, cost-cutting and revenue generation.

We look at the value of analytics, the approach dependent on accommodation or category type and the impact on revenue. In our discussion, learn

  • What is hotel analytics and the value it is providing hotels?

  • Why it is critical today

  • How independent and small hotel properties approach analytics compared to large hotel resorts and hotel groups

  • How hotel analytic solutions improve the efficiency of the revenue management function

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Altexsoft is a travel and hospitality technology consulting company working with travel agencies, travel management solutions, and hospitality businesses


Programme Notes


Ryan Haynes:

Hello and welcome back to Travel Market Life. I'm your host, Ryan Haynes. And today's episode, we are going to be looking at hotel analytics. Now at Travel Market Life, we've been looking very closely at our data and the episodes that are in demand, and it seems to be all about data. So of course, it was essential for us to go and speak to those that are working very closely with analytics and data to enable hospitality companies to grow. So, in this episode, we are going to be speaking to Alex Medavoy, the CEO of AltexSoft. We're going to look at the value of analytics, the approach dependent on accommodation or category type, and the impact on revenue.


Ryan Haynes:

Joining me now is Alex Medovoi from AltexSoft. Thanks so much for joining me today, Alex. Now, hotel analytics, it's a big thing. A lot of focus is going into that area, what is for hotel analytics and the value is providing hotels,


Alex Medovoi:

First of all, thank you, Ryan. It's a big honour and privilege for me to be at the podcast, and thanks for inviting me. And we are very pleased to share some of the things that we've been working on for years. So basically, jump in straight to the question. Data analytics is how we see it as an important discipline for the hospitality industry because it helps businesses in this sector to better understand the customers and make more informed and reasonable decisions. And by analysing data about their guests, hotels and other hospitality businesses can gain valuable insights into customer behaviour and preferences.


Alex Medovoi:

And this information can be used to improve the customer experience, optimize pricing and promotions, and increase revenues. Because obviously during the customer journey, travellers leave a lot of digital footprints at various points such as when you book either through OTA directly when you check in, when you complete your post-day surveys, et cetera. So, any action taken by the tourist or front office manager, or even housekeeper such as booking a room or marking a room clean or making payment, everything creates data.


Alex Medovoi:

And so, these footprints can provide valuable insights for everybody and first and foremost for hoteliers to better first understand their demography, and the demographics of their customers, and second, improve customers’ experience. And the third and most important thing actually to drive hopefully additional business. So, for example, data analytics can help a hotel to understand which amenities and services are most popular for the guests. This information can be used to improve the guest experience by making sure that the hotel has enough staff on hand to provide the services or by offering any additional amenities that guests will appreciate.


Alex Medovoi:

Additional data analytics can be used to identify trends in customer behaviour and preferences from very basic, such as the times of the year when a hotel is most likely to be fully booked and usually hoteliers, they know that, but they also can dig very deep into the details using the analytics and make these predictions much more sophisticated and not just sophisticated, but much more precise. So this information can be used further to set prices and promotions accordingly, helping hotels, obviously to maximize their revenue.


Ryan Haynes:

I was going to say there, there there's, there's a lot of places where you can get data. I mean, so many systems within the hotel tech stack from property management through to, as you say, the data that's generated through your channel manager for where the bookings are coming from through to the CRM and your email campaigns or from social media, there's a lot of places that you need to consolidate that data. And I guess that that needs, that, that framework is going to be different depending on the type of hotel property, whether you're an independent hotel or a large hotel chain. Is there quite a difference between how different size businesses manage data?


Ryan Haynes:

Because I guess that there are huge differences in in in in the volume that you're dealing with here as well.


Alex Medovoi:

Yeah, that, that's, that's correct. And I would probably add a few more cents to this question. So, when it comes to analytical tools for hotels, there are a large number of already-made solutions, and we have to realize that. So, though many systems have built-in analytics tools, their capabilities may be limited or restricted to solving very narrow tasks in a particular niche. And to your point, basically for the large hotel, the situation can often be the following.


Alex Medovoi:

They obviously use some ready-made existing solutions. However, because of the scale of the hotels and different data sources and also aligning all that with a number of goals and objectives, there's probably no unique out of the out of pocket, let's say tools that can solve all this. So usually big chains, combine something ready-made plus they do some custom modules on top when while we are speaking to smaller hotels, usually even smaller hotels nowadays use PMSs, right?


Alex Medovoi:

So basically, what is usually used as some kind of analytics module that is pre-built into the PMs, but obviously well we've been working at this market for the last 15 years. I would say that I have, I know zero PMSs with a brilliant analytics module that is going to be covering everything. So, we usually see the situation when even though the smaller hotels and Hoteliers, use a stick to some PMs, they usually either buy a combination of the ready-made solutions and they're kind of adding topping, I would say the PMs, or they build something custom tailored specifically for their needs.


Ryan Haynes:

I mean, yeah, oh absolutely. Because one of our podcasts that we did last year with say, hopper Hospitality did exactly that working with SIHOT, although SIHOT has a business insights platform, actually drew so much of that data from the property management system to create very specific visualizations of that data for the staff. So, as you say, Alex, there's so much data in a PMS, is the PMS actually able to deliver a sophisticated analytics tool that's needed and is intuitive for all parts, all, all staff within the workforce that actually needs to use it?


Ryan Haynes:

And I guess at the same time, is it able to surface the right data so you can make those commercial games? What do you see at AltexSoft as essential when it comes to the data that you can really commercialize and make accessible to people within the hotel so that they can see the trends, see the hotel performance and actually make some informed decisions?


Alex Medovoi:

First, it really depends on the examples of what kind of business problem are we going to solve. For example, if our hotel has a strong focus on customer loyalty and customer relationship management, it's kind of one set of data. If our hotel is focused, obviously more on driving new customers, it's another set of data. Again, business model, we know that all the hotels would like to maximize for their customers to use multiple amenities and activities, but some of the hotels are still not yet there, so they're not making too much money from that.


Alex Medovoi:

Some of them are, so basically depends like, like, like the, the answer to your question is going to be very dependent, it depends. But as for our experience, I would probably break all the data down into four, like kind of big buckets if you wish, and cases, and I would associate some use cases with the buckets of data. So first and foremost, I would probably start with customer segmentation and targeting, and the data associated with that type of segment, if you wish. Usually, you build some custom analytics module that could help the hotel to understand its customers base and segment them into different groups based on the factors and not very obvious factors, you know, so let's say not like customers that come from some geography, but mostly customers by demographics or booking history on some spending patterns.


Alex Medovoi:

So something really more sophisticated than just, you know, segmenting like, like taking an Excel and saying, Hey, I'm going to, I'm going to check all the customers that came to me from France or from China, whatever. So, and definitely, when it comes to more sophisticated customer segmentation, this then could be used to tailor marketing sales efforts for the different segments and increase the revenue obviously. Now, the second big bucket, I would say sales and revenue optimization itself. And usually, the analytics module could help the hotel to understand which factors are driving bookings and revenues, and then identify the opportunities to optimize price in inventory management and, and other factors to maximize the revenues.


Alex Medovoi:

The third thing is actually the third bucket I would say about marketing, and I would call it campaign analysis. So, the module could be used to analyse the effectiveness of marketing campaigns, identify the channels that drive most of the bookings on volume or the most margin marginal bookings, and then help the hotel to allocate the marketing budget more effectively or adjust the campaigns or just at all refocus the efforts. You know, we all know that direct bookings bring us typically more revenues that that makes sense, but what kind of campaign is going to be the most effective, the most efficient for us in driving the direct booking component?


Alex Medovoi:

Right now, the fourth bucket and probably the last one, but no, not the least obvious, is operational efficiency. So, the model module can be used, and custom analytics basically could be used to analyse data from different systems. So, you do, you, you, you take not only from the PMs but also from the system that helps you to maintain from your, to maintain the property obviously from everything that you are buying for the property and identify inefficiencies, opportunities for process improvement. Let me give you an example for one of our clients, based on the data that they started collecting and based on the data that they, so basically their internal data, their average booking was very short.


Alex Medovoi:

That means that they had to change the bettings very often and they had a few properties around, and they used to use the outsourcing firm that was doing this job for them. This actually led them to build a huge custom facility that they started using for laundry. And it brought them, I believe over 1.2 million in EBITDA in the first year and over 3 million in the EBITDA for the second year. And the, I was kind of just out of it, it just blew rewind, blue, blue, blue rewind basically.


Alex Medovoi:

And this is a very interesting experience from our perspective, just, you know, practical use case.


Ryan Haynes:

It's absolutely fascinating you say, I mean firstly is defining that objective. Okay, yeah, of course, we want every single aspect of the business to be efficient and to be money generating or to be bank balancing or, or just to sort of be at, to optima optimize efficiencies. But you can't do all of those things at once. You've got to hit, you've got to, you've got to tackle one battle at a time. And as you say, sort of, you know, are you looking at maximizing the income from your existing customers? Are you looking at growing your new customer base or are you looking at optimizing existing expenses and reducing those costs?


Ryan Haynes:

And you know, we, I spoke to Turtle Bay a couple of years ago and to Best Western just recently about how they've used their own customer data to really target high-value customers and, and keep bringing in those return customers and, and help them identify where their new customers could be coming from. And, and then that's a value of, of really getting to understand your data, centralizing that data and making sure that data is working effectively for you. You've touched specifically on one of those four buckets around revenue. I mean, it's a big topic at the moment around how can we maximize revenue. How can we drive greater efficiencies within revenue? So, tell me, Alex, how do hotel analytics solutions improve the efficiency of the revenue management function within the hotel?


Alex Medovoi:

Again, we all know one of the key benefits of revenue management, it's allowed businesses to make more precise predictions about demands. And based on that more precise prediction, you can actually play with the pricing. By playing with that pricing, you actually maximize revenue from the same basic number of rooms. It's a well-known case on the market with a myriad's approaches to revenue management. And this was an additional module they called internally dynamic pricing automation that actually allowed them to predict demand and not only demand but also patterns of customer's behaviour using that they just increased their revenue per room for around, if I don't mistake, around 5% in one year.


Ryan Haynes:

Alex, you've actually been working on your own analytics solution at AltexSoft and it's quite interesting the sort of results and the impact that it's had. Can you, can you tell us about your, your, your developments that you've made?


Alex Medovoi:

Yeah, there are quite a few, but if narrowing it down to one, I would probably focus on another case for Rakuten and travel created by the Japanese giant electronic company, Rakuten, it's like Japanese Amazon if you wish. So, they engaged us to create a revenue optimization algorithm for a hotel. So, they have a bunch of systems, most of them have been built internally by their own team, but they actually missed that very component. And the client approached us with a request to develop a solution that could suggest early booking prices for accommodations.


Alex Medovoi:

And what was even more interesting, they had an internal team working in parallel on the same task. So, we worked, and they worked and in order to address that issue, we implemented the strategy that evolved eliminating of all the reservations made within a certain timeframe and then built a lot of things internally and actually created a custom algorithm that helped to analyse all that. Basically, what we get, as a result, this allowed us, allowed us to provide more accurate recommendations for early booking prices.


Alex Medovoi:

And what was even, even more interesting, even though, our algorithm was obviously more sophisticated and took longer time than the one that was built by the internal team, there was a clear value, we enabled revenue managers to track how variations and pricing actually affect occupancy and adjust the starting prices to maximize the revenues. And in order to help revenue managers to optimize their pricing strategies and maximize revenues, we implemented a system that allowed them to track the impact of price and fluctuations on occupancy rates.


Alex Medovoi:

So basically, basically narrowing this down, what happened, the price and fluctuations, they, there was a clear, a clear result in the occupancy rates and with that too, revenue managers were able to see how changes in pricing are going to differentiate and affect the number of rooms that are booked and then use that information to adjust their starting prices accordingly. So, we treat this and we, we think it was a pretty successful project for the customers, keeping in mind that they're using that very active in their business.


Alex Medovoi:

So, you know, and at their scale, obviously because they manage over 20,000 properties that brought them, as far as we are aware, hundreds of millions. So obviously worthy


Ryan Haynes:

Alex, you know we've explored quite a bit already in this, in this short conversation around hotel analytics, how it can be used and the different methods of, of deployment as well as the revenue, and revenue management opportunities from that data. So, it's been really interesting to learn more about that from you today. So, thank you ever so much for joining us.


Alex Medovoi:

Thank you very much for inviting me, Ryan, and It’s our big privilege to be on the podcast and share some of the insights.


Ryan Haynes:

Wonderful. Thank you so much, Alex, for joining us today. That was Alex Medovoi from AltexSoft, the CEO of the travel and hospitality technology consulting company, working with travel agents, travel management solutions and hospitality businesses. Check out more of our podcasts on TravelMarket.Life and you'll see a whole host of interviews that we've had related to data and analytics that will really complement the conversation that I've had with Alex here today. Thanks for listening. Speak to you soon.

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