How to Use Market Data to Win More Direct Bookings with Mridul Bansal of PriceLabs

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Are you relying on the OTAs to fill your calendar, but are dreaming of more direct bookings? In this episode, we'll unlock the power of market data and show you how it can help you take back control. We'll dive into strategies that use market data to transition more bookings directly to your website. Ready to optimize your revenue? Let's get started. You are listening to the Direct Booking Success Podcast, bringing you all the information you need for your short term rental to stand out from the crowd. I'm your host, Jenn Boyles. As an owner and manager myself, I know how hard it can be to navigate the hospitality industry. I'm here to help so you too can have direct booking success. Hello and welcome to another episode of the Direct Booking Success Podcast. I'm Jenn Boyles, your host, and today I have Mridul Bansal with me. Now, Mridul is a product marketing manager at Pricelabs. He is a big believer in using market data to keep your short term rental competitive, regardless of how guests book with you. So welcome, Mridul, how are you?

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Hi Jenn, I'm great. Good to be here. How are you?

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Great, great. It was so wonderful to have Pricelabs as a sponsor at this year's Direct Booking Success Summit and I'm speaking to the listener here. If you missed it, I'm really sorry, but I'm glad you're tuning in today because we're going to talk a bit more about market data. So let's Mridul, let's kick things off. Can you tell us a bit about what Pricelabs is and what you do there?

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Definitely, Jenn. And yeah, we were really thrilled to be the sponsor as well. It was an amazing summit. So PriceLabs, Jenn, is a dynamic pricing and market data platform. We started in 2014, so it's been about ten years now. So we've been serving market data since then. And this market data is about short term rental, midterm rental. We can show rentals across the world. We collect this data and that is what we serve to our customers in multiple forms. My role as a product marketing manager is to make sure that our product team hears the voice of our customers. So I look after our customer base, which is the host and owners. So make sure that their voice is heard within the company for product development, training and support and more. And make sure that we build features which are relevant to those customers. And once those features are ready, make sure that our customers use them, make it easy for them to use them and make it easy for them to find value in those features. So yeah, that's primarily what.

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Great. So let's start with what market data is. What does this mean in the context of short term rentals? What is it?

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Yeah, Jenn, I can imagine. I mean, I think all of us have probably heard this term a million times now. Market data, especially short term rentals. So market data, essentially, Jen, at least in price lapse context, is every publicly available data of listings that is available across booking platforms. So at Pricelabs, what we do is we scan listings on Airbnb, Booking.com, comma, VRBO, on almost an everyday basis. So when we scan these listings, we get information about the property type, we get information about their bookings, their rates, change in their rates and more. So now we do this data collection almost every day. Now, once we have this data, we try to see patterns in it. So, as I said, we've been doing this for ten years. We have a lot of data. Now what we do is we map it with the previous data that is already available with us and when then we try to find patterns in it. So let's take an example. I see bookings for December 2024, right? So today we scanned and we saw how many bookings are there for a neighborhood for 2024, December. Then we will map it to December 2023. We'll map it by December 2022. And we'll essentially see what is the change and what is the pacing, as we call it in this data right now. As I just repeat myself, this is how we find patterns. This is how we see how this year's December is doing as compared to previous December's. And then by finding these patterns, we try to find seasonality. We try to find local events. So let's say if the demand is very high this December as compared to last five Decembers, for instance, we know that something is different, right? For hosts, it's great that the demand is more. It's great for us that something is different. But we got to find what this difference is, and we got to make sure that you don't charge what you usually do in December. So this is what the market data is. This is what we do with identifying and finding these patterns. And we do this individually in every neighborhood, as we call it. So it's just around any listing that you have. We do this for all of those listings across the world.

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Great. Okay, so I think I get it now. I think I sort of understand when we talk about that term market data, what it is. So let's just go through the key components. Then, just in simple terms, we've got pricing and we've got listings. Like new listings or listings, would it be listings that have closed or new listings? What are the other top components?

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Right? Definitely. That's a great question. So there's a lot of data that we pull and we show. It also depends on what as an owner you want to look at, right. Ideally this has again ADR, which is the average daily rate. So how much are the listings priced on this market right now? We do this and we give this data for individual listings. So let's say if you have a property in Chicago, you maybe want to just look at the 15 properties that are just around in your neighborhood, right? So we do this for individual listings. Plus we also give this price, this nightly rate based on market percentiles. So what that means is we tell the data of what, let's say the 75th percentile of the market is priced at. What that means is essentially what are the top 25% properties in the market? Most expensive properties in the market are charging.

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Okay.

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So this future price, we divide it in different percentiles and let you know what different sections of the market are charging.

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Okay.

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So then you get the price, you get the average night. We also then share occupancy rates. So essentially, what is the occupancy of that market? How far in advance are people booking? We share the average length of stays. As you know, Jenn, in the short term rental market, length of stay is very important. Right. Literally the second pillar of revenue management. You can't just be charging more. You also have to make more from each booking. So what is the optimized length of stay that people are ready to book? I'm pretty sure none of us want to get a Christmas booking for just the 25th, right?

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Exactly. Yes, you said it.

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Yeah, exactly. So now it's just finding the average length of stays in that market right now, it depends completely on the market side. If it's a beach market, it's a different length of stay. If it's a market which has skiing, for example, there's a different length of steam and then it changes by season as well. So then that is another metric. Then you have a booking window, which is how far in advance people book. Again, for vacation markets, people book way far in advance, but maybe for a location like skiing, people just book maybe last minute. So how far and what is the booking window for these markets? So these are just some of the main things that are available there, Jenn.

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Yeah, no, it's really interesting. I'm a marketing person. So when I start to hear the word data, I think, oh, I start to glaze over. But I think we have to realize that we need the data to then be able to market our properties effectively. So let's talk about collecting this data. So you are scanning the big online travel agents. That's where you're collecting the data from, correct?

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Yes.

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Okay. So if a host was going to go and do this themselves, well, it would obviously be very difficult. They wouldn't get the depth. But if somebody just wanted to go on Airbnb and look for this data, is there a way that they could collect it themselves?

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I highly doubt it. I mean, they may get some of it. Like, let's say you bring up an excel sheet, you find ten properties, you see their nightly rate, and then maybe you put it in Excel, try to find the average of it, but then there's just so much depth to it. Jen, as you said, like, there's different prices for weekends, there's different prices for weekdays, there's different prices for seasons of, there's different prices for off season, high season for local events. Let's say if Taylor Swift is coming to my city, the price is going to be completely different. So it's just, there's so many factors and it kind of becomes very difficult to do it manually. I'm sure people do this manually. I'm sure it may work for some of them, but it's just you only get to the surface level. Right. You don't realize how much in depth you can go with that. You don't realize what else there can be. So it's relatively very difficult for pricing, but if you go to length of stays, then it becomes almost impossible to understand the length of stays for your competitors for different seasons, different months, different booking times. It's just a lot.

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Yeah, I could go on Airbnb, VRBO, booking.com, comma, Expedia, all this and find out prices for those exact days. But if they're using dynamic pricing, then when you go to look at that same date in a week, it could be a completely different price. So I can see going and doing your research when you're starting out would be a good idea to see what people in your area are charging and get that Excel or Google Doc sheets open and start to figure it out. Is there a kind of data that you think that is often overlooked by hosts and property managers?

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Right. I think, Jenn, people in general overlook competitors sometimes. Right. So you may know the top two competitors, three competitors, five competitors that you have but there are a lot of other people that guests are comparing you with. Right. So people sometimes don't necessarily take in all of those competitors when they are doing the manual analysis. I have made that mistake myself now that it's just very difficult to find, to be honest, your exact competitors. Now, if you have a two bedroom, theoretically you are only competing with two bedrooms. But now there can be properties which are priced at your price and they are giving a three bedroom, say, Villa. Now your guest has the option to choose from your two bedroom to that three bedroom. So essentially that three bedroom villa is your competitor as well. So just understanding and finding those competitors sometimes is tricky.

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Yeah, yeah, I can see that. Okay. So in a hypothetical world here, we've understood what market data is, and the next step is that we started to collect it. Now the next step is analyzing what it actually means. How do we go about that? What are we analyzing? Is it just about the pricing or there are other factors there, right, Jenn?

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So it's actually a lot of factors apart from just pricing. Right. So now how you can analyze and how you can use this data, I think essentially, I think I can put them in two buckets. So one is, say, a market report. So what that means is now all of this data is there. Imagine that data is sitting in a very raw form somewhere in your whatever database. Now you can pull that data, create a customized report. So let's say you want to create a report for a neighborhood that you are looking at. Now, you can put that address, you can put that here. This is the neighborhood. This is the address about which I want to get this report. And now you will get all of these matrices, right. So now it can be if, let's say you are an investor, you're looking to make a new investment in that neighborhood. We'll tell you everything from how much money you can make, right? Every month from that data, you'll see what the average money people are making in that neighborhood. And given that, let's say you have a two bedroom in that address, how much money potentially you can make every month. So it's very easy, completely UI based. You can just find that information. You can see which are, say, the best performing properties and potentially your competitors in that market. You can see the cleaning fee of that market. You can see if they are on Airbnb, what is the service model that they are using? Obviously, given that you have the option to choose the service model, you can see which service model of Airbnb they are using. So essentially, it gives you almost everything that you need to know before making that investment. It helps you clear your expectations. It helps you know what's coming for you.

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Yeah, okay, I got it. So we want to be able to use this data to help us stand out in such a competitive market. Okay, let's look at a scenario here. We're listing on some of the OTAs, but we also have our website and we really want to drive more direct bookings. How can we use this market data that we've gathered, we've analyzed, how can we use it to help stand out?

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Definitely, Jenn. So that's where the second bucket comes in. Right. Let's talk about operations first. So if you're using a website, if you are also present on OTAs booking platforms, you possibly use a PM's or a property management system, right? Because a lot of PMSs offer to connect with their website. So essentially, I would assume you are updating your prices on your website through a property management system, right. So what you can do is you can dynamically update rates on your website and on those booking platforms based on this market date. Right. Now, of course, I'll explain what that means. So dynamic pricing, I think sometimes is very, again, similar to market data.

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You're one of those terms, isn't it? You throw around market data, dynamic pricing. It's like, yes, but what does it actually mean?

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So you have this market data, right? You have so much about the market already. Now, Pricelabs, once you connect your property or once you connect your listings to Pricelabs, Pricelabs fetches information about your bookings performance. So about your listings performance, we get the information. Now what we do is, now, let's say there are a couple of steps. We analyze the market data, which is we scan it through major booking platforms. We found patterns in it. Now, once you connected your listing to Pricelabs, we got the performance of your listing. So we know in the past, let's say for the last six months, what has been your occupancy rate. We know that for the next three months, what is your occupancy, how many days do you have booked for the next three months? So now this market data, again, I'm sorry to be using that.

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No, no, it's good.

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So now you have this market data, you have your properties performing. Both of these are clubs along with a third factor of your preferences, right? Do you really want more bookings? Do you really want more occupancy or do you really want a higher ADR so it's really about your preferences. Are you okay to stay unbooked but you only want, let's say, the top price of the market? Or are you okay to just undersell, even if it keeps your property? So you set up some preferences like this. Now, all of this is clubbed to generate a unique price for every night. Now you have the data, you have the patterns, you have your property performance, you have your personalizations. All of these combined would work every night for you to generate a custom price for your listing. And now, operations wise, I'm sure we as hosts don't have time to know. Okay, you've given me a price. Let me just go and update it on my booking platforms. Update it on my website. Now the operations part that I mentioned, now it goes to your pm's automatically every day, and then it goes to your booking platforms, to your website, anything that you're using, and it updates the prices there.

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Okay.

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Okay. So this is what automation comes in. This is where you get this direct price, which goes straight to your booking platforms and to your website. And now this is where the dynamic pricing factor comes in.

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Okay, I think I've got it. So for hosts, property managers who rely heavily on the otas like Airbnb but want to increase direct bookings, how can the market data, the dynamic pricing, all of this information for them, how can it help them transition more bookings to their own platforms? What's the strategy there to get more bookings on their website?

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So I would say the first part is, of course, to be dynamic even on your website and on booking platforms.

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Right?

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So make a price vary with demand that we just saw, you know, based on the market data, based on the market demand, the local events, the seasons, the weekdays booking window, so many factors make your price move based on those factors. Right. I, and both on your otas and on your website. Now, some things that you can do to, of course, increase bookings directly. So a few things are the most important. One is you can add markups on these channels. So these channels charge commissions and service fees. So you can add markups on these channels to be slightly expensive on these platforms. Okay? So mind you now, you're still moving dynamically. So let's say today you're priced 100, tomorrow you have priced 120. Day after tomorrow you're priced maybe 125. You can do that on channels based on demand, but just say add a markup of 10%. So now on Airbnb instead of 100, you are for 110. Instead of 120, you are for 132. So you are still moving with the demand, you are still making the most out of the market, you are still making the maximum revenue that you can, but you are slightly cheaper on your website or slightly expensive on booking platform so that people, when they are comparing, they come and then they find you slightly cheaper on your website. And again, it doesn't lose revenue for you because OTA charges commissions. Right. And that's the reason that we are coming to direct bookings. One of the reasons we are coming to direct bookings. So you can still be expensive, you can make money, and you can still be dynamic. So that's one of the things that you can do to increase the.

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Okay, so let me talk this through with you to make sure that I've got it. So we're using the market data to find out about the industry, our neighborhood, our competitors. We're analyzing it to see how it can affect our business. And then we're using the dynamic pricing that has got its data from the market to then move our prices up and down dynamically. That's where the word dynamic comes in, making sure that the otas, the pricing there is more expensive. So the best deal is always on our website. And then we have to tell everybody about it, don't we?

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Exactly. Of course. Of course, Jenn. Then you do your marketing, let everyone know, maybe have unique names and stuff like that, and then people will come and then they will hopefully find it cheaper on your website. And then now they probably don't know that you're moving dynamically. You can still make the most out of the market and the situation, but being cheaper on your website. So that's exactly it.

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Yes. And you've got the market data behind you about lengths of stay. So if you're sitting around and you're saying, okay, I really want five night stays, that's really what I'd like. But then you find out that your bookings are suffering because in your market, in your area or neighborhood, a two night maximum, that's what people are wanting. So I can see why it's not always the price that the bookings are coming in.

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Exactly. And talk a little bit more about that is actually, it doesn't have to be static as well, right? It doesn't have to be just based on your market once. Because again, we need to add the word dynamic here as well. Right? So you can, let's say for your neighborhood, for your market, the ideal is two days default, but that can vary. For example, for Christmas, as we spoke, I'm pretty sure we don't want a two day booking for Christmas either. Right? So now that can again vary based on demand. That can again vary based on seasons, based on local events. Again, for Taylor Swift, if there's a three day concert and everything I want along with a booking. So it can again, that length of stay, that trip length can again vary based on the demand, based on how the market is performing, how guests are behaving, and then you can change it. Another thing I really like about this gen is the booking window, which means how far in advance the booking is. So if someone is booking my calendar, let's say four months in advance, I really don't want to take a two day booking or a one day book, right. I don't want to block just a date in my calendar and potentially lose out on a seven day booking. That's just how I work. That's just how I think maybe someone has a different approach. And if someone is booking for, let's say, my property for just tomorrow, it's okay for them to just book a day or two day. Also, because I am empty, I don't have enough time to get more bookings. So now these length of stays varying based on the lead time is also something I find very amazing, to be honest.

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Yes. And I guess another way of driving the direct bookings is using that market data and saying, okay, people in this area at this time of year are booking three months out. Well, let's make sure that they can't book on our otas, that they have to come to our website to book. So I can see it's taking the data and analyzing it and figuring out the best way to use it for your business, for your property management company, for your short term rental, to drive the traffic to your site rather than getting them to book through the otas.

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Exactly. Exactly. And that's the eventual goal. Yes.

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Awesome. Awesome. Well, I've learned a lot today. Thank you so much for coming on again. Thank you for sponsoring the Direct Booking Success Summit this year. It was wonderful to see you there. Amazing presentation. And you've got a special offer for those listening right now, don't you?

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I do, Jenn. I do. Before that, thanks again for having us there. It was indeed a pleasure. The success was great. We are actually hosting a webinar which is specifically just for the listeners of this podcast. It's a free webinar where an expert from our team who is also a revenue management expert will be sharing strategies again, which we spoke about today. It will go in much detail and on more practical how to's right. So we've talked words, we have talked about the neighborhood and what else, but on that webinar in that session, we will be talking more about how exactly to do that. It's completely free for the listeners and we would love to have people over there.

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Great. Well, that's amazing. So it's going to be a special live masterclass free in November 2024 and I'll put the link to that in the show notes. Again, thank you Mridul so much for coming on today.

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Thank you. Thanks for having me. Jenn, it was indeed a pleasure. Thank you.

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A huge thank you to Mridul for joining me today. A huge thank you to Pricelabs for being such an amazing sponsor of this year's Direct Booking Success Summit. It was wonderful to have Pricelabs as part of this global event. If you've been enjoying the Direct Booking Success Podcast and found value in the conversations I'm bringing you, I'd love for you to take a moment to rate and review the show on your favorite podcast app. Your feedback helps me reach more property managers and owners just like you, empowering them to take back control of their bookings and grow their businesses. Plus, it means the world to me. So hit those stars, leave that review, and let's keep building this incredible community together. I thank you so much for your support. In the next episode, I'm bringing you a great guest who's going to be talking about collaboration over competition. Think about the idea of turning your competition into your greatest direct booking asset. Interesting, isn't it? We're going to discuss how sharing guests could actually lead to more direct bookings and build stronger relationships and create a thriving community around you. Until then, go out, take action for your own direct direct booking success. Hey, thanks for listening to the Direct Booking Success Podcast. For more information about this episode and others, head to the website directbookingsuccess.com/podcast. See you next time.