Ian McHenry is co-founder and board member for Beyond Pricing. He is a former investment banker and a management consultant in the airline and hotel industry. He founded Beyond Pricing, which helps vacation rentals and Airbnbs maximize their revenue through innovative software products and which has raised over $45m in venture capital from top-tier investors including Bessemer.
In this episode, Ian shares his expertise on pricing vacation rentals and how to optimize revenue earned from them.
Why you have to check out today’s podcast:
- Discover about marketing strategies that drive pricing for optimized revenue
- Learn about strategies and techniques to pull in data as the basis to optimize pricing for your vacation rentals
- Learn how Beyond Pricing software product gather in data to come up with favorable pricing
“Expose a bit of that black box. As you said, there might be just a couple of factors. There’s a lot of things that go into the factors, but if you can show like the prices up because of the seasonality versus an event, that creates a lot of trust and if you can show some of the underlying data trends that support that kind of recommendation and decision, it helps out a lot.”
– Ian Mc Henry
Get Accelerate Your Subscription Business: Your Blueprint to Packaging & Pricing for Growth Course at https://www.championsofvalue.com
01:13 – What is Beyond Pricing Company
02:27 – What paved the way for him to Pricing
03:55 – How to optimize pricing for only a single unit in Airbnb
05:00 – How to look at external demand data to come up with vacation rental pricing
06:57 – What other information do they have to pull, especially if there’s a one-time event coming up
11:44 – How not to underprice or overprice your vacation rentals
16:05 – How does Ian price their own product
21:53 – On trusting the data versus using the data in a black box
20:23 – His pricing advice that impacts one’s business: “Play with data and segment a lot.”
“I knew it wasn’t true when property managers told us we can’t make income from vacation rentals. I had all the data that tell otherwise. At any rate, we ended up making a lot of money off of it because it was really easy to capture that demand by just dynamically pricing it properly.” – Ian McHenry
“If you’re really trying to figure out to do, play with data and segment a lot like trying to understand demand and willingness to pay across all different kinds of segments you find interesting. I’ve found that you find interesting stuff just playing with the data.” – Ian McHenry
“If you’re building a product like ours where you do have buyers of that data that they need to trust the algorithm and not have it be a black box, one last thing is like expose as much as you can without necessarily giving away the secret sauce because a lot of the problem is getting buy-in for these predictions that you’ve made. – Ian McHenry
“Expose a bit of that black box. Like you said, there might be just a couple of factors. There’s a lot of things that go into the factors, but if you can show like the prices up because of the seasonality versus an event, that creates a lot of trusts and if you can show some of the underlying data trends that support that kind of recommendation and decision, it helps out a lot.” – Ian McHenry
People / Resources Mentioned:
- Allegiant Air
- Oliver Wyman
- Southwest Airlines
- Smith Travel Research
- Andrew Watterson
- Scot Hornick
Connect with Ian McHenry:
Connect with Mark Stiving:
Full Interview Transcript
(Note: This transcript was created using Temi, an AI transcription service. Please forgive any transcription or grammatical errors. We probably sounded better in real life.)
Ian McHenry: Expose a bit of that black box. Like you said, there might be just a couple of factors. There’s a lot of things that go into the factors, but if you can show like the prices up because of the seasonality versus an event, that creates a lot of trust and if you can show some of the underlying data trends that support that kind of recommendation and decision, it helps out a lot.
Mark Stiving: Welcome to Impact Pricing, the podcast where we discuss pricing, value, and the too-often uncertain relationship between them. I’m Mark Stiving and today our guest is Ian McHenry. Here are three things you want to know about Ian before we start. First, he’s a board member of the BWG strategy, which I think of as an executive mastermind organization. He’s the co-founder and CEO of Beyond Pricing. That’s what we’re going to talk about today and he surfs in Santa Cruz, California. He’s insane. Welcome, Ian.
Ian McHenry: Thank you so much for having me.
Mark Stiving: Oh, it’s going to be fun. Hey, before I ask the first question that I always ask, I’d ask a different one. What does Beyond Pricing do? I think I know, but I want to hear you say it.
Ian McHenry: Yeah, sure thing. Beyond pricing is the world’s first revenue management and dynamic pricing software for the vacation rental industry. So, we are similar to this offer that the airline or hotel might use if you ever heard of Pros or Ideas or Duetto and hotel space, and we work with vacation rental property managers where they connect their system to us. We pull in lots of data, come up with recommended prices for every single night for every single property and push them out to everywhere they get bookings for those properties via Airbnb, HomeAway, BRBO, booking.com or their own website.
Mark Stiving: That’s perfect. That’s exactly what I thought. So, it’ll be a fun conversation. By the way, I got to tell you, you stole my idea. I had this idea a long time ago. Well, you know, maybe after you did, but for all my entrepreneur friends out there let me emphasize something, ideas are easy, execution, not so much.
Ian McHenry: That’s it. It always takes longer and it’s harder.
Mark Stiving: Oh my gosh. So, let’s jump back to the question I always ask first. How did you get into the pricing in the first place?
Ian McHenry: So, out of undergrad I went into investment banking in the airline space. I had, you know, traveled a lot as a kid and really loved it, really loved airplanes. And so, when I left Princeton, you know, I wanted to do, you know, it’s kind of a typical path for folks come, come there for better or worse. But I really want to do something in the airlines. And so did that, help raise money for JetBlue, Allegiant Air, a bunch of regional carriers. But, you know, I’d always wanted to do something more operational. And so I ended up in a management consulting company called Oliver Wyman, which had the world’s largest aviation practice. And there I had the chance to get into pricing. I worked for a couple of great guys. One guy, Andrew Watterson, who went on to be chief revenue officer over at Southwest Airlines, and another guy, Scot Hornick, who went on to be the global head of pricing for Hertz. And so I learn from the best and we would go into major airlines and help them improve their pricing. And so that, that was just incredible entrance into that, which kind of led to me starting to be on pricing.
Mark Stiving: That’s actually really cool. And so you think about an airline, let’s just start with airlines for a second. They’ve got X number of planes, they know how many flights and they can see how fast their own planes are filling up.
Ian McHenry: Exactly.
Mark Stiving: I’ll adjust pricing based on that. Let’s say that I’m a vacation rental owner, I’m on Airbnb and it’s just me, right? It’s either full or it’s not. What are you looking at for them?
Ian McHenry: Hey. Yeah, exactly. That was the big problem, right? When we first came, I thought, hey, look, hotels do more or less the same thing, right? They look and say, hey what percentage of my nights are booked X number of days out if it’s booked faster than expected increased price lower than expected lower price. Right. Really, basic kind of pacing to drive pricing if you have, you know, 200 seats on a plane or 200 rooms in a hotel and that works great. But to your question, what if you only have one? And so that’s the hard part. You can no longer look at how quickly you know your 200 or so are filling up cause you need to optimize for a single unit on a given night. And for that we had to say, hey let’s look at external data to figure out, you know, what the increase or decrease in demand is. And that was kind of the big innovation would be on pricing was really starting to use external demand data to figure that out.
Mark Stiving: Okay. So, the first piece of external demand data that I think you should be looking at, what’s the price that Hilton is charging?
Ian McHenry: Yeah. When you get into it, you actually realize hotels aren’t as good at pricing as you would expect. You can do that, right? You can go and see like, okay, well all these hotels, if we assume hotels are great at pricing, let’s just copy the hotels. The problem with that is a couple of things like one vacation rentals are often either in areas with no hotels. If you go to the outer banks, there’s very, in North Carolina, there are very few hotels there to just do kind of compare pricing offer, but also they’re often in different locations with different demand trends than maybe where your vacation rental is. For instance, in San Francisco, you’ll have events like, outside lands, which is over in the golden gate park is actually far away from the financial district where most of the hotels are.
And so you actually won’t see a major significant increase in hotel pricing for that event because it’s so far away from there. However, like vacation rentals right by the park, we’ll see such a huge spike in it. So, hotels weren’t like the best indicator and we realized we needed to look directly at vacation rental demand. And what’s great about that is, you know, we had a kind of a cold start problem, which is like, okay, where do we get this data? We don’t have all this internal data. They don’t have huge histories of data. It’s just one unit in many cases. And so we looked at external data and external public data. What’s great about vacation rentals is very early on we could get decent indications and demand looking at public data because you can see both the price and availability of every single unit. It says if you could go on Expedia and see exactly how many rooms in each hotel were already booked, that would give you a really great demand picture. We were able to do that with just public data. Now that we have hundreds of thousands of properties connected to us all around the globe and billions of dollars book, I’m using our pricing each year, we get tons of internal data that helps us paint even more accurate kind of demand picture.
Mark Stiving: Are you pulling other pieces of information out, like, where the Superbowl’s going to be located?
Ian McHenry: We look at a lot of factors as with any kind of model, you’ll wait some more than others and a lot of the time those factors will just be duplicative of other factors, right? So, if people talk about airline flight arrivals, all these sorts of things. Like we’ll look at hundreds of factors, but really the best thing to look at is just upticks and demand. For the Super bowl or any kind of like one-time event and we’ll do two things and you know, we’ll look at both actual demand increases and we can see at a very micro level. So, as soon as we see a tiny uptick because we’re looking at across the whole, you know, say the 5,000, you know, properties in Atlanta, we can see one as few as like 0.5% of properties are booked, that there is a huge increase in demand relative to what we would expect and will automatically increase prices based on that change in demand without even knowing it’s the Superbowl.
Now on the flip side, we actually do have a full team of analysts like tracking these sorts of events. Also tracking, you know, hotel pricing data too. And we always very far in advance err on the side of increasing price because for these people, they only have one unit often. And even if there is a property manager with hundreds of units that they’re managing, there’s an individual owner behind each one in most cases. So, we cannot let it get booked for two lower prices. So, we air very far in advance on the increase in price. And so we’ll do that. You know, for something like the Superbowl automatically based on all these other sorts of factors including hotels without even having to know that that it’s there.
Mark Stiving: Yeah, I would think it makes sense. This is just me thinking for a second, but it makes sense that if you want to book my rental house, which I don’t have one, but if you want to book my vacation rental house out a year in advance, you’re going to pay a really high price because I don’t know what demand is going to be like then yet. Right. And you still have all this opportunity to book it for that given night coming in, right. You’re not trying to necessarily fill up, you know, 200 seats, you’re just trying to get the right price for that night for that place. And so you’re not like with airlines and hotels trying to kind of hedge your risk, right? By selling some at a lower price and doing those sorts of things. And so you do want to be more conservative and make sure you don’t get picked off when there could be a lot more demand coming and there is like we looked at the data, there’s kind of a sense of people booking very, very far in advance. Often you know are less price-sensitive because they know like family, we’re always going to Taho for President’s day weekend and we always like this house and so they’re often a little bit less price-sensitive as well. And so we’ll automatically increase the price too just based on the distance away.
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Mark Stiving: So, what factors besides watching demand do you think actually have an impact? In statistics there’s this thing called factor analysis where we look at all the different data that comes in and we say, even though I have 20 variables here, in truth, it’s all one variable or it’s all two variables. Right? And so how many variables really are there if you were going to do that type of technique?
Ian McHenry: Yeah. That, you express it very elegantly, right? There’s really two. And so demand is this one, right? Which is, hey, I haven’t given property, its price is going to fluctuate up and down for every given day based on the changes in demand and it, but it’s going to fluctuate kind of up and down around an average. Right. You know, which we think of as the average price for the place, but then how do you figure out what that average is? So you might double it for New Year’s Eve from 200, you know, from 200 to 400. But if you’ve got, you know, because 200 is the average. But if you got that 200 wrong, then it doesn’t matter that you’ve got the increase in demand and the subsequent increasing, you know, nightly price, right? So, we need to figure out what the right average price is. And that is this whole other interesting problem because, with vacation rentals, it’s not as simple as saying, hey, okay, it’s a four-star hotel and there’s a bunch of ones that look identical to that. And so we can kind of use that to figure out the average or occasion where I would know every single one is unique. And so ultimately what we’ve done is use this kind of this, there’s almost like booking curve flipped on its side where we say we know how quickly it should be booked up in general, not, not like percentage of rooms X number of days out, but actually like what percentage of the next 30, 60, 90 days should be booked with the idea that, if you’re overall under-priced, you’ll probably have to say like a hundred percent of your next 90 days booked. Right? If you are overall overpriced, you might only have five, six, 7% of those days book.
And there’s this happy medium where you’re priced on average, again fluctuating up and down for a day a week and that’s all this other sort of stuff. But your price right on average cause you’re hooking up at exactly the right rate and how do we get you to that and by adjusting that average right and things that can feed into that could be so many different things, right? You could have the same exact two properties that are exactly the same but one literally just has a better initial photo and we give this example which will lead to more demand, right? And in turn like you’ll get more booked up at the same price just cause you had a better first photo cause more people when they see it is clicking on it and then buying it. Right. And we have some great examples of this.
And where do you see that as a lot of the condo vacation rentals like in Hawaii and there’s this place Honua Kai, really beautiful? It’s over Kaanapali and they have these great places. And they have these really nice like glassed-in balconies and you can see the ocean, right? But they’re all sort of the same say a three-bedroom ocean view glassed-in and if you see two identical units, but one has like the first picture is the kitchen and the other one, the first picture is just that glassed-in unit. You’ll see their ability to have a 20% higher average price than the other one just literally based on the photo. And so we do it based on that how it’s booking rather than any kind of like regression on features and amenities. Because if you’re not marketing the amenities, it doesn’t matter that you have them in many cases.
Mark Stiving: This could be one of the coolest examples I’ve ever seen that marketing drives pricing.
Ian McHenry: I mean hugely, right? We kind of always say like the two sides of the same coin in so many ways. We’re starting to add a lot more interesting products that combine the two, which we’re really, really excited about. But for now, like beyond pricing at its core where we’re just pulling the pricing lever, we always say we’re just, we’ve priced whatever you give us. So, if you have terrible pictures and terrible all of that, like we’re going to lower prices so that you’re booking at the right rate and we’re optimizing your revenue, given your marketing. Now if you improve all of them, we’ll be able to capture more revenue from that. But like right now we’re just pulling that pricing lever for you and optimizing what you give us, but there’s a lot more than you can do on the other side.
Mark Stiving: Yeah. So if you did some kind of regression and you said, hey, here’s the feature set, you should be getting this price, but you’re well below that now all of a sudden we’ve got marketing consulting capabilities that we could go sell.
Ian McHenry: Yeah, yeah. I mean, yeah. And there are some interesting automated things you can do on that, on like picture rotation and optimization and identifying what’s in pictures and frequency of mention of like the hot tub and the title, all those sorts of things.
Mark Stiving: Nice. Nice. So, okay, so hard question, how do you price your product?
Ian McHenry: We just charge our baseline rate as 1% of bookings. So, we align ourselves completely with our clients. They’ll typically see a 10 plus percent increase in revenue depending on how sophisticated they were before. So, it’s a very ROI positive product for them.
Mark Stiving: Yeah. You can’t measure what they had. So, you couldn’t take a percentage of the increase.
Ian McHenry: We could. There are just so many factors, right? Like marketing, if they decide to decrease their marketing spend a ton and do all of those, it’s just really, really, we would love to, cause we’d probably actually make more money if we, you know, said, hey, we get half of the increase because in this case stems and increase you get 5%, that would be better for us. But it’s just really, really difficult to truly do apples to apples on that short of controlling all of their marketing as well.
Mark Stiving: Okay. So, I don’t want anyone else who’s listening to pay attention to what I’m about to ask. Can you point out to me what properties I want to buy as a vacation rental and how much money I’m going to make when I do that?
Ian McHenry: We don’t do that right now. There are some other great products out there for that. You know, it’s the law of averages on there, right? You know, we do have all that data. We have, you know, over 10 billion data points on average prices and amenities and all those sorts of things. But we instead, we’ll partner with some of those data providers and, and once you buy that property, then we’ll make sure we optimize the pricing around it rather than recommending properties to buy.
Mark Stiving: Okay. I’ll have to talk to you afterward then we’ll figure this out.
Ian McHenry: Yeah, I mean, you know, there is a real estate investment. A lot of sort of stuff, there are some great places where you can get slightly better cap rates and all of those. But, you know, really, the trick in a lot of that right, is finding an undervalued asset. You know, finding the one where, and this is becoming more and more, right? Like you can to the extent that you can figure out that they are under-optimized, right? Like that this is an asset. If they’re selling it like on a cap rate basis and you know, and they have a 5% cap rate on it, but then you see that they’re like average nightly rate and their average occupancy is below the industry benchmark. Then like, hey, that’s a great opportunity. Right? The problem right now is, and this is balding and we’re helping a lot of up and coming companies in this space, is that we don’t have that, right. We don’t have the Smith Travel Research Report that hotels have for that benchmarking right now to be able to do that. And so right now we do have that, we have a density in enough markets where we have it that we just haven’t productized it yet. So yes, you have to know somebody.
Mark Stiving: Okay, well, so I should ask this one then. How many vacation rental places do you have?
Ian McHenry: Myself personally?
Mark Stiving: Yeah.
Ian McHenry: One, but I moved into it.
Ian McHenry: It was such a good deal. I had to move in.
Ian McHenry: Oh yeah. I was lucky enough to be able to move into it. We had the place in Santa Cruz. We had as a vacation rental first, you know, you got to own your product and it was funny actually when we bought it, our home is about five blocks from the beach and most of this dividing line in Santa Cruz called Portola drive. We’re right over the edge of it. So, it meant we could actually buy it for like 40% less than just on the other side, but also all of the property managers in the area told us, oh, you can’t make any income from vacation rentals. People only come in the summer. And I had all the data. I knew that wasn’t true. There’s about 40% occupancy in the winter, but they were only changing the rates from like three 50 on average in the summer to 300 in the winter. So nobody is coming. You can book the nicest hotel for about $125 a night in winter, right in our three-bedroom. You know, you could buy three full hotel rooms for that price. So at any rate, we ended up making a lot of money off of it because it was really easy to capture that demand by just dynamically pricing it properly. Not so much money that we decided not to move in.
Mark Stiving: Right. Ian, I gotta wrap it up with this last question. What’s one piece of pricing advice that you would give our listeners that you think could have a big impact on their business?
Ian McHenry: Yeah, I mean it depends on what space you’re in, but really like for me, it’s playing with data. If you’re really trying to like figure out to do play with data and segment a lot like trying to understand demand and willingness to pay across all different kinds of segments you find interesting. I’ve found that you find interesting stuff just playing with the data. A lot of our insights just came from like me obsessing over it and finding interesting things from there and getting insights which are like very basic data analysis stuff. But you’d be surprised what you can find in that. I’d actually as a side note work that waste management come to my first, truly I’d skip this in the history of it. The first thing I priced was trash, and then we did incredible segmentations and found out really, really interesting things from that just by doing that kind of analysis, that was not anything fancy or that you need a Ph.D. for. So yeah, play with the data.
Mark Stiving: I think that’s a great answer cause I often see if you play with the data and you see something unusual or interesting, then you can dive in and say, well, what was that? What caused that? Then all of a sudden you’re learning from your data.
Ian McHenry: Yup. Exactly. And it’s a lot easier now to access and analyze that data than 10 years ago when I was starting.
Mark Stiving: People often complain about the black box where, oh, we can’t just trust the data but we don’t have to, we use the data to tell us, oh go look at this and see what you can learn.
Ian McHenry: Yup. No, exactly. And you know, if you’re building a product like ours where you do have buyers of that data that they need to trust the algorithm and not have it be a black box. One last thing is like expose as much as you can without necessarily giving away the secret sauce because a lot of the problem is getting buy-in for these predictions that you’ve made. You can have all these great predictions, but like getting people to actually use it is really, really difficult. So, one thing we did early was exposed a bit of that black box, right? Like you said, there might be just a couple of factors. There’s a lot of things that go into the factors. Then you can show like the prices up because of seasonality versus an event that creates a lot of trusts. And if you can show some of the underlying data trends that support that kind of recommendation and decision, it helps out a lot and helps people get over to that black box problem.
Mark Stiving: Yeah. Perfect. Ian, thank you so much for your time today. If anyone wants to contact you, how can they do that?
Ian McHenry: Just email me email@example.com pretty easy or connect with me on LinkedIn or angel list or anywhere else.
Mark Stiving: Excellent. Excellent. Thank you. Episode 53 in the can. Let’s see, what was my favorite part? How man, I just, I enjoyed listening about the algorithms. It was pretty awesome. So, to our listeners, what was your favorite part? Let us know in the comments or wherever you downloaded and listened, and while you’re at it, would you please give us a five-star review? These help us out a ton. If you have any questions or comments about this podcast or about pricing in general, feel free to email me, firstname.lastname@example.org.
Now, go make an impact!
**Note: Mark Stiving has an active LinkedIn community, where he participates in conversations and answers questions. Each week, he creates a blog post for the top question. If you have a question, head over to LinkedIn to communicate directly with Mark.