Latest / The Inspired Stories Podcast / CloudBeds Took 12 Years to Reach Purpose — Founders Say That Was the Point, with Adam Harris

Transcript

CloudBeds Took 12 Years to Reach Purpose — Founders Say That Was the Point, with Adam Harris · The Inspired Stories Podcast

• 0:04
  Welcome to another edition of the Inspired Stories podcast,
• 0:08
  where leaders share their experiences so we can learn from
• 0:12
  their successes and be inspired by how they've overcome
• 0:15
  adversity. As you listen today, let one
• 0:18
  idea shape what you do next. My name is Anthony Kotaspodi and
• 0:22
  today's guest is Adam Harris, Co Founder and CEO of Cloudbeds, A
• 0:27
  hospitality management platform that brings everything lodging
• 0:31
  businesses need into one easy to use cloud solution.
• 0:36
  Cloudbed gives hostels, hotels and vacation rentals tools for
• 0:41
  reservations, payments, revenue and guest management all in one
• 0:45
  place. The company now supports 10s of
• 0:48
  thousands of properties in 150 plus countries, integrates with
• 0:52
  over 400 travel partners and processes around $15 billion in
• 0:58
  annual room sales under Adam's guidance.
• 1:01
  Cloudbeds has been highlighted by Ink Magazine and Deloitte for
• 1:05
  rapid growth, while he himself was named one of San Diego's
• 1:09
  young influentials. Before starting Cloudbeds in
• 1:13
  2012, Adam Co founded Ticket Socket and held finance roles at
• 1:18
  Think Equity Partners and AG Edwards.
• 1:21
  He also serves on the boards of Computers to Kids, Zesty and
• 1:26
  Connect San Diego and hold Series 7 and 66 licenses.
• 1:31
  But before we get into all that good stuff, today's episode is
• 1:35
  brought to you by my company, Add Back Benefits Agency.
• 1:38
  Listen, if you run a business, you're likely stuck in the cycle
• 1:41
  of rising insurance premiums. You're paying more, but your
• 1:44
  team is getting less. And many people can't afford
• 1:47
  coverage at all. So we do things differently.
• 1:50
  We provide your hospitality employees with unlimited access
• 1:53
  to doctors, therapists, and prescriptions.
• 1:56
  It's always free for them to use.
• 1:59
  But here's the part that surprises most people.
• 2:01
  Unlike every other employee benefit out there, our program
• 2:05
  puts more money into your company's bank account.
• 2:08
  As an example, we recently helped the client increase net
• 2:11
  profits by $900 per employee per year.
• 2:15
  Results vary, but gains like that can change how a business
• 2:19
  is valued. And the consultation is free.
• 2:22
  See if you qualify today at AD back benefits.com.
• 2:26
  All right, back to our guest today, the CEO and Co founder of
• 2:29
  Cloudbeds, Adam Harris. Thanks for making the time to
• 2:31
  Share your story today. Thanks for having me.
• 2:35
  So, Adam, before we get into the work that you're doing today
• 2:38
  with Cloudbeds, I want to understand just a little bit
• 2:41
  about the path that brought you here.
• 2:43
  I see, you know, Rose is a financial analyst in your past,
• 2:47
  director of finance for the Keating Hotel Group, which gave
• 2:49
  you a foundation in the hospitality industry.
• 2:52
  And I see an exit from at least one tech company.
• 2:55
  So there's this kind of confluence of entrepreneurship,
• 2:59
  tech and hospitality. Was this sort of the master plan
• 3:03
  or were you just kind of figuring things out step at a
• 3:06
  time and it all sort of came together and cloud beds years
• 3:10
  later? You know, I, I'm a big sports
• 3:14
  fan. I've always been into
• 3:16
  competitive sports. I, I think the best analogy for
• 3:20
  my early career was no huddle offense as I sort of bounce
• 3:24
  between plays in my early days. You know, finance, I, I always
• 3:31
  loved this sort of system and style of what Wall Street
• 3:36
  represented. And if it taught me one thing
• 3:39
  and one thing only, the enemy of good decisions is emotion.
• 3:44
  And when, when you fall in love with a deal or a human, you're
• 3:50
  done, right? Like you're done, you're toast.
• 3:53
  Your, your heart beats for that, that deal or that person.
• 3:57
  And hospitality ultimately taught me that business is
• 4:01
  personal, right? So there's this yin and Yang
• 4:03
  there, right? There's a very different style.
• 4:07
  You're upset customer is still there in the morning, right?
• 4:11
  The only other practice in the world that I could ever think of
• 4:14
  as medicine, right? You are as a doctor or nurse,
• 4:18
  you see your patient in the morning.
• 4:19
  That's a very interesting exchange.
• 4:22
  And so finance gave me discipline, hospitality gave me
• 4:26
  the purpose, and tech ultimately gave me a tool to build between
• 4:31
  the both, between two of those passions.
• 4:33
  Very elegant. I like that.
• 4:36
  So let's think about the time at Keating Hotel Group, right.
• 4:39
  This gave you that foundation and but but the the finance work
• 4:43
  came first, right. The hospitality came later.
• 4:45
  OK, so let's talk about the finance.
• 4:47
  Maybe pull out a story there that showed you this lesson.
• 4:51
  How did you put it? The enemy of good of a good deal
• 4:53
  as emotions. Yeah.
• 4:56
  So you know. Look, I mean, when you're, when,
• 4:59
  when you're young and you're working at an investment bank,
• 5:02
  your, your hours are pretty hard, They're long, they're
• 5:05
  arduous, they, they extend over the weekend.
• 5:09
  And I think what ultimately happens, and it wasn't one deal
• 5:13
  as many deals. You saw the interaction between
• 5:16
  the entrepreneur or the business leader, the private equity firm
• 5:20
  or the venture capital firm, and then ultimately the prize.
• 5:24
  And when you see dollar bills, you're an entrepreneur.
• 5:29
  When you see dollar bills or if you sold a business, you know
• 5:32
  this, right? You start to fall in love with
• 5:35
  the outcome more so than what is actually the journey.
• 5:39
  And, and I think what happened for us, at least for myself,
• 5:43
  working from 4 AM 10:00 PM for over 2 years of my life taught
• 5:48
  me grit, a little bit of hard words, little perseverance.
• 5:51
  But the prize was way bigger than the transaction.
• 5:58
  But what got caught up in that journey was all of the emotions.
• 6:03
  And so you lost sight of the prize.
• 6:06
  And, and, and let me bring this to cloud minutes a little bit
• 6:09
  because, you know, when I, when I was working in finance for the
• 6:13
  private equity firm that own the key team, you know, it was very
• 6:18
  transactional. We were trying to acquire more
• 6:20
  hotel assets or more land to do more hotel assets.
• 6:23
  It wasn't a concept, it wasn't a purpose.
• 6:25
  We weren't trying to take over the world.
• 6:27
  We were trying to deliver better hospitality.
• 6:29
  It was purely financial gain. And, and that that ultimately
• 6:34
  made me fall, fall out of love with what we were doing in, in
• 6:38
  and around, in and around that space.
• 6:41
  But let me, let me come back to cloud that.
• 6:43
  So when you start, I remember this.
• 6:46
  I, I remember this every single time we started a business for
• 6:49
  like, look at the opportunity. It's so big.
• 6:52
  Like if, if my wife is building a new app right now and she's
• 6:55
  like, there's so much opportunity here.
• 6:58
  And I was like, I get it, but we need to take a step back and
• 7:02
  flip it. Yes, there's opportunity, but
• 7:04
  let's talk about the milestones because the first milestone that
• 7:08
  you and I are going to celebrate when I help you launch your app
• 7:11
  is going to be is it done? Is it live?
• 7:14
  Is it downloadable? And then the next prizes.
• 7:17
  Do we have a user that says this is good?
• 7:20
  And then do we have two and then four and then eight and then 16
• 7:24
  and then so on. And it what, what often times
• 7:27
  happens is you as an entrepreneur look at Jeff Bezos
• 7:31
  or Mark Zuckerberg and we see the, we see the .01% outcomes
• 7:36
  and we're like, wow, that would be so cool.
• 7:38
  And society always teaches us to say something is a little bit
• 7:42
  better. The grass is always greener and
• 7:44
  we're always striving for better and more.
• 7:47
  But what what you have to understand as an entrepreneur,
• 7:49
  you have less than one in 10,000 chance of actually getting to
• 7:54
  $1,000,000 in recurring revenue. As a SAS business.
• 7:57
  It's even harder now and then you get to 10 million, it's one
• 8:01
  in 100,000 and you get to 100 million, it's one in a million.
• 8:04
  And so like the statistics are very much against you have a
• 8:07
  better chance of getting hit by lightning or bit by a shark then
• 8:11
  actually hitting real milestones that are baked into the
• 8:15
  entrepreneurial journey of building a company.
• 8:17
  And and so when Rich and I, my Co founder and I realized that
• 8:22
  the celebrations in the journey with our team was in customers
• 8:27
  was way more fun than the milestones because the
• 8:30
  milestones were so fleeting. We we'd hit it and then we'd be
• 8:34
  on to the next and or we, we raise a little bit of capital
• 8:38
  and then we had to go operate off it.
• 8:40
  And so we've just really shaped our journey around purpose much
• 8:46
  more so than the transaction. And that's been an amazing eye
• 8:50
  opener for us over the the years Now we.
• 8:52
  Were you sorry for talking over there, Adam, but were you able
• 8:57
  to start Cloudbeds with that concept, that framework in mind
• 9:03
  or was it something that you developed as you had hit some of
• 9:06
  those milestones so? It's a little bit of both Now
• 9:11
  Cloudbeds is scaled into something much bigger than any
• 9:14
  of the other businesses that we had founded or created.
• 9:18
  They're really successful. This is a multi global you, you,
• 9:22
  you, you shared some of our accolades around, you know how
• 9:25
  much revenue is running through us.
• 9:27
  We're a category leader in our space, close to 700 employees in
• 9:30
  in 144 countries. So very big, very established,
• 9:35
  almost a quarter billion dollars in capital behind us.
• 9:38
  So like, yeah, a little bit different pressure and a little
• 9:42
  bit of different sort of financial engineering comes into
• 9:44
  play as an operator at this stage.
• 9:46
  But but no, like I would say, Anthony, you're right.
• 9:49
  Like early on we had already learned a lot of lessons.
• 9:53
  We were already in a financial position where we could take
• 9:57
  some risk, but but we are also learning the journey of taking a
• 10:03
  venture backed company and going through those phases of, of, of
• 10:08
  expansion, which is very different than, you know, when
• 10:12
  you're fully profitable and you're at scale and and you're,
• 10:15
  you're using dials and levers to sort of optimize for leverage.
• 10:18
  But but nevertheless, like, yeah, I mean, like the early
• 10:22
  journey of cloud beds was very much the napkin.
• 10:25
  Like we had an idea it was on a napkin.
• 10:28
  It, it came from a challenge, but then it was very easy for us
• 10:32
  to connect the dots into how we're going to celebrate this,
• 10:35
  how we're going to build a team, how do we scale?
• 10:38
  And then through that scale, there was a lot of course
• 10:41
  correcting along the way. So it was always self improving.
• 10:44
  One of our core values is Kaizen.
• 10:45
  It's a Japanese philosophy of 1% improvements every day.
• 10:49
  So, and that was kind of kicked in early enough.
• 10:54
  So tell us about the napkin. How did this idea come about?
• 10:57
  What was the challenge that you guys were responding to?
• 11:01
  Yeah, So, so rich was in Brazil, found this beautiful Posada
• 11:06
  Posada is like a boutique hotel along the beach.
• 11:10
  He had the Western Union money to a stranger to book it.
• 11:13
  OK. That was the, that was the
• 11:15
  impetus, I mean. Imagine are we talking about?
• 11:17
  This is 2012, right? So, you know, Internet is very
• 11:22
  real. There's cross, you know,
• 11:24
  cross-border transactions happening, but that was a first.
• 11:29
  That was a that was a first for us as, as individuals who love
• 11:32
  to travel and, and that was the moment.
• 11:34
  And so we built Ojibicar, which means where to stay in
• 11:36
  Portuguese. And it was about connecting
• 11:39
  travelers to unlisted properties across Brazil for one catalyst
• 11:44
  only. And that was World Cup came, big
• 11:48
  players, you know, hadn't really organized and individuals needed
• 11:54
  to connect to rooms. And so after the World Cup came
• 11:57
  and went, all the big players showed up with real money and
• 12:03
  the classic pivot or die moment happened.
• 12:05
  We're like, wow, we can't compete with booking.com and
• 12:08
  $100 billion of, of, of assets that they have under their
• 12:12
  enterprise value. We need to rethink this.
• 12:15
  And what we saw was, oh, like we don't need to be this listing
• 12:20
  site. We can actually go to the full
• 12:23
  management of these hotels and actually lift them up and start
• 12:28
  to connect the dots across their experience.
• 12:30
  And, and, and that was, that was a huge moment for us, but the
• 12:35
  purpose had never changed. We just found a better vehicle
• 12:38
  for it. So the idea started in Brazil.
• 12:42
  And so you were supposed to be at the, in the original concept,
• 12:46
  you were like a, a booking.com and expedia.com kind of a thing.
• 12:50
  We were. We were a YEAH connection to
• 12:53
  help a guest find a hotel that had a room that was available.
• 12:57
  OK. And so then the World Cup
• 12:59
  happens, then big players are like, OK, now we see Brazil for
• 13:04
  some reason they hadn't before, this big country in South
• 13:06
  America. And now we're going to move in
• 13:08
  there and you're like, OK, we've got a pivot.
• 13:11
  And so the pivot is, is it roughly what into what Cloud
• 13:15
  Meds is today? Yeah.
• 13:17
  I mean, I think what what we started as was just the
• 13:21
  distribution side of what a hotel needs to to do to find a
• 13:25
  guest. And that shifted into how do we
• 13:29
  help a hotel run their business and that's everything from the
• 13:32
  operation side, sure, selling a room, what that guest
• 13:36
  experiences and then ultimately how do you make more money on
• 13:40
  behalf of the hotel through intelligence layers.
• 13:43
  And that all came from one data model.
• 13:45
  We're both technologists as as leaders.
• 13:48
  And so it was very easy for us to see how this product
• 13:52
  envisioned into something of a platform as you said earlier.
• 13:57
  And in what, what was really timing in our favor was
• 14:03
  competitors were just bolting on things together.
• 14:08
  They were just like either acquiring things and kind of
• 14:11
  like loosely bolting them on and, and here's our suite of
• 14:14
  solutions. And then you know, you just had
• 14:17
  others who had less aspirations and they're like here's our PMS
• 14:21
  or here's our platform and like you can connect all these
• 14:23
  partners. We saw that totally different.
• 14:27
  We saw vertical SAS in 2012 as an opportunity.
• 14:30
  We saw, we saw a software systems going to go deeper and
• 14:34
  wider and what they could deliver.
• 14:36
  And and there was rumblings from the investor community that
• 14:40
  these were going to be big, big business models.
• 14:44
  And so we early on started to see the unified platform as the
• 14:48
  differentiator. And so we came into a market
• 14:51
  that never had unified platforms ever and started the uphill
• 14:56
  battle of pushing a boulder and in introducing Cloudbeds way and
• 15:02
  here we are today. Say more about the unification
• 15:05
  piece. Can you give us one specific
• 15:07
  example of how what you guys were doing was more integrated
• 15:11
  and easier for the hotel rather than the bolt on solutions that
• 15:15
  existed? Yeah, yeah.
• 15:17
  So I mean the, the average number of tools that a hotel
• 15:20
  uses or tabs and browsers as as we like to call it, is 19 in
• 15:26
  20/26/19 to run their property. Our unified ecosystem takes
• 15:32
  about 14 of them off the shelf and combines them into a single
• 15:36
  username and password. And, and as a result, we have
• 15:39
  organically grown into one of the biggest platforms in the
• 15:42
  world for a reason. Our, our system lifts revenue
• 15:45
  year over year on behalf of the hotel.
• 15:47
  There's more coordination amongst intelligence of pricing
• 15:51
  rooms to how we do the guest experience and the left hand
• 15:54
  starts to talk to the right hand.
• 15:56
  So what's going on on the operation side and then what's
• 15:58
  on the guest side starts to bridge into a very, a very
• 16:04
  strong cultural exchange between those two parties.
• 16:07
  And what that leads to is, you know, every award you can think
• 16:13
  of in the space A-Team that's motivated to to drive more
• 16:17
  purpose for our hotelier and ultimately their guest.
• 16:21
  And now we're introducing data products like signals that are
• 16:25
  driving accuracy that this industry has never, never seen
• 16:28
  before. And it kind of means that we're
• 16:32
  the pacesetter in the race, and that's kind of fun.
• 16:36
  Tell us about the signals product.
• 16:38
  What is this accuracy that's being delivered?
• 16:40
  What? What is the usefulness of the
• 16:42
  data? Yeah.
• 16:44
  So you know, look, I the best way to describe signals is Cloud
• 16:51
  Bids is in this really unique place where because we sell
• 16:56
  rooms on behalf of our hotels, because guests interact with our
• 17:00
  tools every single day, because operations interact with our
• 17:03
  tools every single day. And then we have partnerships
• 17:06
  with all the major brands in the world.
• 17:09
  We have all these different signals coming in.
• 17:12
  This is the, this is the participant name from guest
• 17:16
  review data to search traffic on the Internet to what LMS are
• 17:20
  sending in terms of traffic form to how rooms are being sold on
• 17:24
  distribution sites. It is a monument of data, a lot
• 17:29
  of its proprietary to us. And then there's a lot of third
• 17:31
  party data that we have partnerships that are unique to
• 17:34
  us as well. And so when you bring all that
• 17:36
  together, AI really can only act on what it can see, right?
• 17:41
  That's, that's the biggest issue with AIAI is very good at
• 17:45
  pleasing, but it will make stuff up very quickly if it doesn't
• 17:49
  have enough context or data to, to accurately provide the, the
• 17:53
  input. So when when we build signals,
• 17:56
  we're like, wow, we have all these signals, all these data
• 17:59
  models, all these single models. And we designed in a way where
• 18:03
  you have booking and rates and guests and channels and reuse
• 18:06
  all in this one place. And as a byproduct, we can run
• 18:09
  millions and millions of permutations on that data.
• 18:12
  Anthony And in the way the best analogy is, is when you see your
• 18:16
  Google Maps traffic being really red or really orange or really
• 18:22
  green. Well, that's a causal engine
• 18:25
  working behind the scene. It sees cause and effect of a
• 18:28
  lot of devices in one cluster using or around a certain
• 18:33
  location. Or another example would be Uber
• 18:35
  when they surge demand price you for coming out of the Staples
• 18:40
  arena after a basketball game, right?
• 18:43
  So they see high concentration of people trying to get a ride
• 18:47
  and so they surge price. So that cause and effect
• 18:49
  behavior is actually a neural machine learning model.
• 18:53
  It's been around for 20 plus years, but it's never been
• 18:56
  applied to hotels. And so we actually took a team
• 18:59
  of data scientists and we said we think we have enough data
• 19:03
  between our proprietary and our third party to do a causal
• 19:07
  neural engine. And as a result, we can forecast
• 19:10
  a demand curve of a hotel up to 180 days at a 95% accuracy.
• 19:16
  In some cases that is about 10 absolute points higher than
• 19:21
  anything in our system in terms of forecast ability.
• 19:25
  OK. So like monumental lift in terms
• 19:28
  of accuracy. Well, that's like a crystal
• 19:30
  ball, Anthony. If I know what my forecast is
• 19:33
  going to look like, if I know that in 36 days my occupancy is
• 19:36
  going to be 82%, why might staff differently?
• 19:39
  I might buy supplies differently, I might price
• 19:41
  differently, I might sell my rooms differently.
• 19:44
  My whole commercial strategy gets upended and I now have
• 19:48
  tools that I can deploy. And that's that institutional
• 19:51
  knowledge layer or what, what, what, what, what we're calling
• 19:55
  signals is our, our domain, domain ready LM.
• 20:00
  And it's there to to make recommendations and it's badass.
• 20:04
  So are you able to do this for any of your hotels or only where
• 20:10
  you've got enough concentration of clients that you've got sort
• 20:14
  of the quantity of data that you need?
• 20:16
  Every single hotel is in A1. OK, So we designed the model so
• 20:21
  that each hotel has its own, each model, we take 10
• 20:25
  mathematical models and it converts itself into one
• 20:28
  depending on the region. And, and you, you brought up a
• 20:31
  great observation. So first of all, you nailed it.
• 20:34
  Never get asked this question, but some hotels might be in a,
• 20:38
  a, a market where there's tremendous amount of pressure
• 20:42
  for events, right? Others might not see a lot of
• 20:45
  those events, some might have a lot of competition, some might
• 20:48
  not. And so depending on all those
• 20:50
  attributes, the model adjusts itself to, you know, complement
• 20:55
  not only said property, but also said model market.
• 20:58
  And that might mean we lose a little bit of accuracy because
• 21:02
  of those factors. We might gain a little bit of
• 21:04
  accuracy because of those factors too.
• 21:07
  But every single individual gets their own model and that is very
• 21:12
  unique, very enterprise and and more importantly, it can come
• 21:16
  down all the way down to the smallest of hotel.
• 21:18
  So we're really excited about the flexibility here.
• 21:22
  So this is really interesting. So I'm seeing multiple value
• 21:27
  propositions, right. There's the fact that folks
• 21:30
  don't need to use all these bolt ONS.
• 21:32
  You've what did you say went from 26 tabs to 14 because you
• 21:36
  got. 19 to 1419 to 40, but it feels like 26.
• 21:40
  It feels like 26. Yeah, and so, right.
• 21:44
  It's just easier if you've got one tool where everything's
• 21:47
  integrated and you can access the data and it talks to each
• 21:50
  other better. Now this and sorry I was trying
• 21:53
  to write down the the phrase for it but then you were explaining
• 21:57
  it. It just blew my brain.
• 21:58
  The causal neural network. Causal neural engines, yeah.
• 22:02
  Neural Engine. And so being able to have that
• 22:05
  forecast data is enormous too. Are there other components here
• 22:09
  that like when you go in to talk to a new client or new prospect,
• 22:13
  like what, what does that presentation look like?
• 22:15
  Like, you know, give me sort of that elevator pitch.
• 22:20
  I'm the worst at this elevator pitch, by the way, but I but I
• 22:23
  appreciate you putting me on the spot.
• 22:26
  So if, if I was putting my sales hat on and I was walking into a
• 22:30
  hotel, I think the elevator pitch was very similar to what
• 22:34
  I'm saying and what I said earlier, which is, look, we live
• 22:39
  in a world where data is so fast and it gets captured or it
• 22:43
  doesn't and there's context or there's not.
• 22:45
  And, and when we can ask a new technology information and we
• 22:52
  can ask a new technology for an output and it can give us an
• 22:56
  observation and then the context and an explanation at a PhD
• 23:00
  level reasoning, there's something here.
• 23:02
  OK, so when we thought about all the data that lives in cloud
• 23:05
  beds and what those data points connected or isolated reveal, we
• 23:11
  realized there was this tremendous visibility that a
• 23:14
  hotelier was, was lacking. And most of the models that are
• 23:18
  there to help price a room or package or how you think about
• 23:21
  selling was heuristic, meaning it was a point in time looking
• 23:26
  backwards. OK, so imagine a photograph.
• 23:30
  It's nostalgic. You see yourself as a child.
• 23:33
  I just saw one of me dressed up in my soccer gear for my school
• 23:37
  pictures. Why my mom allowed me to wear my
• 23:39
  uniform for school pictures I don't know.
• 23:41
  But she's like, it was a fight I wasn't willing to take that
• 23:44
  morning. But I literally saw this
• 23:45
  yesterday and it brought back a lot of memories in time.
• 23:51
  Well, if I'm going to make decisions on memories and time,
• 23:54
  I was clearly needed a haircut that day.
• 23:57
  I don't know if I had a soccer game that afternoon because I
• 24:00
  don't have any contacts except for what's in that picture.
• 24:04
  Fast forward, a causal neural engine is like a motion picture
• 24:07
  leading up to that moment as well as whatever follows.
• 24:11
  OK, So we can get all that snapshot of that data, but we
• 24:15
  can then start to piece it together so that you actually
• 24:17
  understand why Adam, as a cute little kid with a bowl cut
• 24:22
  haircut, is in his soccer uniform for school pictures,
• 24:26
  right? And we can understand what led
• 24:28
  up to it and then what's going to follow.
• 24:29
  And then we can run permutations against that.
• 24:32
  The beautiful thing is there's no human on the planet that can
• 24:35
  run a million permutations an hour.
• 24:38
  It's not possible, right? And so if I can give you trust
• 24:41
  in the system and show you that, hey, on this day, Anthony, you
• 24:45
  probably should increase your rates or you should probably add
• 24:48
  more advertisements or you should send an e-mail marketing
• 24:51
  campaign to this segment of customers who always come to
• 24:53
  your properties to try to help adjust customer lifetime value
• 24:58
  or capture a cheaper acquisition of that guest.
• 25:01
  Yeah, you should turn that light switch on today.
• 25:04
  Where we go with that is a totally different arena.
• 25:08
  I mean, we're talking about things like, hey, should I take
• 25:12
  customers from a corporate account versus a leisure
• 25:15
  account? How do I buy my breakfast
• 25:17
  supplies? All of those things will come
• 25:19
  next. And for us, what's exciting is
• 25:22
  signals is is invisible. They make it visible through
• 25:26
  user experiences, but it's really invisible.
• 25:28
  It's just a backbone infrastructure that's taking
• 25:31
  lots and lots of data, running it against hospitality models
• 25:34
  and advanced math models. And it produces something that
• 25:37
  you and I as as probably less experienced in the revenue, the
• 25:42
  revenue intelligence layer of a hotelier can actually like
• 25:46
  transcribe that into a decision. So that action layers, we went
• 25:50
  from system of record, we're just storing data system of
• 25:54
  action, which that intelligence orchestration unlocks the real
• 25:58
  input in output that people were asking.
• 26:01
  So it took us 1213 years to finally see purpose.
• 26:06
  Like we were always after this, but it took us all this scale
• 26:10
  and all this data and all this, all this like perseverance to
• 26:14
  finally get to a moment where I'm like, I actually can hand
• 26:16
  the keys back to the, to the, the hotel.
• 26:19
  And you're like, here's your brand new Ferrari.
• 26:21
  Let's go take it for a test brand because it's it's really
• 26:24
  powerful under the hood. So before the causal neural
• 26:28
  engine that you guys had the idea for and have implemented,
• 26:33
  the real sales pitch was, hey, we're going to take away a lot
• 26:38
  of those tabs and we're going to give you a more integrated
• 26:40
  solution. And you guys started in Brazil,
• 26:44
  you had that pivot and then how did you get that first client
• 26:48
  with with the new platform? Typical sales motion, right?
• 26:53
  You got to call him, you got to talk to him, you got to survey
• 26:56
  him, you got to be in front of the face of the customer.
• 26:58
  I don't speak Portuguese, so that was not my role, but there
• 27:01
  were other individuals in inside our girly company that helped
• 27:06
  unlock getting those first customers.
• 27:09
  But there's a story here, OK? And there's a very pivotal
• 27:12
  moment in our journey that was the make or break of, of our,
• 27:19
  our story. And about two years in, we just
• 27:25
  started doing the pivot to let's build the SAS application, this
• 27:29
  platform that hotels serve versus the place that a guest
• 27:32
  just finds them. And our head of sales went to my
• 27:38
  Co founder and said, Hey, we need a channel manager in the
• 27:45
  two technical founders with no hotel experience were like,
• 27:48
  what's a channel manager? And they're like, well, that's
• 27:51
  how you sell rooms online across all the major OTAs.
• 27:57
  So like booking and Expedia and things like that.
• 27:59
  I was like, OK, so it's like a switch, like network switch.
• 28:04
  You, you plug one line in and then it expands and goes to
• 28:08
  other like, yeah, that's a that's a good way of describing.
• 28:11
  I'm like, which one? What, what are the channel
• 28:14
  managers? We didn't know any of that
• 28:16
  stuff. And so they're like, well,
• 28:17
  there's just one called My Allocator.
• 28:20
  It's based in the UK and it has lots and lots of customers like
• 28:26
  the ones that we are now serving in Brazil.
• 28:30
  Let's go partner with them. OK.
• 28:34
  So I introduced myself to the leadership team through within
• 28:39
  three days, we had an actual M and a call.
• 28:42
  They were saying, hey, would you guys be open to us joining the
• 28:46
  team because we like what you're doing, you like what we're
• 28:49
  doing. And we had just raised
• 28:52
  $2,000,000 in capital, OK. Well, three weeks later, we only
• 28:57
  had a million of that capital because we actually wrote a
• 29:00
  check and bought my allocator and it was bigger than us.
• 29:05
  My alligator was like two or three times bigger than us in
• 29:08
  revenue. It forced our entire model to go
• 29:11
  from transactional to SAS. It was a one way door moment, if
• 29:16
  you've ever heard that analogy. And we were fully committed and
• 29:21
  Cloudbuds went global overnight. We had sixty countries at the
• 29:25
  end of 2014. And to build something last, you
• 29:29
  got to take some exorbitant amount of risk and walk through
• 29:32
  a door and know that it's kind of shut behind you.
• 29:34
  And that was our commitment to to the the my allocator thesis.
• 29:39
  But what we learned in that moment was a, a really valuable
• 29:47
  lesson. So my allocator was not just
• 29:51
  connected to cloud bets. It was a resource for about 15
• 29:55
  of our other competitors that were early, OK, they were all
• 30:00
  connected into and they were all using it as distribution on
• 30:03
  behalf of their hotels. And there were some very good
• 30:05
  established partners there. That was part of the reason why
• 30:08
  I had it had grown. It was cheap, good tech,
• 30:12
  reliable and it had other PMS partners.
• 30:15
  The moment we bought it, I controlled a very valuable
• 30:20
  resource because all these hotels needed to sell online.
• 30:23
  And over time, US owning that pipeline meant that we had
• 30:29
  exorbitant amount of viewership on what's going on at our
• 30:33
  competitors as well as we had pricing control over them.
• 30:38
  And none of those 15 competitors exist today.
• 30:41
  As a byproduct of that, it was our control we seized.
• 30:47
  I was about to say we see some oil fields, but like the the
• 30:51
  that might be too soon, but like the the reality is we control
• 30:54
  the very valuable resource overnight and so.
• 30:57
  So did you just cut them off or what happened to them?
• 31:00
  We didn't. Why did they not survive?
• 31:02
  We didn't need to cut them off. What we did is we changed
• 31:05
  pricing and over time when you used one of those applications
• 31:10
  plus my allocator, my allocator became a cost center.
• 31:15
  They had to pay for the subscription to that service as
• 31:18
  well as us. But when they came to us, they
• 31:21
  didn't have to pay for that service twice.
• 31:23
  We could give it away for free. We could lower in half.
• 31:25
  And so there was an arbitrage in how we delivered our SAS fees
• 31:29
  versus a competitor and they were always higher.
• 31:32
  We always had a slightly competitive advantage in price,
• 31:36
  which for small hotels at that time was, was was very
• 31:39
  important. There was an elasticity there.
• 31:42
  But the other thing was because we control the asset, it meant
• 31:46
  we unlocked data. So we were the ones sent sending
• 31:49
  rooms to booking.com. So we were the ones who are
• 31:52
  getting to know booking in their team.
• 31:55
  Some of our best hires came from that team early on.
• 31:58
  And so over time we started getting more and more accolade,
• 32:01
  more and more reach, more and more resource.
• 32:04
  The the greatest lesson in my life has always been never
• 32:09
  closed doors. You never know when you need to
• 32:13
  access a resource. And in this case, like we, we
• 32:18
  wanted to continue to grow. We wanted the seat at the table.
• 32:24
  We always talked about that. We wanted to bang our hands on
• 32:27
  the table on behalf of the hotelier because the hoteliers
• 32:31
  that we were serving were independents and they didn't
• 32:33
  have a seat at the table. That the groups that did were
• 32:35
  the Marriotts and the big brands of the world on the OTAs.
• 32:39
  And so here we are, this little company getting a seat at the
• 32:42
  table, becoming a top 10 distributor of rooms online.
• 32:45
  That that's pretty cool. So did you acquire any of these
• 32:49
  competitors that were starting to drift off?
• 32:52
  Nope. You just kind of let them fall
• 32:53
  by the wayside and we let them get their customers.
• 32:56
  Yeah, we let them drift off into the BIS.
• 32:58
  We won. We won over time with better,
• 33:01
  better product. We, we scaled as a by product of
• 33:04
  that. And did we do it perfectly?
• 33:07
  No, that's part of the journey, that's part of the fun.
• 33:10
  But we definitely were pretty disciplined in our in our
• 33:14
  approach and we we did that seven times again over over
• 33:17
  time. Did what specifically?
• 33:20
  7 times acquired. Like another alligator.
• 33:22
  Yeah. We bought 7 other assets over
• 33:24
  time that were very mission critical to the ecosystem of, of
• 33:30
  hoteliers and that allowed us to bridge more of those tabs into a
• 33:35
  unified ecosystem. We did it early.
• 33:38
  So by the time we got to today, we were way ahead of of our
• 33:41
  competition and the unified unification and and as a result
• 33:45
  we can do more things on behalf of that consolidated data model.
• 33:51
  So when you started in Brazil working mostly with small
• 33:55
  independence, obviously you've expanded to dozens of countries
• 33:59
  now over what do we say, 150? 150, yeah.
• 34:05
  Are you still working mostly with Independence, Oregon?
• 34:08
  Do you have some of the big chains in there too?
• 34:10
  No. So we we love independence.
• 34:12
  We will we will happily work with big brands, but we we we
• 34:16
  see that this is a rising tide lifts all boat moment for for
• 34:19
  the independent ecosystem. And so we, we're big fans of, of
• 34:23
  helping hotel yours that whether they're a group of independent
• 34:28
  hotels or, or a micro chain of hotels or just a mom and pop
• 34:33
  that's running their, their, their family business, we're
• 34:37
  here to help them. And do you need feet on the
• 34:41
  street in all of the geographies that you're located or doing
• 34:44
  business in? Different models in different
• 34:47
  regions depending on depending on what, what, what is required
• 34:53
  of us. But I would, I would argue we've
• 34:55
  always been hyperlocal. So we, we want to feel like that
• 34:59
  market. We probably took a, a chapter
• 35:02
  out of other other larger businesses that operate in our
• 35:08
  ecosystem as examples of how they did their go to go to
• 35:11
  market motion. But you know, for us it was how
• 35:15
  do we connect on a human to human level?
• 35:19
  Hospitality is a human industry, right?
• 35:21
  So we needed to put our humans in market where possible.
• 35:26
  Now, fascinating. And so you've mentioned that
• 35:30
  there's been some investment. What can you say about your
• 35:32
  partners? Meaning the investors who have
• 35:38
  invested in US. Yeah, these like, you know,
• 35:41
  friends and family. Is this like big institutional
• 35:44
  you got private equity involved? We got a little bit of
• 35:47
  everything, but like we, we had the friends and family early on
• 35:51
  who took a huge bet. We've we've made them a fortune.
• 35:55
  We had our early stage institutional investors, the
• 35:58
  peaks bands, the cultivation capitals of the world though the
• 36:04
  counterpart. Those were early stage VC,
• 36:07
  traditional VC in the Bay Area mindset.
• 36:11
  We then added groups that were like the Vikings and the soft
• 36:14
  banks of the world. These are big, big funds with
• 36:17
  unlimited capital behind them. The that was the scaling motion,
• 36:23
  right? Those were the the big
• 36:25
  resources. So, you know, three days before
• 36:27
  lockdown with COVID, Viking gave us $80 million at the height of
• 36:32
  the market in 21, we raised $150 million.
• 36:35
  And, and those gave me resources to take what was a very fast
• 36:40
  growing company in, in leverage that into a very profitable
• 36:44
  company, still growing just as fast, but now profitable and
• 36:49
  with operating leverage. And that was a very big motion
• 36:51
  because we, we went from a world where where lending or the
• 36:55
  lending rates were pretty much free, right?
• 36:58
  Like if you think about 21 interest was nothing and then
• 37:02
  we've gone into a high interest environment, which is why
• 37:05
  mortgages are higher. And so like you and I are forced
• 37:08
  to show profit or forced to show operational leverage.
• 37:11
  So this has been a journey. I mean, like what wasn't going
• 37:14
  on in 2012 to, to what was going on today has been a couple
• 37:19
  roller coasters, but it's been fun.
• 37:22
  And, and I think what has got us here is Rich and I absolutely
• 37:30
  frigging love our team and love that we get to lead them, love
• 37:34
  that they are here to make us stronger.
• 37:37
  And, and ultimately we, we saw that if we did right by them,
• 37:44
  they'll do right by our customer and that will ultimately do
• 37:46
  right by our shareholders. And that that model work for us
• 37:49
  from day one. So it's been, it's been a very
• 37:54
  humbling roller coaster. How about that?
• 37:57
  I want to understand the culture of the company a little bit
• 38:00
  more, right? You, you love working with your
• 38:02
  team. You've mentioned that multiple
• 38:04
  times during our conversation. But you've got this widely
• 38:07
  distributed team, not just like half the teams here, half as in,
• 38:12
  you know, be it not, it's like you're spread across dozens of
• 38:16
  countries. Like, how do you think about, I
• 38:20
  don't know, developing and then maintaining a company culture
• 38:23
  across such a a wide geography and a diverse set of folks?
• 38:28
  So we've always been fully remote since Day 1 and in in in
• 38:33
  to to a crime. I I would even argue maybe too
• 38:36
  far at times, our investors actually told us to open an
• 38:41
  office in Nashville. This was our early stage friends
• 38:44
  and family like just open an office and we push back our P&L
• 38:49
  made the case and, and, and I think the biggest challenge at
• 38:53
  scale is presence. So it's like you don't have that
• 38:56
  physicality, the kind where every person feels heard
• 39:01
  regardless of time zone or title because you're all in an office,
• 39:04
  you're all showing up at the same time and you're roughly
• 39:07
  leaving at the same time too. And, and so the hardest lesson
• 39:11
  that we had to learn was remote parody, OK, concept that we
• 39:15
  created, which was like the moment you create two classes of
• 39:19
  employees, those in the room and those in the in on the screen,
• 39:23
  you have to recalibrate immediately.
• 39:27
  So what I wish I had sort of known sooner is small local
• 39:35
  office for gatherings, not for work.
• 39:40
  It's for each other. So what I meant by that, when
• 39:43
  you have to create parody of like, let's say you 2
• 39:45
  individuals who happen to be at the small office in, in Spain
• 39:50
  and they show up in the conference room and they're on
• 39:52
  screen and you're the only one on the on the on Zoom.
• 39:57
  That doesn't create an equality of that meeting because those
• 40:03
  two walking in the room could be talking about the subject.
• 40:06
  Those two leaving the room could be talking about the subject and
• 40:09
  here you are just turning off your computer and there's
• 40:12
  isolation there. And so we forced everyone back
• 40:15
  to the computer. If you are all not in the same
• 40:17
  place, don't meet in the same room, meet on the same Zoom
• 40:20
  experience. And so we really, really were
• 40:24
  intentful. We had employees who were taking
• 40:27
  a 10 1/2 hour round trip bus ride to meet teammates.
• 40:36
  That's a. Gigantic waste of time.
• 40:38
  Gigantic waste time. So we said the human instinct is
• 40:42
  there but we got to redesign this.
• 40:45
  That's not fair and and so remote done right returns the
• 40:50
  commute to the person, not the company.
• 40:54
  And it only works if you trust your people and, and hire people
• 40:59
  worth trusting. So for us, like one of the, one
• 41:03
  of the, the, the models that I live by is like you have 3
• 41:07
  buckets. You got life, you got work and
• 41:09
  you got health. Health itself, call it that.
• 41:13
  And you get 24 hours a day to align the, the, the marbles in
• 41:18
  each of those buckets. I know people who want to work
• 41:20
  harder and, and spend more time working.
• 41:23
  I know who people, who, I don't know how they do it, but they,
• 41:26
  they live more. And then I know people who don't
• 41:28
  take care of themselves at all. And, and like, that's a choice
• 41:32
  that we have to make, but you get to balance that.
• 41:34
  And what we try to do is give as much time for life and self as
• 41:38
  possible so that they're healthy, happy and hungry every
• 41:41
  time they show up to work every morning.
• 41:44
  So I myself have managed remote teams for years.
• 41:47
  And, you know, it's a blessing most of the time I get access to
• 41:51
  some really great folks that, you know, I wouldn't have
• 41:54
  otherwise. But it also does raise questions
• 41:57
  of, is that person really being as efficient as they could be?
• 42:00
  Are they really getting stuff done?
• 42:03
  Like not everybody has an easily measurable output.
• 42:08
  How do you think about this? Or do you think I'm overthinking
• 42:10
  it? It goes back to that gap that
• 42:20
  that that that bucket, right? You have emotional pair payroll
• 42:27
  when you get an interaction with a employee.
• 42:30
  OK. And what I mean by that is if I
• 42:34
  have an employee who does not want to participate fairly with
• 42:39
  my exchange, they give me their time as a form of equity and I
• 42:45
  give them compensation back for work product.
• 42:49
  And if that exchange ever becomes inequitable, it it ends.
• 42:54
  If they no longer believe that I'm giving them an environment
• 42:57
  that makes them happy, makes them successful, makes them
• 42:59
  compensated fairly, they're going to leave.
• 43:02
  If they're not doing the work product that I need, then I'm
• 43:04
  going to ask them to leave, right?
• 43:06
  And that mutual exchange going back to the three buckets that I
• 43:09
  described earlier is all about emotions, right?
• 43:12
  It's, it's whether or not you're, you're in or out.
• 43:15
  And if I'm in and out and, and I love it's, it's that black and
• 43:19
  white. And so for us, like it's never
• 43:21
  about trust, trusting the team. It's about can we create an
• 43:26
  environment where all the various people manager down peer
• 43:31
  support reinforces what we're trying to do And that gets back
• 43:35
  to that purpose that we're sort of driving for.
• 43:37
  Do I believe that we we probably have individuals who are
• 43:41
  underperforming? Sure, at any given time I
• 43:43
  underperform. It's it's human nature.
• 43:45
  You got good days, you got bad days.
• 43:48
  But overall, this company screams in productivity and if
• 43:53
  anything, we can do more in productivity with with tools.
• 43:58
  What we talked about is not how do we get rid of humans, it's
• 44:01
  how do we amplify humans always. And, and, and in a world where
• 44:06
  you're seeing big, massive, you know, riffs going around like it
• 44:10
  gets every operator to think, wow, Claude, code can make an
• 44:14
  engineer five times more productive.
• 44:16
  Do I need as many engineers? Do I need as many support
• 44:20
  people? Do I need as many salespeople
• 44:22
  and so on. And so we, we run, we run
• 44:24
  formulas around that exchange. Do we get the right, are we
• 44:28
  getting the right output? And it becomes a mathematical
• 44:31
  decision for us with a very heavy personal connection there
• 44:36
  as well. But I've done, I had to make 2
• 44:38
  riffs in, in this company. They're not easy.
• 44:40
  They're the hardest decisions I've ever made in my life.
• 44:43
  But I work for this business, I'm a shareholder of this
• 44:46
  business, and I'm the fiduciary of this business.
• 44:48
  And so I have to put, you know, I have to put a different hat on
• 44:51
  it occasionally. When you say 2 riffs, what do
• 44:53
  you mean by that? We've had two reductions in
• 44:56
  force over time depending on the moments in, in history, whether
• 45:00
  it was driven by behaviors in the macro stuff that I can't
• 45:04
  control. I'm proud of those moments.
• 45:07
  But when you know, Block and Jack Dorsey cut 40% of their
• 45:11
  team or Oracle starts their ribs or Amazon or Facebook or
• 45:14
  whatever. I mean, these are these are
• 45:17
  organizations looking at the bottom 10% and saying bottom 10%
• 45:21
  has to go right or bottom 20% has to go in.
• 45:24
  And I think they're looking at systems to try to determine
• 45:27
  output. It's not a fun.
• 45:28
  This is the this is the least favorable moments of of running
• 45:32
  a business, but it is a business at at the end of the day.
• 45:35
  Yeah, there's two things that are sort of butting heads there,
• 45:38
  right? You love your team.
• 45:39
  You love leading the team and building this with your team.
• 45:43
  And then you're also talking about, you know, hey, there are
• 45:46
  opportunities, communities for us to make ourselves more
• 45:48
  productive, more efficient, more cost efficient, right?
• 45:52
  And but that's so I'm gonna mix my metaphors.
• 45:56
  You got things, bounce it. But you've also got this tug of
• 45:58
  war that's going on between the two sides.
• 46:00
  Totally. And, and I, I, I always go back
• 46:06
  to my fall back statement, which is it's my job to create
• 46:10
  environments for everyone to be successful in.
• 46:13
  It's their jobs to take those environments and make it
• 46:16
  successful for their peers. And if there is too much blow or
• 46:20
  too much noise or too much, we call them sea anchoring where
• 46:26
  something's dragging along and holding us back.
• 46:28
  Like I have to fix the environment, have to do that on
• 46:31
  behalf of the organization. And, and those are, those are
• 46:35
  moments. They're moments.
• 46:38
  Anthony, you'll, you'll appreciate this as a founder.
• 46:40
  At one point in time, we were, this was many, many, many, many,
• 46:45
  many years back. I actually don't even remember
• 46:48
  when it was, but like 5 plus years back we were re
• 46:53
  architecting some of our main systems and we were dealing with
• 46:57
  a little bit of availability issue in in a reliability of our
• 47:00
  application. We're just completely rebuilding
• 47:03
  plumbing and upgrading systems and whatnot.
• 47:06
  And we had like 3 weeks of just a little bit too much downtime.
• 47:11
  It was it was bad. And one of them happened on
• 47:14
  Christmas morning. No joke.
• 47:17
  OK. I remember getting the phone
• 47:18
  call 5:00 AM and the next week we all happen to have an all
• 47:23
  hands. And we started talking about
• 47:26
  what is these outages mean in like perspective of the world.
• 47:31
  And we framed it like firefighters.
• 47:33
  And I didn't know this, but firefighters train every single
• 47:35
  day. But in a course of the year, an
• 47:38
  average firefighting team only puts out 16 fires a year.
• 47:43
  So the rest of the year they're disciplined around what are we
• 47:47
  going to do when we get our moment.
• 47:49
  And I guarantee when that bell rigs, they're fired up, they're
• 47:52
  practice, they're trained and they're they have an execution
• 47:55
  plan. And so when we started putting
• 47:57
  that lens against what just happened at the company, I was
• 48:02
  like, guys, these outages are like a three out of 10 in terms
• 48:05
  of a blip, Adam dying in a bus, bus like a bus and a car
• 48:12
  accident, get hit by a bus. It's like a 5 rich 5.
• 48:15
  Like Amazon going offline and taking all the world systems
• 48:20
  offline for a day. Yeah, that's like a nine that
• 48:23
  that has serious economic impact.
• 48:26
  But like these little moments, we need to just start flipping
• 48:30
  the lens and approaching it as if we are trained, disciplined
• 48:33
  and ready to help our help our customers.
• 48:36
  And so we just we shifted mentality always around that
• 48:39
  environment. If your environments are there
• 48:41
  to be successful, we're good. We got this in good, bad and
• 48:44
  ugly. And you know, COVID hit cloud
• 48:47
  Nets. We lost 35% of our revenue in
• 48:50
  three weeks. By the end of the year, we had
• 48:54
  already pivoted and we grew 13%. That was astonishing when you
• 48:59
  couldn't stay in a hotel anymore, right?
• 49:01
  What was the pivot? It was a, it wasn't a pivot,
• 49:04
  actually. We just listened to our guests.
• 49:07
  We listened to the guests, we listened to our hotels and we
• 49:09
  figured out how to serve humans in hospitality in that moment.
• 49:14
  And we did some of our best work.
• 49:15
  And that was our, it was a catalyst for one of the
• 49:17
  catalysts for the business. So was it just that the hotels
• 49:21
  were coming back online towards the end of the year and that
• 49:23
  boosted the revenue again or were you guys introducing new
• 49:26
  services? Your new services, it was, we
• 49:29
  kept building. It was hotels were like, well, I
• 49:32
  have a lot of free time on my hands all of a sudden, like I'm
• 49:35
  gonna revisit all of my systems and, and we gained a lot of
• 49:38
  customers at the end of it. The the proudest moment there
• 49:43
  was hospitality helps. We launched A nonprofit.
• 49:46
  We put 55,000 frontline workers in safe rooms away from their
• 49:53
  families because at that early days of COVID, you didn't know
• 49:56
  if you could go home. You didn't know if you could
• 49:58
  take off all your gear as a police officer, a firefighter,
• 50:01
  an EMS or whatever, a doctor in like go sleep in the bed next to
• 50:05
  your loved ones So they would isolate.
• 50:07
  These doctors would sleep in hotels and these hotels had no
• 50:11
  way of connecting. So we worked with Amazon, we
• 50:13
  worked with States, and we put 55,000 frontline workers into
• 50:17
  hotel rooms and that was a an amazing, amazing moment for our
• 50:22
  company. So cool Adam, what's 1 of the
• 50:25
  hardest things you've ever had to overcome and what did going
• 50:28
  through that teach you so 2? Things one is I grew up with a
• 50:35
  father who was deaf in one year, OK, and I would always have to
• 50:41
  sit on his right side to, to to enable conversations and, and
• 50:46
  sometimes I saw that as awkward as as weird, as strange.
• 50:50
  And then at the age of 12, I was diagnosed with a learning
• 50:53
  disabled. I was a neurodivergent and it
• 50:57
  was a really friendly reminder that deficiencies also become
• 51:02
  skills. So my father being deaf turned
• 51:05
  out and took a career in hearing.
• 51:08
  He's now one of the world's leading experts in hearing and
• 51:11
  he's a surgeon fix his ears all the time.
• 51:15
  He taught me that those skills are overcomeable.
• 51:18
  And are those those deficiencies are overcomeable if you hard
• 51:20
  work and grit. And so for my life, my early
• 51:25
  years, I had to retrain how I learned and I had to work extra
• 51:29
  hard at every subject that I needed to absorb because my
• 51:32
  brain wouldn't just connect the dots like like a normal brain
• 51:36
  would or neurotypical brain would.
• 51:38
  And so over time, it became this master class in like brain
• 51:45
  engineering. And by the time I was in
• 51:47
  college, I had photographic memory.
• 51:50
  I could, I could see things and dots and, and connect the dots
• 51:54
  in, in analytical ways, which is why I love finance.
• 51:57
  But I never lost that you're going to have to work harder.
• 52:02
  And so for me, it was a a the way my brain works taught me how
• 52:07
  to work harder to never back down, to run through walls for
• 52:11
  my team. And then all stem from my dad
• 52:14
  and, and watching him and hearing his stories in like
• 52:17
  going through, which was probably a very hard up up
• 52:22
  upbringing for himself in a time that he didn't have all the
• 52:25
  skills. Now, what's crazy is to, to
• 52:28
  bring this full circle. He could have fixed his issue as
• 52:31
  a surgeon today when he was 16 and had sudden hearing loss.
• 52:36
  So, you know, I, I love that moment because my son has the
• 52:42
  same sort of learning behavior that I do.
• 52:45
  I do. And in like seeing him navigate
• 52:48
  it, it, it is almost like full circle for me because I can kind
• 52:52
  of walk him through and coach him and, and say, like, bud, you
• 52:55
  got the same memory as me. We just have to train you how to
• 52:58
  use it. And, and that, and that's
• 53:00
  something where my, my team, I'm sure I, I probably drive them
• 53:03
  crazy from time to time because my, my brain bounces everywhere
• 53:08
  as part of its process. But that was, that was, that was
• 53:10
  my moment. And, and God, it was a, it was a
• 53:13
  very hard one when you're 12 years old.
• 53:17
  You know, and it's interesting that you got the diagnosis when
• 53:19
  you did, because I talked to a lot of business founders that
• 53:23
  later in life were diagnosed with learning disabilities, A
• 53:27
  dyslexia, severe ADHD. There wasn't a name for it.
• 53:32
  They didn't know when they were younger.
• 53:34
  They just they naturally had to adapt how they move through the
• 53:38
  world in order to be able to to keep up.
• 53:41
  And as they strengthened that exactly like you're describing,
• 53:44
  as they sort of strengthened that coping mechanism, if you
• 53:47
  will, it became more of a superpower for them.
• 53:50
  And so I'm curious, you know, as you who somebody got a younger
• 53:53
  diagnosis, what did that process look like for you?
• 53:57
  How did you retrain your brain and how will you think about
• 54:00
  helping your son do? Yeah, so it's interesting like,
• 54:04
  like there was medicines that you could take that would would
• 54:08
  help you slow your brain synapse down things that that would
• 54:14
  treat ADHD and others. And there was, there was first
• 54:18
  of all, it was so early, it was so new.
• 54:20
  I mean, this was this was Jesus like 30 years ago.
• 54:23
  So like from, from, from my perspective, like what is today
• 54:28
  is very different than what we know or what we knew.
• 54:30
  Then what what I found is I was not an auditory learner.
• 54:37
  I was a visual learner. And that was the first thing
• 54:40
  that I had to do was just take copious amounts of notes.
• 54:42
  I had to write it down to then relearn it.
• 54:45
  So I would make lots of flash cards that do PowerPoints like I
• 54:49
  would. I would just learn, take
• 54:51
  anything I could and like throw it into something that I could
• 54:55
  like actually like look and read and like move my finger across
• 55:00
  it. It's a weird way to learn small
• 55:02
  population, small part of our population learns this way.
• 55:06
  The other thing and it's, it's also why Anthony, I love AI,
• 55:10
  it's because it's so visual interaction, like it's such a
• 55:14
  amazing tool from for the way that I that the way that I work.
• 55:18
  The hardest thing was feeling different and, and, and
• 55:23
  overcoming like societal pressure to fit in to to know
• 55:30
  that those coping mechanisms didn't look the same for every
• 55:36
  single one. So for example, like I'm born
• 55:38
  ambidextrous, I'm left-handed natural, but I learned to write
• 55:43
  and throw in bat in golf and tennis and everything
• 55:47
  right-handed because my dad's right-handed.
• 55:49
  He didn't know how to show me left-handed right, but I'm
• 55:53
  naturally better at left. Like I eat left-handed, I use
• 55:57
  chopsticks left-handed, but I right right-handed.
• 55:59
  My handwriting's horrible for that.
• 56:03
  And so like it would. Have used in the wrong hand.
• 56:05
  I'm using the wrong hand. I'm using the wrong like side of
• 56:08
  my brain in, in certain practices.
• 56:10
  And so like I still right right-handed, but I had to like
• 56:14
  retrain the practice of connecting dots.
• 56:17
  And that's my son's issue. It's called apraxia.
• 56:19
  It's like you have to like retrain the, the, the nerve
• 56:23
  pathways and once you establish them, they're there.
• 56:27
  But for kids and for me, if you learn them the wrong way, you're
• 56:31
  never breaking them. It is like a routine that is
• 56:34
  like in concrete. So you have to like break that
• 56:37
  down. I learned that so that we now,
• 56:39
  we now apply that in in a similar manner.
• 56:42
  But like that's where dyslexia comes from and ADHD.
• 56:46
  And so like all of those same patterns happen, even autism,
• 56:50
  for example, they all share very comments or neurotypical or
• 56:54
  neurodivergent sort of methods. I'm fascinated with the brain
• 56:58
  synapses. I now like look at neurotropics
• 57:01
  and things like that on like how to biohack myself to just bring
• 57:05
  a sense of calm. It's like I will work 24/7.
• 57:08
  No one will get me to stop unless like I physically come
• 57:11
  down. I have to like emotionally come
• 57:14
  down and like it's typically my wife or kids go like, hey dad,
• 57:17
  come do something with me because otherwise I'm just a
• 57:20
  tinker. My brain is running 24/7.
• 57:23
  So look, I, I, I, that wouldn't change anything.
• 57:27
  I love it. I love it about myself.
• 57:29
  But it took 44 years to get there.
• 57:32
  But what? What does that process look
• 57:34
  like? Like give us a specific example
• 57:36
  of a training that you did or that you will encourage your son
• 57:39
  to do as he gets. Older, yeah.
• 57:40
  So first of all, physic, physicality, you, you, you need
• 57:43
  to keep yourself in shape, brain and and body.
• 57:47
  So we do a lot of physical exercise.
• 57:50
  We do a lot of sort of like things that are would be very
• 57:54
  obvious, like grabbing a ball, dropping a ball and then being
• 57:58
  able to go like this and rotate your hands or throwing it
• 58:01
  against and catching across the midline.
• 58:03
  So a lot of midline training. I do it still today.
• 58:07
  I do jujitsu. I love it because it's a mental.
• 58:11
  The mental strategies, they're just as much as the physicality.
• 58:14
  So trying to connect the mental decision making with the
• 58:18
  physical decision making is, is something that we really
• 58:22
  instill. I do it every day with my child
• 58:27
  and, and, and it even led me to to build an app for my child to
• 58:32
  help me do this right. So for, for him, I didn't have
• 58:36
  like for him. I can, I know this, I didn't
• 58:39
  have any of that. So it took me doing my own
• 58:43
  research and having access to incredible medical medical
• 58:47
  practitioners because of my father's connections at the
• 58:50
  hospital and access. But I think the, the, there's so
• 58:55
  much rooted science in my family.
• 58:58
  I, I, I know 6 doctors just in my immediate family, like
• 59:02
  medicine is real and, and science is real until like the
• 59:05
  research has instilled in me. So I'm, I heavily researched my
• 59:10
  whole life. I looked at different things
• 59:12
  that I could take to slow my brain down.
• 59:14
  I didn't like to be like prescription drugs.
• 59:17
  I never liked it. It made me feel different and I
• 59:19
  lost sleep. So I had to create a routine.
• 59:21
  I had to create balance and, and I'm religious about it, like
• 59:26
  religious about it, but it also means I can't do certain things.
• 59:30
  I can't get into traps. Like I've never done drugs in my
• 59:34
  life because I'm too afraid my brain will wire to liking that.
• 59:38
  And and so I have to do other things and to to create that, to
• 59:44
  create those that that good feelings in, in, in, in, in some
• 59:47
  more ways. But yeah, man, it's, it's wild.
• 59:49
  Like the brain is a computer. It's so fun to to play with.
• 59:54
  So what's the future of cloud bets look like?
• 59:57
  Where you guys? Going yeah, you know, look, I,
• 1:00:01
  I, I feel like. One year from now, all of that
• 1:00:11
  science and all that math and all that decision making that we
• 1:00:16
  are, we are having conversations with about where hospitality
• 1:00:20
  goes in the age of AI, in the age of macro friction with
• 1:00:27
  things that are going on politically, life looks
• 1:00:32
  different for all of us. And, and that's exciting and
• 1:00:35
  terrifying. And, and when we we listen to
• 1:00:39
  the expert researchers and AI, some of which have recently rage
• 1:00:44
  quitted and and have our leading lives of poetry, a little scary
• 1:00:49
  to, you know, others saying like we need to fall off cliffs.
• 1:00:52
  We need a better understanding. We need this system to train
• 1:00:55
  systems and like we are very early in the day, like we could
• 1:00:59
  create a superior being here scary.
• 1:01:02
  We could end society maybe scary or we could better off every
• 1:01:08
  single human being on this planet because of this product
• 1:01:12
  and actually allow individuals to live life till it's fullest.
• 1:01:15
  Like I wouldn't care if any of our adversaries cured cancer.
• 1:01:20
  I'd be the first in line if I had cancer to want to have
• 1:01:23
  access to that. So if we as Americans create
• 1:01:27
  some of the service, we should give it to the world.
• 1:01:29
  And if the Chinese or the Iranians or the North Koreans or
• 1:01:34
  whoever create those types of advances that make humans live
• 1:01:41
  longer, live happier, less pollutants, more food access,
• 1:01:46
  better environment, whatever it is, we need to harness that
• 1:01:50
  together. And so I'm I'm holding out.
• 1:01:53
  I'm holding out for the alien invasion that like brings us all
• 1:01:56
  together so that we can finally get this planet on on the right
• 1:02:00
  path. But cloud beds is going to
• 1:02:02
  unlock all of this technology that is at our finger fingertips
• 1:02:07
  before anyone other before any other brand.
• 1:02:09
  And we are going to deliver solutions for our hoteliers that
• 1:02:13
  make their life easier and ultimately drive better value
• 1:02:17
  for the guest. And I'm a traveler.
• 1:02:19
  I've been to 62 countries in the world.
• 1:02:21
  I want that. And every day I talk to
• 1:02:24
  hoteliers who want that too, on behalf of me as the traveler.
• 1:02:27
  And so we're going to put 750 people in a room and we're going
• 1:02:31
  to drive for that every single day.
• 1:02:33
  And that's the celebration I want most.
• 1:02:36
  So can you give us a a little peek behind the curtain?
• 1:02:38
  What's a specific example of a new feature function benefit
• 1:02:43
  that's coming from Cloudbeds? What are we going to see in the
• 1:02:48
  next 12 months? There's so many I'm I'm trying
• 1:03:03
  to choose very carefully. I I, I, you threw me at AI
• 1:03:08
  didn't think you'd ask me this question one, but two, the
• 1:03:13
  conversation is gone in so many different directions.
• 1:03:15
  I feel like I need to give you a really big win here.
• 1:03:19
  But then I'm also trying to be mindful of some of the things
• 1:03:21
  that are coming out in in, in what's under embargo.
• 1:03:25
  I how about this. We have so much tack coming in
• 1:03:33
  the world of distributing rooms online that we want to help our
• 1:03:39
  independent hoteliers win some of that back more efficiently.
• 1:03:43
  OK, and most consumers don't know this, but the average cost
• 1:03:48
  of a hotel to a hotelier to acquire you as a guest and
• 1:03:53
  support you is about 40% of their revenue.
• 1:03:56
  So if you pay them $100.40 dollars is going into cost and
• 1:03:59
  support in in super majority of that cost and support is going
• 1:04:04
  to a third party. So when you book through
• 1:04:05
  booking.com, you charge anywhere from 18 to 25% in Commission to
• 1:04:11
  that hotel. OK OTA spent $20 billion a year
• 1:04:16
  trying to get you Anthony to go to their websites to book on
• 1:04:20
  behalf of a hotelier. And, and I want to take some of
• 1:04:24
  that back now. I want to shift that back to
• 1:04:27
  educate you as the consumer to say, hey, don't go through them.
• 1:04:30
  You can do that. You can use those for resource
• 1:04:32
  or whatever you want to do. But I need you.
• 1:04:36
  I need you to go direct as often as possible.
• 1:04:40
  And we have a bunch of tools in tech that are going to unlock
• 1:04:43
  ways that guests can find you more efficiently as a hotelier.
• 1:04:48
  And, and it won't be one, it will be many.
• 1:04:51
  And, and I think what, what's going to be beautiful part of
• 1:04:53
  that is it's a real big number and, and, and we, we can
• 1:04:58
  absolutely connect the dots. And the best part about that is
• 1:05:01
  if we connect the dots and we bring the intelligence systems
• 1:05:05
  together, you as the consumer will actually spend more at the
• 1:05:09
  hotel here at the hotel and get better experiences for that.
• 1:05:15
  Because I'll begin to able to personalize down to what you and
• 1:05:19
  your family or your business travel needs are.
• 1:05:24
  And I cannot wait for that moment for this industry.
• 1:05:26
  It's very human. It's very human.
• 1:05:29
  Well, exciting. We're going to have to have you
• 1:05:31
  back on to tell us more details about that as it rolls out.
• 1:05:35
  But last question for you, And before I ask, I want to do 3
• 1:05:38
  quick things for the audience. First of all, to get in touch
• 1:05:43
  with Cloud Beds or website very easy to remember cloudbeds.com,
• 1:05:47
  we'll have it in the show notes, but cloudbeds.com, you can learn
• 1:05:50
  more about what they're doing. If you're enjoying the show
• 1:05:53
  today, please take a moment to subscribe wherever you're
• 1:05:55
  listening. It sends a signal that also
• 1:05:57
  helps others discover our podcast.
• 1:06:00
  So thank you for taking a quick moment to do that right now.
• 1:06:03
  And as a reminder, you can get your hospitality employees
• 1:06:07
  access to therapist doctors and prescription meds.
• 1:06:09
  That is paradoxical as it seems actually increases your
• 1:06:13
  company's net profits, real gains that can change how a
• 1:06:16
  business is valued. So contact us today at
• 1:06:19
  adbackbenefits.com. So last question for you, Adam,
• 1:06:23
  and you kind of hinted at this, but I'll open the door in case
• 1:06:26
  there's anything else you want to throw in there.
• 1:06:29
  A year from now, what's 1 specific thing that you would
• 1:06:31
  hope to be celebrating? So it's probably two things.
• 1:06:54
  One that cloud beds is synonymous with being the
• 1:07:01
  unified hotel management layer, as is Kleenex is the way we
• 1:07:07
  think about tissue. OK, not just the best, but the
• 1:07:12
  one that everyone goes to define to ultimately define the
• 1:07:15
  category, right. And then personally, that is all
• 1:07:21
  750 people that are in in rooms with me occasionally.
• 1:07:27
  That's what our team asked for more than anything.
• 1:07:30
  And that's the celebration, right?
• 1:07:32
  So like when, when you are, when you are approaching leading a
• 1:07:39
  large bucket of humans, it's, it goes back to those milestone
• 1:07:44
  milestones that we talked about earlier, But it's been shifting
• 1:07:48
  that to how milestones mold into purpose.
• 1:07:55
  And, and so we have a, we have a belief system that there is a no
• 1:07:59
  exit strategy here, right? Just more to build.
• 1:08:03
  And so we always tell our team that, hey, this is just another
• 1:08:07
  chapter and we're going to keep writing chapters until we can't
• 1:08:10
  write any more chapters. And there is no exit here.
• 1:08:14
  It's just build more and let's keep going.
• 1:08:16
  And that's purpose. And that gets me up every single
• 1:08:19
  day. And to be honest with you, 14
• 1:08:21
  years in, I have never had more fun at COVID.
• 1:08:26
  Adam Harris from Cloudbeds, I want to be the first to thank
• 1:08:29
  you for sharing both your time and your story with us today.
• 1:08:32
  Really appreciate you being here.
• 1:08:34
  It's been fun. Thanks for the great questions.
• 1:08:37
  Folks, that's a wrap on another episode of the Inspired Stories
• 1:08:40
  podcast. Thanks for learning with us.
• 1:08:42
  And if one thing stood out, put that into action today.