Jetsetter uses Kapow Software Robots to gather competitive data from other luxury travel sites to stay ahead. A vice president explains that as competition grew, they needed to monitor deals, prices, and sales across multiple competitors. Kapow's robots allowed them to do this with minimal IT resources. Access to this mission-critical competitor data helped them strategize pricing and marketing to maintain an advantage.

1. Kapow Software Robots Help Luxury Travel Site Jetsetter
Track and Stay Ahead of Competitors
Transcript of a BriefingsDirect podcast on how one travel company uses synthetic APIs to gather
mission-critical data from a variety of sources.
Listen to the podcast. Find it on iTunes. Sponsor: Kapow Technologies
Dana Gardner: Hello, and welcome to a special BriefingsDirect panel discussion coming to you
from the 2013 Kapow.wow user conference in Redwood Shores, California.
We'll hear how innovative companies are dodging data complexity through the
use of Synthetic APIs. We'll see how -- from across many different industries
and regions of the globe -- inventive companies are able to get the best
information delivered to those who can act on it -- with speed, and at massive
scale.
I'm Dana Gardner, Principal Analyst at Interarbor Solutions, and I'll be your
moderator as our panel explains how they improved data-use benefits from novel information
integration to gain business success. [Kapow Technologies is a sponsor of BriefingsDirect
podcasts.]
Our next innovator interview examines the improved data-use benefits at Jetsetter in New York.
Here to explain how improved information integration and delivery can be made into business
success, we're joined by Shaun Stewart, vice president of sales and operations at Jetsetter. Glad
to have you with us.
Shaun Stewart: Thanks for having me.
Gardner: Tell us a little bit about the organization you're involved with. I think we need to
know that, before we can understand why data is so important to you.
Stewart: Jetsetter started in the fourth quarter of 2009. We started off as a flash-sale site,
actually, jumping into the similar business that our major investor, the Gilt
Groupe, had gotten into. Doing flash sales or short-term sales of luxury high-end
apparel and home goods.
What we ended up pivoting into, similar to their concept, was a flash-sale site
focused on luxury travel. The major differentiators were a couple pieces. One
was obviously price. The flash sale meant that you had a short-term period to
buy a hotel in a specific region. And you got it at a great discount. A non-
refundable price point that you couldn't get anywhere else.
But the flip side of it was that we curated the product. We picked every hotel that we wanted. We
had riders go to stay and experience the hotels to make sure the product we're actually

2. introducing our members to was of a certain quality. And the last piece was an editorial approach
that was different from what the online travel world had been doing in the past. We invested a lot
of money into the quality of imagery, the quality of the content, the reviews we got back.
We used freelance writers from the quality levels of Condé Nast and Travel and Leisure to give
us fantastic reviews of these products that made people experience Jetsetter like a magazine,
rather than just another online travel agency that could exist anywhere else.
Gardner: And I take it that this was successful quickly.
Lot of competition
Stewart: Yes. In our first financial year, we did $18 million in gross bookings. That's starting
from scratch. We quickly saw a lot of competition come into the
space. So the success was that we saw a great return from the
customers we had, as well as a great reception from the partners.
We provided luxury hotels with a method of moving distressed
inventory that they were comfortable with to an audience they were
comfortable approaching. The flip side was that it got pretty competitive pretty quickly. There
were a lot of new entrants into the space in in 2010 and 2011, which is where Kapow came into
place.
Gardner: So you found yourself in the enviable position of being highly imitated. And that
presented a data challenge to you, because you're in a marketplace, and it's important to know
what the others are charging. What did you do to solve that problem?
Stewart: Our first piece was to go out to the membership and see if they were becoming
members of other competitive sites and whether it mattered. Did it actually matter if other sites
were promoting similar products at better prices, or anything along those lines? We quickly
found the majority of our members were essentially dabbling in all of these different new
startups in the flash-sale space at that time.
There was a lot of buzz around the concept. People were trying to investigate which ones were of
worth. It quickly became apparent that it was very important for us to know exactly what was
being sold and when it was being sold by all of these different competitors out there. At that
time, there were only 20 of us. So it was a small enterprise in the early days.
The second piece was that startups were popping up every week. So you couldn't exactly find a
solution that just monitored one website, because you had to build to a new competitor every two
or three weeks. We brought on Kapow Software to for a range of reasons, but mainly to monitor
every single offer that existed on any other website. For any other competitor that popped up, we
would build a bot and track everything they offered.

3. We tracked from the deal itself, to how long the sale was, to the price points by day. So if we ran
the same hotel two weeks later for the Fourth of July, we knew that we had to price it at $150
rather than $160 to remain competitive. The other great thing back then was the flash-sale sites
kept tickers of how many units were sold of each of the sales they were running -- a lot of them
still do, but not as many.
So we were also able to track what kind of production they were providing to see who was a
major competitor in the space and who was providing a stronger return on investment (ROI) to
the hotels than we were. So it gave us a lot of intelligence to figure out how to merchandise,
when to price things at certain levels and when not to, and also to target our strategy on who the
competitors were in the space that were really going to make it through the next couple of years.
Gardner: So this really became a mission-critical type of data collection and analysis.
Stewart: Obviously, hindsight is 20-20, but looking back, it certainly was a key piece to how we
were able to fend off and move out a lot of the competition -- just being more strategic about
every single thing we sold with an insight to everything they were doing. As we did interact with
the competition out there, they certainly didn't have the same level of insight into what their
competitors, including us, were doing in the space.
More innovative
So it was something that was slightly more innovative. It provided us with a leg up in an
industry where we had access to all of their price points, how they were strategizing, and what
hotels and which regions they were promoting. That gave us a pretty strong advantage.
Gardner: Now, given that you're a fairly limited-sized organization, particularly with a limited
IT budget and staff, how was it that you were able to so quickly get that advantage without a big
IT budget?
Stewart: I can't take any of that credit. I didn't have the insight to build robots through Kapow.
None of us in the in the company, at that point, had ever heard of them, to be honest, or had
touched any of the interfaces or tried actually building these pieces.
The amazing thing, which is a credit to Kapow, is that we brought in people straight out of
school. Most of our employees were out of NYU or different colleges around the New York area.
And they were young enough where they were able to jump into this software and immediately
start managing it.
We have a single person who manages our competitive tracking. He started with us as an intern
out of a local college in New York and quickly took over, managed, built, and produced all of
these different robots for tracking the competition.

4. Gardner: Aside from that competitive differentiation, have there been other payback benefits
from being able to have the skills and capability of searching out data, perhaps now on the hotels
and even extending the value of this capability?
Stewart: There are two big ones there. In our in our second year of the business, we pivoted. We
actually continued to have the flash sales and continued to offer this distressed platform of
inventory that was on sale, but we moved into the full-price arena.
So we essentially got into the same game as a Travelocity, Orbitz, or Expedia. We started having
a specific section of our product that was on sale, but the rest of the stuff was in line with the
prices you would pay with hotels directly. When you're starting to pivot into a whole new arena
like that, you need to capture a whole bunch of data about what's going to make you competitive
in that industry.
And so the game changed. We essentially had to look at if we're going to go into the full-price
arena, what is the competition out there? What's their product offering? How much depth do they
have in certain markets? That's where we were able to quickly pivot as well with Kapow
technology, which was to start looking at this new set of competition and what we needed to do
to compete with that arena. That was certainly one of the one of the major pieces.
The second piece was just the flexibility of being able to jump on new competitors as they came
out, including when they popped into other businesses that weren't travel specific. We had been
following all the travel startups. Then folks like RueLaLa or Ideeli, who had traditionally been
focused on apparel had suddenly jumped into travel as well. It allowed us to quickly keep an eye
on those guys as well.
Gardner: Any lessons learned in the use of this technology and approach that you might impart
to others who are also in in the time-sensitive, dynamic information needs business?
Flexibility is key
Stewart: We obviously shopped around a bunch of different competitive products in this area,
and they all had their own advantages and disadvantages. Among the big ones that won out for
us, which I would push people to consider when they're looking at options out there, one is
flexibility, which was key. You don't know today what your competitive landscape is going to
look like in 24 months. Having a product that's flexible and allows you to move into those
different arenas as they pop up was key.
The second piece is, depending on the size of your organization, is whether you have the
sophistication to use more complex tools, or whether you need something which is quite user
friendly. There are very different solutions, depending on which of those you need. For us, we
needed something that was pretty user friendly and able to be used by a team of folks who
traditionally didn't come from that background. Those are probably the two major lessons that
we learned through that experience.

5. Gardner: It sounds like a very interesting use case. I'm also interested in deployment models. As
more organizations and individuals are trying to be in the mobile space, recognizing that people
are spending more time there, have you had to adjust to that in order to deliver your value out to
the mobile devices? And from the data-delivery perspective, would moving to a cloud model
with Kapow, for example, make some difference in how you reach those mobile devices?
Stewart: For the cloud side, it's probably not the area we've been as focused on. The piece that's
changing for us is that this whole world of competitive landscape is moving onto the mobile
platform. It's a completely different price point now. There are there are a range of competitors
who now send different prices to the mobile devices for last-minute stays, versus what they're
showing on direct web.
The difficulty now is looking for the ability to track what's happening on apps, as well as mobile
web, as well as the desktop web that people are visiting. That's been the key part for us for
mobile. Mobile for us has always been about 15 or 16 percent of our business.
Most of that is through iPad, but our competitive intelligence is mainly focused on what's
available on the web and not necessarily what's on the iPad, iPhone, or any other mobile devices.
Most of the competitors that have been built out of the last three or four years have the ability to
send different offers and different price points to devices.
Traditionally, your travel agent had one rate. Or if you went to Expedia, there was one rate there
and that was the main the main price point available. What we find now is that it may be $100 on
the desktop and $90 on the iPhone. And our ability to know about that is going to be even more
key in the next generation of competitors.
Gardner: And how is Kapow relevant to that?
Stewart: They've certainly helped us with the mobile web part, building robots that can track
what's happening on the mobile website. Now, we're actually talking to them about how to solve
the solution for the app side, what to do against apps that are focused just as a mobile device app,
and how to track their offerings and make sure we're competitive with those as well.
Gardner: I’m afraid we’ll have to leave it there. We've been talking about how Jetsetter in New
York has improved information integration and delivery using Kapow technology and a
Synthetic APIs approach to gain significant business benefits.
Please join me in thanking our guest, Shaun Stewart, Vice President of Sales and Operations at
Jetsetter. Thanks for being on BriefingsDirect.
And thanks to our audience for joining this special discussion, coming to you from the 2013
Kapow.wow user conference in Redwood Shores, California.

6. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host throughout this series of
Kapow Software-sponsored BriefingsDirect discussions. Thanks for listening, and come back
next time.
Listen to the podcast. Find it on iTunes. Sponsor: Kapow Technologies
Transcript of a BriefingsDirect podcast on how one travel company uses synthetic APIs to gather
mission-critical data from a variety of sources.Copyright Interarbor Solutions, LLC, 2005-2013.
All rights reserved.
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