TLabs Showcase on travel startups featuring US-based Guestmob, an opaque hotel booking service using big data and other next-generation technology.
UPDATE: Guestmob has since pivoted to a new concept, called Virgo and profiled by Tnooz in 2014.
Who and what are you (including personnel and backgrounds)?
Guestmob is a next generation opaque hotel booking system that uses big data, social data and predictive analytics to re-invent the model pioneered by Priceline/Hotwire.
Our company was formed over a year ago by Yann Ngongang, CEO (former-CEO, eSmog – Partner, Mercer/Microsoft, Bell Labs,other startups, Stanford MBA); Alan Kaiser, CTO (former Chief Architect, Liberate Technologies, other startups, PhD/CS), Damien Keller, Director Hotel Ops (Dir of Sales, Joie de Vivre group)
What financial support did you have to launch the business?
We raised a seed round last summer from Eric Chen (co-founder Tinyprints, investor Palantir), Fabrice Grinda (CEO, OLX), Jose Marin (Chairman ViajaNet, investor eDreams), Ron Rofe, Vaizra fund (vkonkatke.com/facebook of Russia), Joe Lonsdale (co-founder, Palantir), and many others.
What problem are you trying to solve?
For consumers, we offer a much more flexible opaque booking solution. Guests know exactly what hotels they’re getting, and our bookings are refundable: no secret hotel, no bidding, no gimmick!
Our prices are lower than published rates by up to 50%: we track and show the numbers. For hotels, in addition to helping with yield management/filling empty rooms, we solve a timing problem around discounts.
Describe the business, core products and services?
Guestmob core innovation lies in the concept of hotel collections, coupled with a magic pricing algorithm.
Our team spends hours reviewing & curating hotels into collections of 4-8hotels of the same class/location/ratings – we tend to eliminate 30-50% of hotels based on quality.
Then our pricing engine uses an adaptive algorithm to determine day by day the appropriate discounted price at which we will accept booking and guarantee customers a room at one of the hotels in the collection.
These prices tend to be 20-50% lower than the published prices of any hotel in the collection.
The pricing system anticipates the level of discount we are to get from hotels during our regular mob auctions.
Sometimes, we loose money on these transactions, but we guarantee our guests a booking at one of the hotels in the collection.
We see our company as a pricing technology company, as we’re applying the supply & demand science from airlines to hotels. But we do not sell cheap rooms.
We focus on building quality baskets of hotels and optimize for price within these baskets.
Who are your key customers and users at launch?
At a top level, we are going after hotel shoppers with a little flexibility on hotel choices. We serve value-driven customers, but we remove all the friction points of current opaque sites: non-refundable bookings, secret hotels, last minute mobile only, complex bidding.
We’re still learning exactly who that customer profile is.
But based on our initial launch in San Francisco this past fall, lots of people loved our offerings and they tended to book longer stays, well in advance, and were more methodical about finding discounts because they were booking more room-nights.
Did you have customers validate your idea before investors?
We spent lots of time surveying & talking to prior customers of companies like Hotwire & Priceline, lots of time talking to major hotel managers and investors to also understand how to position ourselves effectively for them.
What is the business AND revenue model, strategy for profitability?
We have a traditional merchant model where our revenue is the delta between the discounted price we get from customers, and the mob price we pay to hotels after auctions.
SWOT analysis – strengths, weaknesses, opportunities and threats?
Strengths:
- Experienced startup guys
- Strong technology
- Disruptive model
Weaknesses:
- Team needs to be rounded up
- Team’s ability to scale fast
- Potential complexity of our system for consumers
Opportunities:
- Big data
- Social data and machine learning
- Consumers becoming savvy
Threats:
- Traditional online travel agencies (OTA) expanding their opaque-type models such as the Expedia-Groupon partnership
Who advised you your idea isn't going to be successful and why didn't you listen to them?Some experienced OTA executives were most skeptical of our model, especially those that fought the battles of the past 10years.
While we have to simplify, simplify, simplify, we stayed the course because our platform brings significant/measurable benefits to consumers, as well as hoteliers.
What is your success metric 12 months from now?
In a year, we will continue to grow rapidly, and will not limit ourselves to the US market.
NB: TLabs Showcase is part of the wider TLabs project from Tnooz.