I overhear my colleagues in the hallway say “I am planning to travel this weekend to Goa; Hotel recommendation anyone?” Despite, dime a dozen FREE online travel sites and recommendation platforms available out there in the Market, I never ceased to wonder why?
Until, one fine day when I was tasked to own a Hotel Recommendation platform product. There are user generated reviews everywhere out of which some are paid and rest genuine…thus the confusion “how do I make the right choice? A choice that’s tailor made for me?”
How different it is asking a colleague/friend/acquaintance for Hotel Recommendation Vs Booking Site Vs A programmed engine?
There is quite a difference considering …
All these questions lead me to believe that TRUST is the key factor, of course COST being a volatile player or influencer and the complexity of building a Hotel Recommendation engine without Room Night cost information, it doesn’t get any easier, challenging and interesting problem to have, I suppose.
REAL TIME Vs QUALITY REVIEWS:
It’s a noisy world out there. The channels we use to discover the stories we’re interested in — Twitter, Facebook, and a slew of news readers, etc. – are dictated by page views and favor real-time, meaning great content has a relatively short lifespan. Thus, what’s good for a Hotel Recommendation is constantly pushed down by what’s simply new. What we’re missing is a channel where great content doesn’t have an expiration date. One that catches the best stories before they fly on by.
CLARITY OF INFORMATION:
When we seek recommendation, we are seeking specifics, depending on the clarity of the trip or destination and should the recommender be a good story teller, Your search ends there!?!
We wanted our product to be a catalyst of change; in providing personal & contextual information based on the historic contents from millions of reviews.
A Hotel Recommendation engine delivering contextual, personalized recommendations and insights based on the historical sentiments and matching algorithm for a specific Persona be it Business, Family, Couple, Solo, Elderly, Friends or Homosexual from user generated global reviews, how about that?
Today travelers must go through multiple sources such as customer reviews, images/videos, location, amenities, social media interactions for the best Hotel Recommendation in any given destination matching his/her criteria not to mention the blind date with room night, cost.
THE BIRTH OF KePSLA TRAVEL RECOMMENDATION (TRECS)
Ergo, we set out to build A discovery platform, that personalizes hotel recommendation and boost customer decisions processes through our integrated Travel recommendation platform.
Big data of customer reviews were aggregated globally and processed by the platform to generate scores and values for a very large and diverse set of hospitality parameters that act as promoters or detractors for recommendations and Persona matching index.
We started with a base bucket of Departments & Categories mapped to Important Hotel Attributes of different Hotel Products/Services representing the major Hotel industry sectors, to which a business belongs for e.g. Amenities & Décor, Service & Value, Food & Beverages, Vibe & Recreation, Stay, Comfort, Safety & Security & etc.
A lot of research time was spent around buying & selling habits, necessities & luxury, need to travel & love to travel kinds of Persona’s behind the base bucket of this taxonomy. Bonus, all this and more are built to be client configurable whilst the sentiment & polarity are analyzed and calculated by our cool in-house algorithm!
In short, we’ve built Hotel Recommendation Platform to make it even easier for you to catch the content you care about and in turn assisting Hotels to promote their uniqueness, services or offerings.
Empowering online shopping experience driven by customer satisfaction metrics, context & expectations and that we call TRECS (Travel Recommendation Engine)