Identified as one of the major trends impacting the travel industry, among many other industries, big data is already playing an important role in how travel organizations are shifting their efforts. To read the original article on my blog: http://fredericgonzalo.com/en/2013/07/07/big-data-in-tourism-hospitality-4-key-components/

2. 
Identified as one of the major
trends impacting the travel
industry, among many other
industries, big data is already
playing an important role in how
travel organizations are shifting
their efforts. Many people think
it’s a “technology thing” when
it’s really about business
processes and intelligence to
better deliver the customer
promise. What is big data all
about and how can we better
understand the phenomenon? A
easy way to memorize it is to
consider the four Vs of big data:
Volume, Variety, Velocity, and
Veracity.

3. It boggles the mind to think about how much content
is created on a daily basis, even on an hourly basis.
Better yet, take a look at this infographic that depicts
what takes place every minute on the internet:
With so much information circulating on external
platforms, it becomes difficult to make sense of it all
specially when brands attempt to reconcile this level
of data with their internal data. That is, data provided
through points of sales or traditional channels of
distribution, i.e. call centre, web site, on premises,
newsletters, customers relations, etc. Thus the
challenge here is akin to drinking from the fire hose or,
to put it differently: how does one make sense of the
information, transforming big data into smart data?

5. Big data is not just about volume, though. Another
key component is the variety of data that stems
from all this easily accessible technology, both in
terms of cost and ease-of-use. It’s now estimated
that organizations can count on only 20% of
structured data, against 80% of unstructured
data. Think of structured data as your hotel
Property Management System (PMS), your web or
blog’s Content Management System (CMS), or
your Customer Relationship Management (CRM)
system. Ideally, brands already capture loads of
data on customer preferences at various points of
contacts, turning this into customer intelligence to
propel a better experience, research and
develop new or improved products and services.

6. So what’s unstructured data, then? Everything else,
basically. Think of:
 Questions or comments answered on Facebook,
Twitter, Linked, or any other social platform where a
travel brand has a presence.
 User-generated content (UGC) platforms such as
TripAdvisor, Yelp and other sites and forums where
consumers discuss your brand and where your ereputation may be in question.
 Any and all interactions on third-party sites, from tour
operators to inbound receptives to online travel
agencies (OTA) and anyone in between, including
travel agents, offline or online.
 Emails, photos, videos, testimonials exchanged either
directly with the brand or one a shared platform.
 Different devices where customers interact with a
brand: desktop, laptop, mobile, tablet, iPod, etc.,
through a mobile site or a mobile application.

7. Source: Amadeus Report, “At the Big Data Crossroads:
turning towards a smarter travel experience, June 2013.

8. Not only do travel brands have to deal with
enormous quantities of data that are most often
unstructured, a third key component lies in speed
of responsiveness, also referred to as velocity.
How do you send the right offer to the right
person, at the right moment when he or she
arrives at your destination, for example? What if
someones checks-in to your hotel, is disappointed
with the room and decides to tweet about it
rather than call front-desk? This aspect came into
light with the most recent survey conducted by
the Social Habit in the Fall of 2012, finding that
42% of customers active on social media expect
an answer from a brand within the hour!

9. 42% of customers expect answer within the hour. Source: Social Habit

10. A challenge that arises from the velocity consideration is how
travel organizations reorganize their business processes in
order to be as nimble and flexible as can be. In the travel
business, airlines are perhaps the most advanced in this
regard, for example with their dynamic revenue
management, allowing to shift pricing according to complex
algorithms based on real-time inventory and near-real-time
customer online behaviors. From a customer experience
standpoint, how airlines react to incidents such as the
Icelandic volcano or major weather crises is also an excellent
example of how fast information circulates. Case in point:
when American airlines suffered an important glitch this past
April, grounding its entire fleet for many hours, customers took
over to Twitter for information. To a point where information
given via Twitter was faster than gate agents who were not
always kept in the loop, thus creating frustration and a bad
overall customer experience.

11. In terms of business intelligence, many
hoteliers and industry partners can’t rely
anymore on reports provided by their
destination management organizations
(DMO) since it is often a couple of months
old by the time it gets to them. With lastminute bookings becoming the norm,
intelligence therefore requires a near-realtime aspect in order to be useful to the
restaurant owner or hotelier.

12. At the confluence of the three above
considerations comes a final aspect, not
always mentioned when it comes to big
data: veracity. Or truthfulness and
accuracy of data, given the context, the
variety of communications touch points
and the speed at which things happen.
Traditionally, brands would clean up their
databases on a yearly basis, if that often.
This is no longer sufficient.

13. An analysis of how people browse for a
destination online must be taken into
context to understand if there is an
unusual or newsworthy event that may
be influencing the search patterns. Not
doing so might lead marketers to think
their SEM campaign is working well while
results may be completely random and
unrelated.
For other organizations, veracity may be
linked to identifying their best customers,
using traditional methods such as RFM
(recency, frequency, monetary) or BCM
(best customer model), or by continuing
this analysis in the context of big data,
looking at external interactions, in
particular within unstructured data.

14. In its most recent report, At the Big Data Crossroads:
turning towards a smarter travel experience, Amadeus
identifies a series of usages for big data in the travel
industry: revenue management, distribution, travel
management, internal operations, financial
performance and investment management. There are
interesting examples and case studies featuring
Hipmunk, Kayak, Amadeus and Marriott, among others,
helping to better understand how some well-known
companies are embracing these challenges and
incorporating its usages in their business processes.
Is your brand or organization doing something about big
data? Let me know by commenting in the section
below

15. Subscribe to the blog
http://fredericgonzalo.com
Enter your email address to subscribe to this
blog and receive notifications of new posts
by email.