Working together for customers - 7th March 2018 John Musk Product Director at - ITB Kongress
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Working together for customers
7th March 2018
John Musk Andy Owen Jones
Product Director at CEO at
An award winning pioneer of travel AI
solutions that bring control and increase
revenue.
We profile every individual
and understand what they want
in the context of their
current travel search.
We provide our clients with
the scale, insight and tools
to compete at the highest
level and at the cutting edge
of technology.
Our story
At Travel republic we decided to rebel
“To reject, resist, rise up against one’s government or
rulers”
CONVENTION AND LAZINESS
• Forcing customers to search in a
particular way
• Treating customer generically
• Not providing customers with relevant
products and services throughout their
experience
…… FILTERS.
According to Google…….
‘’69% of leisure
travellers worry that
they’re not finding
the best price or
making the best
decision’’
https://www.thinkwithgoogle.com/articles/micro-moments-travel-customer-journey.html
What are we aiming to be?
Acceleration Bamboozled So much
of customer with choice customer data
expectations and options and a need to
action it
yesterday
Being more relevant to our customers!
Example: Filter usage in 12 months
2.3
43m Filter or
Sort
selections
per visitor
16m >30
options
Relevance VS. Price
We know we can influence product selection with overlays
‘Family Favourite’ etc.
40% of Travel Republic customer sort
by price
We can influence either end of the
price spectrum with basic
merchandising
Yet 70-80% of our customers book 3*
and 4* Hotels.
How do we make it easier for those
Our hypothesis “To drive conversion and loyalty we need to understand the unique needs of every customer in order to offer them relevant products throughout their experience.”
Relevance 1.0
Traditional Volume Based Relevance Sorted Order
OrderTravel Republic’s partner in AI driven personalisation
FINISHED FILES ARE THE RESULT OF YEARS OF SCIENTIFIC STUDY COMBINED WITH THE EXPERIENCE OF
The travel domain is not straight
forward
So we had to develop our own knowledge base and AI approaches
• Data is sparse (1-3 holidays
a year)
• Signals are implicit or
unstructured (why did the
user not book?)
• Everything is depending on
context (because it wasn’t
available anymore)
• Features provide little
! It’s impossible to use the ordinary
approaches like frequency based
collaborative filtering
differentiation (most hotels
have a pool)
• Seasonality and delayedbd4travel in a Nutshell
A comprehensive AI-driven approach
• Easy, legal and secure
integration
• Sophisticated tracking
• AI-based profiling
approaches
• In-depth product profiling
• Specifically geared for
travel
• Constantly learning &
growing
• Probabilistic
> Hotels Knowledge
> User DNAs > Users >
Base Availability Checks > Bookings >
Booking Values > Demand Trends >
• Real-time, for true
Data Quality > …Our profiling approaches are
comprehensive
ML based characterization and abstraction of entities and
relations
User Clusters Hotel/Destination
and Segments Clusters and Segments
User Profiles
(Interest, Hotel/Destination
Intent) Profiles
(Features, Ratings,
….)
Individual Individual
Users Hotels/Destinat
ionsWe create profiles of everyone Unique and detailed real-time profiling
And derive outputs for our clients
We build product sets that bring bland travel websites to life
for each client
bd4recommender
Real-time product recommendations, tailored exactly to
the interest of the individual user.
bd4sort
Search result lists, sorted according to the individual
preferences of the specific user profile.
bd4callcenter
Personal interaction with particular relevant users,
based on current interest & experience.
bd4profiling
Real-time profile of each individual user - including ML
driven predictions on personal interests and intents.We profile everyone on the TR site
For the current trip
Revenue Engage-
“How much
ment
is he “What is he
Intent
willing doing right Targeti
to now?”
ng
“Does he spend?”
want to “What
book would
soon?” catch his
attention?
”
Intere Conversio
st n
“What is
“What did he
importan
book so
t to
far?”
him?”We provide recommendations, sort orders
andAPIs
Via data
for the Travel Republic Team to build onWe provide recommendations, sort orders
andAPIs
Via data
for the Travel Republic Team to build onWe provide recommendations, sort orders
andAPIs
Via data
for the Travel Republic Team to build onbd4travel and Travel Republic – Moving forward What have we learned and how have we worked together?
What went well
4% decrease in customers using a
Hotel filtering vs. our old
ordering
1.5% increase in click
through rate from Hotel
listing
2% improvement in
conversion
Up to 15% improvement in average
booking valueWhat we’ve learned
It doesn’t work as well for all
segments due to fewer choices e.g.
high value customers
Hotel visibility needs to be
tracked
Customers want to
understand why they get
shown specific lists
Replicating cross device is hard!How do we build on what we’ve learned?
TELL THE CUSTOMER WHAT WE THINK WE KNOW ABOUT THEM…
…AND LET THEM MANAGE THEIR PREFERENCES!And we can use the profiles for many
cases evolution in targeted remarketing
Natural
Customer value
Add colour to remarketing lists
High value
• Use any profile characteristic alongside
4 x bid modifier
your existing rules to add new flavours targeted campaigns
to your retargeting
Example use case Medium value
2 x bid modifier
• Use the expected wallet prediction to Assign to all
target high value users with generic campaigns
customised display adverts
• We have seen that CPA can be
Low value / unknown
reduced Don’t target
Optimise your budget by targeting
the most valuable usersWhat’s next?
Google are right – customers can’t be sure they found
the best product for them. We’ve made it hard by
being lazy.
Look at your filter data usage holistically – are you
guiding customers from search to book or letting them
find their own way?
Customer preferences are unique.
Treat them as such, it pays back.
With GDPR on the horizon, we can use what we know
about customers transparently to let customers tellWhat have we achieved?
We have created a new data framework for Travel
Republic
to drive product towards relevance through
customer centricity
We have learned to work together to set visions
and to trust each team to make good decisions.
We have created a flexible approach that means we
can deliver projects quickly and with measurable
benefits.RESULTS ACTIONS Opportunities Possibilities RELATIONSHIPS
From an idea to a learning process
We (Travel Republic) knew what we wanted to do
for our customers and were prepared to take some
risks to learn.
We (bd4travel) had a vision of how travel needed
to be sold and a technical capability to deliver
AI based personalisation.
We committed to some outcomes together and have
built a long term constructive relationship.
Both parties recognise that we have much toEarly days but a huge and exciting map ahead of us
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