De individuele klantreis van Cor en Don Corné Hoogendoorn

2. Introduction – Corné Hoogendoorn
Manager Online Marketing - Corendon
Married and father of a daughter
10+ years experience in digital marketing

3. Introduction – Corendon
Netherlands & Belgium
> 500.000 passengers per year
Bookings for 1650+ hotels

4. E-commerce challenges in travel
industry
Transparant
market
Comparable
offers
Price sensitive
customers

5. Trends with huge impact on digital
marketing
‘Surprise the customer with a
personally relevant offer in
no-time’
Business goal
Online marketing challenges
Identify customer needs
With only few – or even no –
transactions per customer
Decrease online marketing costs
Advertise only when its relevant
Increase online marketing revenues
Improved conversion rates with relevant
offers
On average we have
20+ online touchpoints
per booking
In a rapidly changing online
environment:
Increase in costs of online advertising
due to competition in search engines
Many different devices and locations

6. How to achieve this in online marketing?
Personalization
of content and
service
an integrated
strategy over
all marketing
channels
Customer-centric
strategy
newslett
er
customer
service
website
online
advertising
Requirements for solution
Scalable Automation Lowering costs
and improving
turnover

7. Individual customer journeys
Family with kids Couple without kids
1 vacation per year
Activities for kids at
hotel
Medium budget
Multiple vacations per
year
Cultural trip
Low budget
Extensive search, long period, multiple
devices
Short search, multiple touchpoints,
last minute bookings
Booking period
Early bookers
(December – March)
Summer
holiday
Booking period
Last minute
(Oktober)
Summer
holiday
Winter
holiday
Booking period
Last minute
(June)

8. These consumers need a different
approach
Klantdata (DWH)
Productdata
Boekingen (DWH)
Websitegedrag
Input Recommendation Output
Website
E-mail
Post
SEA
Contact Center
Matching
Recommendation
Individu
al
Predict
ion
Conversion
Customer and
product
characterstics
Preferen
ces
Model
estimation

9. More personalized approach
Old version of
newsletter
New version of
newsletter

10. Results of this project
Business results Consumer results
98% decrease in unsubscribers for e-
mail marketing
151% increase in click-through rates
for e-mail marketing
54% higher conversion rate on entire
e-mail marketing
85% less mails send
Increased customer satisfaction
Less irrelevant mails for consumers
Relevant holiday suggestions

11. Next step: multiple channel
implementation
Klantdata (DWH)
Productdata
Boekingen (DWH)
Websitegedrag
Input Recommendation Output
Website
E-mail
Post
SEA
Contact Center
Matching
Recommendation
Individu
al
Predict
ion
Conversion
Customer and
product
characterstics
Preferen
ces
Model
estimation
Channel TimingProduct

12. Q&A Session @ Building
Blocks’ stand
14.15 – 14.30h