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1| Success factor: user data and personalisation
Big data for deciphering user profiles and
preferences
VALUE OF THE DATA
ANALYSIS OF PREFERENCES
Customer data can prove to be a
real goldmine for companies – if
they use it in a targeted way.
Google and Facebook earn billions
with data-driven business models.
A company can use information
gained from interacting with
customers to draw conclusions
about their individual preferences.
User profiles can be created from
big data (such as from data
mining/discovery, pattern
recognition, predictive analytics)
and can then be used to address
customers in a more targeted
manner (marketing), develop more
attractive products/offerings (sales)
or provide customers with better
support in service business on the
basis of their preferences. As a
result, customer satisfaction is
enhanced and the customer
lifecycle lengthened.
FRIENDS
NPS [1]
KEYWORDS
CONTENT
STATED
PREFERENCE
USAGE
BEHAVIOUR
CSAT [3]
FCR [2]
RESPONSE
TIME
WILLINGNESS
TO PAY
CONVERSION
RATE
SEARCH BEHAVIOUR
Big data
ACTIVE, PERSO-
NALISED
CONTROL OF
OFFERINGS
[1] Net promoter score [2] First contact resolution [3] Customer satisfaction score
Source: goetzpartners, goetzpartners Big Data Study 09/14