The “Big Data Inspirator” has been designed to help you grasp the full spectrum of business value that can be unleashed through data. Start by identifying for which business purpose you would like to leverage data and get inspired by the 40 real life examples that explain each one pattern how to derive value from data.

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The “Big Data Inspirator” has been designed to help you understand all the ways in which data
can help add value to your business. Start by identifying why you want to collect data and
the purpose it will serve within your business. Be inspired by 40 real life examples
illustrating different ways of deriving value from data.
Once you have understood what you would like
to accomplish, use our ”Data-To-Value Builder”
to design how to achieve your business
objectives with data.
AT&T
Targeted up-selling
The telecommunications
company AT&T uses
multiple indicators such as
billing and sentiment
analysis in order to identify
customers that can be
upgraded to higher quality
products.
USAA
Targeted cross-selling
The insurer USAA analyses
data from multiple sources
to spot key events in
customers’ lives. This
enables USAA to approach
customers with just the
right cross-selling offer: car
insurance when a
customer’s daughter is just
about to get her driving
license, for example.
Jeanswest
Retention vs. acquisition
The apparel chain
Jeanswest figured it was
in a far better position to
retain the customers it
already had than to
acquire new ones. By
tracking purchases,
Jeanswest predicts when
its customers repurchase
products and is the first to
send them an offer.
Avis
Customer lifetime value
The car rental company
Avis identifies customers
with the greatest lifetime
value by predicting their
rental frequency and
profitability. This has
enabled Avis to focus its
customer acquisition on
handpicked customers of
potentially high value.
Lavazza
Clustering vs. segmenting
When it launched Fair Trade
Coffee, Lavazza used
analytics to group custom-
ers instead of segmenting
them. Lavazza discovered
that 11.6% of customers
had been overlooked so far,
as no one thought about
advertising the self-made
rather than the altruistic
aspect of fair trade.
Dollar General
Cross selling partnerships
Discount retailer Dollar
General analyses which
products from different
suppliers tend to end up in
the same shopping basket
of customers. This enables
suppliers to work out
cross-promotional agree-
ments with other suppliers
to share their customer
bases for mutual benefit.
Sotheby’s
Leads identification
The real estate company
Sotheby’s identifies
potential home sellers by
approaching wealthy
households whose children
are leaving for college.
Sotheby’s identifies new
“empty nesters” by tracking
shifts in a household’s
buying patterns.
Walmart
Personalised online shopping
Walmart has increased the
number of purchases made
in its online shop by
10-15% by making search
results more relevant.
Walmart uses text analysis
and synonym mining to
understand the searcher’s
intentions and the contex-
tual meaning of the terms
he or she has used.
John Deere
Insights enabled services
John Deere places sensors
on the tractors it sells.
Combining the data
collected by these sensors
with data on soil conditions,
weather and crop features,
John Deere helps farmers
identify where and when to
plant to get the highest
yield and how to reduce
fuel costs for their tractors.
Sephora
Personalised shopping
The cosmetics chain
Sephora has installed
beacons at its stores. This
technology enables
Sephora to send persona-
lised offers and recommen-
dations to its customers’
phones, tailored to their
specific interests and
position in the shop.
Kayak
Insight as service
Kayak is a travel search
engine that allows users to
compare prices of flights.
To make itself even more
attractive, Kayak has used
big data analytics to design
a new service which
predicts whether the price
for a particular flight will go
up or down within the next
week.
Hagleitner
Monitising insights
Hagleitner Hygiene fits
sensors in the toilets of
fast food restaurants to
ensure that paper towels
do not run out. In addition,
Hagleitner analyses the
data it collects about how
frequently toilets are used
to help its customers
decide how best to deploy
their cleaning staff.
Express Scripts
Insights enhanced products
Express Scripts, which
processes pharmaceutical
claims, realised that the
patients who most needed
to take their medication
were also the most likely to
forget to take it - so, the
company introduced
beeping medicine caps to
remind these patients to
take their pills.
BMW
Information enhanced products
Like many other automobile
manufacturers, BMW has
transformed its cars into
mobile data generators.
Drivers benefit from
relevant information such
as measurements of
distance and environmental
conditions.
Delta
Information as service
Lost baggage is one of the
biggest inconveniences
faced by airline passen-
gers. Delta Air Lines uses
big data to enable its
customers to track their
baggage from their mobile
devices. This gives travel-
lers a lot more peace of
mind, and 11 million
downloaded the app.
Thyssen Krupp
Information enabled services
The elevator manufacturer
Thyssen Krupp collects
data about the elevators it
has sold, enabling it to offer
its customers remote
diagnostics and predictive
maintenance. The sensors
integrated in the elevators
have a strong lock-in effect
and can be used for new
services in the future.
Marriott
Real-time pricing
The hotel chain Marriott
uses weather reports and
local events schedules to
forecast demand and to
determine a value for each
room throughout the year.
Optimising pricing
efficiency is vital for
Marriott, since its custom-
ers often use price
comparison services.
Verizon
Verizon Wireless, the
largest U.S. carrier with
over 98 million retail
customers, sells aggre-
gated and anonymous
subscriber data to third
parties. Details such as
gender and geo-localisation
allow for targeted market-
ing campaigns.
Monetising information
JE Dunn
Clients of the construction
company JE Dunn often
ask for buildings they
cannot afford. For this
reason, JE Dunn allows its
clients to tailor buildings to
their needs in a modular
way, calculating the price in
real time using data on
material and construction
costs.
Modularised pricing
Ryanair
Ryanair uses a dynamic
price calculator to capture
the willingness to pay of
travellers depending on
factors such as time of
purchase and weather at
the purchaser’s location.
Ryanair analyses a huge
amount of data that
influences the perceived
value of a flight.
Capture willingness to pay
DM
The drugstore DM is a
retailer with high levels of
fluctuation in customer
volume. By analysing
historical turnover and
contextual parameters, DM
has been able to automate
the shift planning for each
of its stores. This has
significantly improved staff
availability for customers.
Shift scheduling
Union Pacific
Union Pacific Railroad has
reduced derailments of its
trains by 75%, by proac-
tively identifying and
carrying out maintenance
work on at-risk equipment.
Union Pacific uses
thermometers, micro-
phones and ultrasound to
collect data about its
engines and rails.
Proactive maintenance
McDonalds
McDonalds has started
adapting its franchising
model to tailor all of its
restaurants to their own
markets. McDonalds
analyses the preferences
of local customers. This
data is used when design-
ing menus, drive-through
restaurants, etc.
Smart franchising
Intel
The chip manufacturer Intel
has saved USD 3 million by
analysing the data
produced by its manufac-
turing equipment for one
line of chips in order to
predict quality issues. This
has significantly reduced
the number of quality tests
that need to be performed.
Streamlining production
Otto
The availability of
purchased goods is crucial
for customers of online
retailer Otto. Using an
algorithm based on sales
history, current stocks and
marketing campaigns, Otto
has managed to increase
availability while reducing
stocks.
Predicting stocks
Telekom
The telecommunications
company Telekom scans
social media almost in real
time to identify potential
customer service issues,
and proactively contacts
the author of the post.
Customers appreciate the
effort the company has
gone to, and feel that
Telekom cares about them.
Proactive customer service
Saarstahl
The steel company
Saarstahl sorts scrap parts
at an early stage of
production in order to make
better use of its production
capacities. It has installed
sensors to monitore
product and process
quality, which allows for
real-time adjustments to
the production process.
Production optimisation
Tesco
The supermarket chain
Tesco has cut energy costs
for its refrigerators by 20%,
resulting in €20 million in
annual savings. Tesco
achieved this by collecting
and analysing 70 million
refrigerator-related data
points coming off its units.
Asset performance
Bristol-Meyers
The pharma company
Bristol-Meyers has used
clinical trial simulation to
speed up drug studies from
2.5 to 1.7 years. Applying
analytics to historical trial
data has enabled the
company to reduce the
required number of blood
samples per subject from
12 to 5.
Speeding up R&D
Nestlé
Social media has caused
serious damage to Nestlé’s
brand. Today, the company
uses social media analytics
to actively engage with
people that post about
Nestlé. This gives Nestlé
the opportunity to explain
its point of view and thus
mitigate brand damage.
Social media management
Red Roof
The hotel chain Red Roof
realised that up to 3% of
flights are cancelled during
harsh winters. By analysing
weather conditions and
flight cancellations, Red
Roof is able to place ads on
mobile devices in the areas
most affected, increasing
hotel occupancy by 10% in
these areas.
Event based marketing
T-Mobile
T-Mobile realised that when
customers with a lot of
social influence switch
brand, many of their peers
follow. By identifying the
so-called “tribe leaders” via
social network analytics,
and focusing its marketing
efforts on them, T-Mobile
has managed to increase
overall customer loyalty.
Tribe leader marketing
Kroger
The supermarket chain
Kroger launched a direct
mail campaign with a
coupon return rate of over
70% within six weeks,
compared to an industry
average of 3.7%. Data
about customers’ shopping
history was used to make
the coupons highly relevant
to each customer.
Personalised loyalty program
HDFC Bank
HDFC Bank analyses the
profiles and user behaviour
of its customers in order to
tailor the content and
channels of its communi-
cations to each individual
customer. This has created
a more personal relation-
ship, with less perceived
spamming.
Smart communication
Sport Scheck
The retailer Sport Scheck
gets its customers to run
on a treadmill in its shops
to analyse their running
style. Using product and
running data, Sport Scheck
helps customers select the
footwear that suits them
best. This experience
encourages customers to
visit physical stores again.
Selection support
Citibank
As soon as people use their
Citibank card to make a
purchase, Citibank sends
them information via a
push notification about
how to save money on that
purchase. The comapny’s
services have generated a
lot of word-of-mouth
recommendations and
brand love on social media.
Contextual marketing
Xerox
Xerox has used talent
analytics to reduce the
attrition rate in its call
centres by 20%. In order to
do this, Xerox analysed
what was causing the high
rate of staff turnover. This
enabled Xerox to hire the
right people and to improve
employee motivation.
Smart hiring
DHL
For logistics company DHL,
the “last mile” is the most
expensive part of the
distribution process. Using
location data from DHL’s
fleet and participating taxi
drivers, commuters and
students, DHL has deve-
loped a low cost, crowd-
based delivery service for
the last mile.
Smart delivery
EMI
By intentionally leaking
music and monitoring
reactions to it, the record
label EMI can confidently
predict demand for albums.
Since sales volumes vary
for each album, this has
enabled EMI to match
production to actual
demand in a much more
accurate way.
Forecasting demand
“Information is the oil of the 21st century,
and analytics is the combustion engine.”
Peter Sondergaard
One of the challenges
faced by Daimler Fleet-
Board is assessing the
individual risk level of each
of the truck drivers it
insures. By analysing their
truck data, the company is
able to price insurance
policies based on drivers’
individual driving behaviour.
Usage based pricing
Daimler
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BIG DATA INSPIRATOROrange HillsTM
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Avis
Sotheby’s
Lavazza
DollarGeneral
AT&T
USAA
Jeanswest
Citibank
T-Mobile
Nestlé
Red Roof
Telekom
Kroger
HDFCBankSportScheck
Sephora
Walmart
JohnDeere
ExpressScripts
Kayak
DM
UnionPacific
Otto
EMI
Tesco
Saarstahl
Intel
Bristol-Meyers
Xerox
DHL
McDonalds
Ryanair
Marriott
Daimler
JE
Dunn
Verizon
Delta
BMW
ThyssenKrupp
Hagleitner
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“The goal is to turn data into information,
and information into insights.”
Carly Fiorina
...is ”raw”, unorganised and
without meaning on its own.
...is interpreted data with
contextual meaning.
...are conclusions derived
from information.