The consumer society of 2013 enables commercial opportunities that were previously not possible but it also brings massive challenges. How should all of these digitally recorded actions, movements and behaviours be interpreted and used to help us engage with consumers and promote our offerings? What customer journeys are being enacted offline, online and on premise? Marketing data should reflect the buyer decision process and therefore what people are doing, feeling and thinking. What needs are being satisfied? What preferences, interests and influences come into play? How relevant is context and place?

1. Briefing Paper
Briefing Paper By Paul Kennedy, Head of Consulting at Callcredit
Today’s consumer behaviour
demands a new data model

2. // Briefing Paper// 01 // www.callcredit.co.uk
Paul Kennedy is Head of Consulting within the
Marketing Division of Callcredit, focusing on
the use of data and digital media to impact
client marketing programmes. During his 17
years in the industry, Paul has undertaken a
wide range of insight based projects across
consumer sectors specialising in the custom
development of solutions to address business
issues. He acts as a bridge between data and
digital domains and leads Callcredit’s thinking
across emerging techniques, technologies and
engagement channels.
Ideas
Vision
SuccessDevelopment
Pragmatic

3. © 2013 Callcredit Information Group Ltd. All rights reserved
// www.callcredit.co.uk // Briefing Paper // 02
Contents
Today’s consumer behaviour demands
a new data model 3
The constantly connected customer 6
Consider seven categories of data to
support your contact strategy 8
Callcredits network of
consumer intelligence 9
1. Demographic
2. Channel preferences
3. Transactions
4. Credit, risk and Fraud
5. Current consumer needs
6. Digital engagement
7. Attitude / Personality

4. By Paul Kennedy, Head of Consulting
at Callcredit
The consumer society of 2013 enables
commercial opportunities that were
previously not possible but it also brings
massive challenges. How should all of
these digitally recorded actions,
movements and behaviours be interpreted
and used to help us engage with
consumers and promote our offerings?
What customer journeys are being
enacted offline, online and on premise?
Big Data?
Every day, vast amounts of data are
generated as we search for and buy the
things we need from our chosen brands.
Whilst it’s fantastic to have access to
all of the ‘digital exhaust’ coming off the
back of those activities, many marketers
are now drowning. In fact, 2.5 quintillion
bytes of data1
are generated every day.
Every minute of every day, Google gets
over 2 million queries, Facebook users
share 684 million pieces of content,
brands receive 34k likes, about 50k apps
are downloaded on iTunes and email users
send over 200m messages. Now multiply
those numbers by 1,440 to see what’s
generated in a day. Imagine how much will
have been collected in a year’s time!
Big data is not just about
size but more the awkward
nature of it
Today’s consumer behaviour
demands a new data model
// Briefing Paper// 03 // www.callcredit.co.uk
1
source: http://www-01.ibm.com/software/
data/bigdata/

5. // www.callcredit.co.uk // Briefing Paper // 04
There is a lot of hype around at the
moment about ‘big data’, but data without
commercial context and proper application
is an easy trap to fall into. Maybe big data
is a misnomer? Not all large datasets are
‘big’. Big data is not just about size but
more the awkward nature of it. If it will fit
into a traditional relational database, it’s
probably not big data. If the structure of
the data doesn’t change much, then it’s
probably not big data. If it can be analysed
using traditional analytical tools and
analysts we’re familiar with in marketing,
it’s probably not big data.
Ever since 1965, we’ve had Moore’s law –
and accordingly, data inflation continues.
A ‘Zettabyte’ sounds like a good upper
limit at 10 to the power of 70 bytes but
we now have the Yottabyte – 10 to the
power of 80, currently too big to imagine.
Actually, the thought that there’s more
data than we can process (which has
probably always been true) is dressed up
as the latest trend with associated
technology must-haves. Actually, it’s not
size that matters, but rather having the
‘right’ data to address the business
objectives we are working to. Over the next
few years we will therefore see the rise of
componentized small data – creating and
integrating small data ‘packages’ rather
than building big data monoliths.
© 2013 Callcredit Information Group Ltd. All rights reserved
“There is a lot of hype around at
the moment about ‘big data’, but
data without commercial context
and proper application is an easy
trap to fall into.”

6. // Briefing Paper// 05 // www.callcredit.co.uk
“44% of consumers always
research purchases online
before actually buying
in-store, while a further
52% sometimes check online
before buying in-store.”

7. // www.callcredit.co.uk // Briefing Paper // 06
© 2013 Callcredit Information Group Ltd. All rights reserved
The constantly connected customer
From the consumer point of view, the lines
between offline, online and on premise
experience are blurring – especially when
we look at retail. A recent survey found
that 44% of consumers always research
purchases online before actually buying
in-store, while a further 52% sometimes
check online before buying in-store.
Econsultancy reports2
that 85% of
marketers say using online data to
optimise offline is important and vis-á-
vis; joining online and offline data is now
listed as a top three priority. But, the
greatest challenge for marketing is that a
customer’s experience is now an aggregate
of online and offline events, mobile and
desktop, store and device, marketing and
service. This is a very real issue. One recent
study has found that 92% of retailers are
struggling with offline/online integration.
Have you noticed more shops are now
offering in store wifi such as Asda,
Superdrug and even some bank branches?
Customers can log on and browse the
internet whilst they are on premise.
Why are companies doing this? For
the customer it allows them to check
Facebook and email without eating into
their data allowances. For the retailer, it
offers improved conversion, better data
collection, personalization opportunities
and a richer multi-channel experience.
If customers are going to do the
showrooming thing, having wifi in the shop
will not stop them but it actually gives the
retailer an opportunity to be in the loop…
customers become visible as they browse.
Retailers can track them more closely
and promptly engage the customer with
its proposition. But it will only work for
retailers if it’s promoted well, is easy for
customers to log on and there is a clear
data collection strategy.
Recent research by On Device Research
showed that 74% of respondents would be
happy for a retailer to send a text or email
with promotions while they’re using in-store
wi-fi. Recent research3
shows that about
80% of mobile consumers are influenced by
the availability of in-store WiFi when deciding
where to shop.
2
http://econsultancy.com/uk/reports/
quarterly-digital-intelligence-briefing-digital-
trends-for-2013
3
http://stakeholders.ofcom.org.uk/binaries/
research/cmr/cmr12/UK_4.pdf

8. // White Paper// 07 // www.callcredit.co.uk
2013 will be the year when more companies
actually work out what more complex
customer journeys mean for their particular
business and aspirations for becoming truly
‘omnichannel’. But there is still plenty of
room for improvement as anyone
who’s been the subject of an aggressive
retargeting campaign knows. At the heart
of this is a well thought out contact strategy
supported by a data model which is right for
your business.
// Briefing Paper// 07 // www.callcredit.co.uk
CUSTOMER
CLAIMED -
INTENTIONS,
PRODUCT USE,
VISITS, LIKES
EXTERNAL
INTERNAL
Known
Modelled
Source: Callcredit analysis
Known and modelled data types across internal and external domains
and customer claimed data
Credit, risk and fraud
Insurance
Renewal dates
Home move triggers
Switcher triggers
Social likes
Check ins
Store wifi logon
Date of birth
Logged in web visits
Email clicks/opens
Purchases
Contact history
Predicted value
Life time value
Modelled
behaviour
Lifestyle
Demographic
House
characteristics
Attitudes and
personality
Post code
Local attributes

9. // www.callcredit.co.uk // Briefing Paper // 08
Consider seven categories of data to
support your contact strategy
By collecting and building the right
customer data a joined up customer
lifecycle programme can be designed
and implemented to engage with
customers as they discover, explore, buy
and revisit – whatever the touchpoint. Hit
and run marketing is definitely out. Recent
Google research showed that consumers
make an average of 10.4 touches4
from
initial stimulus to final conversion. The ‘push’
message that used to lie at the heart of
marketing is outdated; now consumers also
want to pull brands into their world and by
pre scoring customers with ‘lie in wait’ offers
driving the content strategy, they will be
more receptive. This needs a combination
of traditional and emerging data types such
as browsing, intent, trigger and switcher
data. It should take into account clickstream
variables such as web visits, email clicks
and real time geo location movements as
well as more traditional attributes such as
transactional, demographic and risk.
Marketing data should reflect the buyer
decision process and therefore what people
are doing, feeling and thinking. What needs
are being satisfied? What preferences,
interests and influences come into play?
How relevant is context and place?
The next page shows seven data categories
to consider within your data model. While
each one may be stored in isolation, they
relate to each other. High performing
marketing programmes are based on an
understanding of the role of each data type
and how they work together.
This may be one of the
first things to tick on
your ‘channel integration’
checklist
4
http://www.google.com/think/research-
studies/zero-moment-of-truth.html
© 2013 Callcredit Information Group Ltd. All rights reserved

10. 1. Demographic
• Includes gender, age, ethnicity,
income, home ownership, location
and census data
• Create profiles by combining these
variables with other data
• Use externally available classifications
such as Callcredit’s CAMEO suite
2. Channel preferences
• Channels include mail, phone, mobile,
email and web – owned sites and ad
networks
• Customer claimed, and solicited from
the brand as well as externally appended
• Helps drive initial path to purchase
as well as building retention
3. Transactions
• Data sourced from billing /
ecommerce systems
• Detailed product purchase data can
be used to drive relevant offers
• Can now source data from third party
sites to identify customers shopping
around
• Linking store transactions with known
individuals can be a problem
4. Credit, risk and Fraud
• Useful for both lending and
non-lending products
• Often combined with demographics
and transactional data
• Some variables can be used at
public level where company does
not contribute to a credit reference
platform such as SHARE
• Fraud screening data can help identify
transactions for alternative processing
/ checking
• Some services require the identity of
the purchasing customer to be verified
using external reference data
5. Current consumer needs
• Identification of consumers in the
market / shopping around
• The ability to identify, distribute and
action within hours or days is vital
• From insurance renewal dates to moving
home and switching energy provider
• Check out Lifestyles Online - Callcredit’s
lead generation agency
6. Digital engagement
• Traditional web visitor segmentations
often group people into current
customers, lapsed customers,
prospects etc depending on the level
of engagement
• Need to also use raw email / website
data to capture movements at a
customer level
• Map onto defined customer journeys /
paths to purchase
• Can now source geo location data
from in store Wi-Fi, telcos and social
platforms
7. Attitude / Personality
• You are what you like – social likes
and connection are predictive of
attitudes and interests and can indicate
intent to purchase
• Can be collected via social API,
Facebook Connect, etc
• Additional insight can be gained
from visual quizzes – motivations
and aspirations
// Briefing Paper// 09 // www.callcredit.co.uk
Callcredit’s network of
consumer intelligence
© 2013 Callcredit Information Group Ltd. All rights reserved

11. // Briefing Paper // www.callcredit.co.uk
“High performing marketing
programmes are based on
an understanding of the
role of each data type and
how they work together.”

12. // www.callcredit.co.uk // Briefing Paper // 10
DEMOGRAP
LOCATIONS
WEBSITE
VISITS
EMAIL
SOCIAL
DIGITAL
ENGAGEMENT
SALES
TRANSACTIONS
CONS
Age
Pages
visit
Tone of
voice
3G
Social
WiFi
Categories Monetary
RFV
Share of
wallet
Topics of
conversation
Influence
Items
clicked on
Incomplete
journeys
Goals
achieved
Opens
Clicks
Referrals
Affluence
Household
type
Customer
entered
data
Brands and
categories
Journeys
completed

13. // www.callcredit.co.uk // Briefing Paper // 11
Key to Diagram
Modelled data
solid line links example data types
dotted line indicates likely links
between data types
Known data
size of circle
proportionate to
typical amount of
data in scope
PHIC CHANNELS
CURRENT
NEEDS
ATTITUDES
PERSONALITY
CREDIT,
RISK,
FRAUD
UK
SUMERS
Postal
Mobile
Device
Insurance
Credit
rating
Long term
goals
Personality
traits
Brand
affinities Tastes and
preferences
Interests
Affordability
Over
indebtedness
Risk
Fraud
Financial
preferences
Technology
usage
Motivations
Lifestyle
Property
characteristics
Energy
Telecoms
Switching
Lending
Purchase
intent
Home
move
Email

14. I
http://www-01.ibm.com/software/data/bigdata/
II
http://econsultancy.com/uk/reports/quarterly-digital-intelligence-briefing-digital-trends-
for-2013
III
http://www.google.com/think/research-studies/zero-moment-of-truth.html
Callcredit Information Group
Enabling Smarter Decisions
To find out more about Callcredit’s Marketing Solutions
email info@callcreditgroup.com call 0845 60 60 609
or visit www.callcredit.co.uk
© 2013 Callcredit Information Group Ltd. All rights reserved
About Callcredit Information Group
Callcredit Information Group has a leading edge approach to using consumer information
in credit referencing, marketing services, interactive solutions and consultative analytics.
This enables our clients to cost-effectively identify, engage and convert more new
customers and optimise existing customer revenues.
Callcredit Marketing Solutions can help develop an integrated channel strategy with
the following services:
• Appending emails, mobile numbers and landlines to terrestrial data
• Reverse matching of email addresses
• Profiling of online enquirers and customers
• Finding e-lookalikes
• Helping to build engagement with invisible offline customers
• Joining online intents and behaviours with offline data and activities
• Presenting unified content, including offers and messages to customers based on all
channel interactions