Business success through data driven insights

BUSINESS SUCCESS THROUGH
DATA-DRIVEN INSIGHTS
Unleashing the power of your customer’s voice through data

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Questions remain about the best ways to structure marketing teams in this new
world order of data. Organisations are experimenting with different resourcing
models: some building analytical teams in-house, while others are leveraging
technical expertise and market intelligence from external suppliers.
We are learning that despite differences in the way organisations choose to
implement their data strategy, those who are successful share specific common
characteristics. These businesses have:
A robust, clearly-defined data strategy
Access to substantial analytical skills
Data strategists with the right mix of commercial intelligence, communication
and broad analytical skills to provide strong connections between business
objectives and its use of data
Effective leadership that actively influences the C-suite and works productively
across internal silos
Intellectual curiosity and courage to ask insightful questions that uncover
intelligence that positively affects the business.
IN THIS PAPER WE DISCUSS:
Data’s role as the customer’s voice
The future of free-service business models
The best way to design your data strategy
Effective ways of infusing data throughout your organisation
The skills needed to implement your data strategy effectively
Specific internal communications needed to leverage your data investment
How to find the right balance of skills by mixing in-house with external suppliers
Ways to improve the connection between your data scientists and marketers
A possible picture of the ideal data function.
IT IS WIDELY RECOGNISED THAT DATA HOLDS THE KEY TO
UNLOCKING AN IN-DEPTH UNDERSTANDING OF CONSUMER
BEHAVIOUR. HOWEVER, MANY BUSINESSES HAVE A LONG WAY
TO GO TO MAKE THE MOST OF THEIR DATA. A LOT OF WORK
STILL NEEDS TO BE DONE TO FINE TUNE BOTH THE DESIGN
AND IMPLEMENTATION OF DATA STRATEGIES.
INTRODUCTION

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GOLDILOCKS OF DATA: TOO MUCH, TOO LITTLE, JUST RIGHT
The amount of data you can capture for analysis has never been greater.
This deluge of data has produced some unexpected consequences:
Although data-rich organisations benefit from the potential to
understand a lot about their customers, there are downsides to having
so much data. Not only can the costs of managing and analysing large
volumes of data be high, but also, with so much data to choose from, it’s
easy to become distracted and confused about where the priorities lie
for analysis.
Data-poor businesses do not necessarily need to be limited by their
apparent lack of data. With limited data to work with, their analysis
is focused and inexpensive. These businesses are often more open
to investing in their data strategy through partnerships with external
research companies.
These firms can identify other groups of consumers with similar
characteristics (qualified leads), and uncover insights from larger sets of data.
THE IMPORTANCE OF DATA HAS CONTINUED TO GROW
UNABATED FOR GOOD REASON: DATA HAS COME TO
REPRESENT THE CONSUMER, AND THEIR VOICE. FOR MANY
BUSINESSES IT HAS BECOME THE PRIMARY TOOL THEY USE
FOR LISTENING TO CUSTOMERS, UNDERSTANDING THEIR
CURRENT NEEDS, AND PREDICTING FUTURE DEMAND.
DATA HAS BECOME THE VOICE OF THE CONSUMER
DATA STRATEGY HAS BECOME
A DIFFERENTIATOR BETWEEN
BUSINESSES
An organisation’s data is one of its
most powerful assets. As with any
other asset, managing it effectively
has become a way for consumers
to differentiate between businesses
competing in the same markets.
It is therefore more important than
ever that you manage your data as you
would any other core business tool.
You need a clear, effective strategy
and thorough implementation plan to
maximise the benefits you derive from
your data.
MORE IS NOT ALWAYS BETTER
Without a clearly-defined data strategy, there
is a tendency to collect everything you can find
out about your customers. This approach is costly
and inefficient, as it is not driven by an overarching
data strategy.
“Just because you can collect the data, doesn’t
mean it’s going to be meaningful and useful.”
A better approach is to focus on quality
interactions with customers. There is no need
to over-engage customers.

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Currently there are two free-services
business models:
1 Free service available to all,
plus a premium paid-for service
that includes exclusive extras.
Examples include Dropbox and
Evernote.
2 Advertising model, where the
service is provided free, but
contains advertising. Spotify,
Pandora and Facebook use the
advertising model.
These two business models can only
continue if the data they capture,
and the insights they generate are
monetised.
FREE-SERVICE MODELS WILL
CONTINUE TO BE POPULAR
There are a number of specific
characteristics that make free-service
models an attractive way of doing
business. They provide a way to:
Build a new business
Grow a customer base
Develop trust in a brand
Obtain customer insights.
Moreover, there is strong demand
for free-services from consumers.
The bottom line is: consumers
want to use ‘free’ services, and are
comfortable with the value exchange
offered by this business model.
FUTURE DEVELOPMENTS
FOR FREE-SERVICES
Consumers know their data has value,
and that once they have given it away,
their personal information belongs to
the company they gave it to.
Most consumers accept that giving
their data away is the price they
pay for better products, services
and customer experience. For
example, Google services can now
link your calendar and location
information to tell you how long
it will take to travel between
meetings.
Customers recognise the benefits
of more targeted advertising that
comes from data exchange.
Free-service business models could
face changes as consumers become
more active participants in the
exchange of their data.
Data problems reflect poorly on
reputation and represent a risk
that needs to be actively managed.
Customer experience continues to
drive perceptions. When customers
have negative experiences as a
result of having provided their data,
they will react. In some cases this is
as simple as blocking advertising,
however, if their experience has
been positive, most customers will
continue to openly share their data.
There will always be customers
who are happy to trade their data
for lower prices, and there will
always be those who do not want
to reveal their data at any price.
Paying to opt-out may become
more prevalent. ‘Do not track
me for a fee’ could become
an attractive option for some
customers.
THE POSSIBLY UNINTENDED
CONSEQUENCE OF THE RISE
OF FREE-SERVICES
Customer’s expectations have risen
significantly. We now demand at
least some degree of personalisation
in our customer experience, whether
the product or service is free or not.
THE ARGUMENT FOR FREE-SERVICE BUSINESS-MODELS
FREE-SERVICE BUSINESS MODELS ARE THOSE WHERE
THE CONSUMER MAY OR MAY NOT PAY A FEE TO ENJOY SOME
OR ALL OF THE SERVICES PROVIDED.
DATA ESSENTIALS: RULES OF THUMB
The way you treat your customer’s data reflects directly on your organisational culture
and reputation. It’s critical therefore that you behave in a transparent way, being open and
honest about the information you collect about customers and how you use it.
Social media provides consumers with a platform and audience outside your control. It
makes sense therefore to provide channels for capturing customer sentiment, comments
and negative feedback, so you have an opportunity to deal with issues as they arise, out of
the public eye.
Consumers are savvy. They know their data is valuable to business, so you must offer a fair
exchange of value to obtain it. Today’s customers need compelling reasons to provide you
with their data.
When you collect data, customers expect to be treated more personally in exchange. If
you are not able to deliver a better product or service, which demonstrates you know the
customer as an individual, it may be better not to collect their data.
Focus your investment on your most profitable customers. Direct your primary data
analysis at quantifying the value of your customers, and identifying those from whom you
derive the most profit.

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FEEDBA
CK
GOALS
TECHN
OLOGY
TEST IMPLEMENT
DATA
PEOPLE
• examine all your touch points
• make an inventory of all the data you’re capturing
• determine what you’re going to do with the data you’re capturing.
It’s likely that what you’re capturing won’t match your needs completely.
You will need to modify your strategy to fit the reality of your situation.
• prioritise any new points of data you’re going to capture. You can’t have it
all, but your strategy can help you determine which data points to focus on.
ORGANISATIONAL CULTURE CHALLENGES DATA STRATEGY IMPLEMENTATION
Your organisational culture can
create challenges to smoothly
implementing your data strategy.
Data is a relatively new function, and
as such, it can be difficult to fit into
existing organisational structures.
There are a number of key questions
that need to be answered and
understood across the organisation
in order for a data strategy to be
executed effectively.
Just what does marketing do?
Common misunderstandings
about roles can make it difficult for
marketing teams to make the shift
from being seen as ‘the coloured
pencils department’ to a strategic
function that feeds business insights
into the organisation. Data and
analysis have traditionally fit in IT or
accounting functions. Transitioning
these key skills and responsibilities
into marketing can be made
smoother by explaining to the
organisation as a whole:
why they need data
why they should be using it
what their role is in capturing data
how the business benefits
commercially from using its data.
The solution to this problem is
communication. Marketers need
to do what they do best, and that is
market the marketing team.
Who owns your data?
Although IT has been the traditional
custodian of an organisation’s data
(IT typically own the CRM system), in
order for its value to be fully realised,
it needs to be shared beyond the IT
function or department. For it to be
of commercial value, data needs to
be analysed by those with intimate
knowledge of:
the business
the market that its products and
services compete in
consumer behaviour.
These areas of experience fall
beyond the traditional scope of the
IT function. It therefore makes sense
that ownership for data be shared
beyond IT.
SUCCESSFUL BUSINESS STRATEGIES
PRODUCE EFFECTIVE DATA STRATEGIES
FOR A DATA STRATEGY TO BE SUCCESSFUL, IT MUST SUPPORT OVERALL BUSINESS GOALS. TOO OFTEN THERE IS ONLY SCANT
ALIGNMENT BETWEEN THE OVERALL COMMERCIAL STRATEGY OF A BUSINESS AND THE DATA STRATEGY THAT SUPPORTS IT.
Successful business strategies define objectives at a granular level. For example, the overall business strategy
will define the objectives, such as improving customer loyalty, but it will also define what loyalty mean in terms of
measurable outcomes. These specific, measurable outcomes
can then be fed into the objectives of each business unit.
Effective data strategies are derived directly from the overall organisational strategy. Their outcomes mirror those of
the businesses. Before formulating a data strategy, objectives have been agreed to at a business level. These objectives
flow directly into your data function, and serve as the starting point for designing your data strategy. This approach
ensures your data strategy aligns completely with your overall business strategy.
To find out more about effective ways to design your data strategy, please refer to the 2015 white paper,
Harnessing the value of your data.
DATA STRATEGY DESIGN
Designing your data strategy is an iterative process. It begins with your organisational goals, and then moves
on to assessing your data:

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Where does responsibility for data strategy lie?
Data strategy is derived from business strategy. And
once a data strategy has been established, appropriate
technology is then applied to achieve its objectives.
Responsibility for data strategy therefore lies with
those responsible for setting and delivering the overall
business goals. This can be interpreted narrowly or
widely across the organisation.
Although IT is intricately involved in delivering an
organisation’s data strategy, it does not necessarily
make sense for IT to be responsible for defining the
strategy. Technology in of itself is not a data strategy.
Rather, it is the tool with which solutions to data
questions can be answered.
Where do data skills fit in the organisational structure?
A range of skills is needed to make effective use
of an organisation’s data. Experts from across the
organisation need to be brought together into one team.
As with project-based teams, resources from marketing,
product or services, finance, operations and IT all need
to be actively involved in delivering your data strategy.
With all the skills in the one team, the connection
between technical skills used in analysing raw data,
and commercial skills used to apply data to support
marketing and business objectives can join with a
common purpose. The ‘cross-pollination’ between job
functions that occurs in data teams helps build bridges
and understanding across silos. When diverse functions
understand what each other needs to perform their
particular roles, not only can the two functions work
together more efficiently, but they will work together
more harmoniously to benefit the business.
Technology has changed very quickly, enabling
businesses to know more about their customers than
was possible even five years ago. Although our collective
thinking at the cutting edge has progressed, many of the
day-to-day systems we rely on have not caught up. This
poses challenges to those responsible for implementing
data strategies today.
A lack of understanding by business of how its data
works and what it can achieve leads to unrealistic
expectations about what a data strategy can deliver.
Internal clients can think solutions are easy to obtain
‘at the touch of a button’.
In the quest for precision, quick solutions can be
overlooked. There is often a lack of appreciation of the
benefit of learning things incrementally; building on
your experience.
When ‘everything is possible’ there is a tendency to
become overly detailed. When your internal clients
know how detailed your data can get, they often ask
for extremely specific data, when often a wider sample
would be faster to analyse, easier to use, and provide
sufficiently insightful answers.
As expert communicators, the marketing team can
improve the overall understanding of the function of data
and its role in an organisation.
IMPROVING THE GENERAL LEVEL OF UNDERSTANDING
ABOUT DATA CAN HELP AVOID COMMON MISUNDERSTANDINGS
DATA HAS TRANSFORMED
THE ROLE OF MARKETING
Data strategy has revolutionised the
role of marketing. It has changed
the marketing function from one of
‘marketing push’ to one of ‘marketing
pull’, or ‘engagement based upon
customer experience’.

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ALL DATA
COMMERCIAL FOCUS
LEADERSHIP
DATA STRATEGY
DATA ANALYSIS
DATA EXTRACTION
DATA COLLECTION
EXTERNALRESOURCES
INTERNALRESOURCES
THE COMMERCIAL LENS PROVIDES FOCUS FOR EFFECTIVE IMPLEMENTATION
Today’s marketing team requires decisive leaders who
can clearly articulate business strategy. Effective leaders
are strong communicators who provide a direct, two-way
channel between the C-suite and marketing team.
Data now drives the majority of marketing activities,
and as a result, we need to broaden our skills to keep
up. To lead a marketing function you need to have
expanded your skill set to include:
An understanding of what your organisation’s
marketing technologies can achieve. You need to
ensure you are using the tools you have to their fullest
potential to deliver the greatest return on investment.
Courage to support curiosity. New insights into
consumer behaviour can be uncovered through
original research by analysts. As an effective leader,
you should provide your team with sufficient leeway
to investigate new lines of enquiry.
Balancing curiosity with commercial direction. Your
understanding of how to use the commercial lens will
help you lead your analysts down paths of investigation
that support overall business goals.
Use your data to guide your activities. By embedding
specific, measurable targets in your marketing
program you can use attribution modelling to
determine the effectiveness of each activity. This more
detailed modelling enables you to more carefully
measure your return on investment from each activity,
and incrementally improve the overall return-on-
investment generated by your marketing function.
DATA-DRIVEN ORGANISATIONS SUCCEED WITH THE RIGHT COMBINATION OF SKILLS. THEY HAVE AN ADEQUATELY RESOURCED
INTERNAL TEAM OF TALENT, AND DRAW ON APPROPRIATE EXTERNAL SUPPLIERS TO FILL SPECIFIC GAPS.
SKILLS NEEDED TO IMPLEMENT YOUR DATA STRATEGY EFFECTIVELY
LEADERSHIP’S ROLE

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WHEN EVERYONE IN YOUR
ORGANISATION SUPPORTS
YOUR DATA STRATEGY, YOU
CAN ACHIEVE EXCEPTIONAL
RESULTS. THE MOST
DIRECT WAY OF ENGAGING
EVERYONE IS THROUGH
EFFECTIVE INTERNAL
COMMUNICATIONS.
Deepening the relationship with customers
Your internal communications should focus on
connecting the organisation with the customers
it serves. You should aim to:
1 Develop a common view across the organisation of
who your customer is, their likes and dislikes, what
their needs are and why they choose to interact with
your business
2 Deepen the understanding of why customers come
to you and what need they are hoping to address.
This will enable everyone in the business to focus on
providing products and services that maximise the
benefits customers receive from their engagement
with your business.
3 Help to build an understanding that data is your most
important asset. If you don’t understand who your
customers are at a deep level, you cannot create
brand loyalty.
4 Share customer insights across business units. Silos
can be broken down when business units are able to
learn from one another, with the shared purpose of
better understanding the organisation’s customers.
Disseminating immediate information about customer sentiment
It’s important that information and insights generated by your data strategy are available quickly and easily to those
who need them. You should ensure that your internal communications strategy supports the day-to-day operations
of your data function.
Your internal communications strategy should provide:
1 A smooth connection between the business and data analysis, so quick answers to high-level questions can be
accessed easily.
2 Regular data analysis to departments as part of their every-day internal communications news feed.
3 Feedback of the results of analysis, as well as any commercial opportunities and insights identified from the data
analysis process.
4 Signals that directly relate to KPIs. Having built data into KPIs at a business and individual level, your internal
communications need to provide feedback and tracking against those goals.
INTERNAL COMMUNICATION SKILLS REMAIN CRITICAL
SPEAK THE LOCAL LANGUAGE
TO ACHIEVE ENGAGEMENT
Different parts of your business will use their
own language with phrases and acronyms
that are meaningful to them. To achieve
understanding and respect, you need to
speak the local language, using terms that
are relevant.

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THE BEST MARKETING IN THE WORLD
CANNOT SELL BAD PRODUCTS OR SERVICES
Although data can significantly improve business
performance, it cannot overcome the challenges of bad
products and poor services.
Currently we have a very output-centric view of the world.
We measure in terms of commercial output goals that are
relevant to the organisation. We need to shift to customer-
centric metrics that more closely align to measure the quality
of the customer experience.
KEY AREAS TO ADDRESS IN YOUR INTERNAL COMMUNICATIONS ARE:
Common misperception
“If we’ve captured the data, we should be
able to use it quickly and easily.”
“Only very detailed analysis can provide
accurate answers.”
“It’s better to wait for answers to specific
questions than to draw conclusions from
broader analysis.”
“Data and data strategy have nothing to
do with most people’s roles, rather, it
is something done by marketing or the
C-suite.”
Communication required
Data requires manipulation and analysis to become useful
information.
Legacy issues and the complexity of existing systems can make
it difficult to extract data for analysis.
Data analysis can be refined incrementally
High-level data analysis might be sufficient to answer basic
questions quickly, before detailed modelling can be done.
These initial high-level enquiries can help refine questions and
the data analysis required to provide meaningful answers.
An overall roadmap for data strategy implementation needs to be
given priority by the C-suite.
The link between broad business strategy and tangible priorities
for each area of the business needs to be made.
Clear data strategies should be applied and communicated to each
line of business, tailored to their own needs.

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COMPLIANCE MATTERS
Although the law lags behind technology and the ways we use data, it is essential that brands operate
with integrity when it comes to using customer information.
Consumers are smart and more aware now of the value of their data and how it is being used. They
expect to be in control of their own information, and be given the opportunity to provide consent before
it is used. To ensure these expectations are met, it is vital that data systems are designed in a way that
protects customers, and regulates the use of their data.
Marketers need to work closely with their legal teams to ensure that they are fully versed in the that
relates to privacy and data. Where gaps in legislation occur, marketers should act conservatively,
following the spirit of the law, protecting the rights and privacy of their customers.
Invest in listening
All organisations, regardless of size, compete in markets
with others. Although your data can indicate what’s
going on outside your business, it will never be able to
provide you with a complete picture. To find out what’s
going on in the market around you, you need to actively
listen to information beyond your own doors.
Part of your data collection strategy should include
active monitoring of your market for intelligence. It will
help you understand what is important to your customer
base, and how they are likely to behave in the future.
Monitoring other segments, such as another geographic
location, can also provide useful insights, and should
not be overlooked as part of a comprehensive market
intelligence program.
Partner with data specialists
When you have a small customer base, it can be difficult
to find out more about them beyond their contact
information. Generating insights from limited data can
be very expensive. There are businesses that specialise
in filling your data gaps and providing you with insights
into the characteristics of your customer base, drawing
from larger pools of similar customers.
Partnering with a data specialist can be a cost-effective
way of learning more about your audience. Those with
very large, broad databases, and years of analysis will be
able to tell you far more about your audience and their
behaviours than you are likely to be able to find out on
your own without spending a lot of money.
LEVERAGING DATA SKILLS BEYOND YOUR BUSINESS
THE DATA SCIENTIST: WHERE ART AND SCIENCE MEET
Data scientists combine a unique set of skills that unlock the commercial potential
of your organisation’s data. They are both creative in their marketing approach and
scientific in their analytical practice.
Successful data scientists balance a range of skills including:
analytics
predictive modelling and
data manipulation,
while at the same time understanding how data drives commercial decisions
in the business.
A true data scientist is able to:
translate a business problem into an equation that can be solved using data, and
realise the potential in an existing data asset.

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DATA ANALYSIS
HARDWIRING STRONG COMMUNICATIONS IN YOUR DATA STRATEGY
GETTING THE MOST OUT OF YOUR ANALYSTS
Be reasonable. Be mindful of the communication
challenges most analysts face, and adjust your
expectations accordingly. Build flexibility into their roles
so they can be creative with your data. Enable them to
explore avenues of enquiry and also further develop their
technical skills.
Embrace curiosity. It leads to uncovering insights and
new opportunities.
Consider testing theories manually. If the theory is
correct, you have proved the method is accurate and
the outputs are useful; you can then consider investing
time and resources to automate the system.
Balance curiosity with KPIs, so your analysts achieve
what you want them to.
BUILDING BETTER CONVERSATIONS
BETWEEN DATA SCIENTISTS AND MARKETERS
Greater understanding and appreciation of each other’s
roles begins with communication. Marketers and data
scientists can take active steps to improve the way they
interact by getting to know one another.
Common goals provide the basis for common purpose.
Discussing how each area contributes towards serving
customers can help build respect.
Shifting the focus from a product push to a customer
pull will help teams focus on their commonality of
purpose. Project teams that span both functions,
designed to solve specific problems, will help improve
understanding.
Analytics and marketing are not mutually exclusive.
For data to be useful, it needs to be infused with
creativity and ideas. Conversely, marketing is not
effective without the insights produced by data
analysis.
Marketing can begin by learning how to ask the right
questions: ones that are directly linked to business
objectives. Marketers need to learn the language so
they know what to ask for.
COMMUNICATE
RESULTS OF
ANALYSIS AND
COMMERCIAL
OPPORTUNITIES
IDENTIFIED
COMMUNICATION/
ENGAGEMENT
FOR DATA CAPTURE
AND EXTRACTION
COMMUNICATE
DATA STRATEGY
DATA
ANALYSIS
GREAT DATA ANALYSIS COMBINES THE ART OF
STORYTELLING WITH THE SCIENCE OF STATISTICS.
Finding someone who can make the connection between your data and the
journey your customers experience can be like finding a unicorn. Statisticians
who have both commercial awareness and strong communication skills are rare.
Acknowledging that you are unlikely to find the ideal mix of skills in any individual
is the first step to solving this problem.

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1. DEFINE YOUR GOALS
2. IDENTIFY THE OUTCOMES YOU NEED TO DELIVER
TO REACH THOSE GOALS
3. DESIGN YOUR DATA STRATEGY AROUND YOUR
ORGANISATIONAL GOALS
4. FIND THE IT SOLUTIONS TO DELIVER YOUR
DATA STRATEGY
test your processes first manually to see the method you’re
proposing is possible, and that the outcome is meaningful. If
it works, then automate. Invest in only what you need, rather
than buying the system and hoping the outputs will meet your
business needs.
once you have invested in a particular IT solution, it can be
tempting to collect as much data as you can. The problem with
this approach is that you can end up trying to find something
interesting from within a very broad set of data. You are looking
for answers without knowing what the question is. A better
approach is to lead with a data strategy: identify the questions
you need answered, and then build the IT solution to address
those needs.
DATA STRATEGY ESSENTIALS
Without a clear data strategy in place,
significant resources can be spent
investing and supporting systems that
don’t produce the information your
business needs to make decisions.
Moreover, these systems will not achieve
a positive return on investment.

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OBSESSION WITH YOUR CUSTOMER
REMAINS A PRIORITY
The ideal team contains marketers who:
are immersed in understanding the customer’s
experience at all points along their journey
develop deep relationships with customers,
interpreting changes in the voice of the customer,
feeding the change back into the organisation,
and adjusting or re-shaping the business’s
response accordingly.
SIZE DOESN’T MATTER
With the growth of specialist data services, it is now less
important for organisations to have their own in-house
team of analysts. As Laura Prophet of BusinessMinds
Australia points out in the following case study, you are
better to focus on understanding what skills you need,
and bring experts in as you need them, rather than
scaling up your internal function.
THE RISE OF DATA’S IMPORTANCE HAS CHANGED THE
COMPOSITION OF THE IDEAL MARKETING TEAM. DATA HAS
INTRODUCED A NEW SET OF SKILLS TO THE MARKETING
FUNCTION, AND IS CHANGING THE STRUCTURE OF MANY TEAMS.
THE IDEAL MARKETING TEAM: HOW TO BUILD A DREAM TEAM
THE DREAM TEAM
The ideal marketing team contains:
1. People with the right combination of
a. analytical skills
b. psychological insights and social media skills to understand and interpret
the customer’s journey and the effect of their sphere of influence on behaviour
c. communication skills and
d. commercial intelligence
2. Clear leadership
3. Curiosity: the ability to ask why.
a. Data strategy needs to begin with curiosity.
4. Doers: people who
a. Take responsibility for commercial outcomes
b. Are committed to understanding and improving the customer journey
c. Continue their own education in both technology and marketing
5. KISS: People who keep things simple, and don’t overly
complicate things.
CURIOSITY WILL MAKE THE DATA FUNCTION
OF YOUR MARKETING TEAM EXCEPTIONAL
The best data teams are:
Intellectually curious, and keen to ask the question ‘why?’
Curious about their data and how they can use it in
different ways to find out more meaningful uses
Courageous, following their instincts to pursue
unconventional lines of enquiry to uncover valuable
insights for the business
Actively look for business opportunities through their
knowledge of an organisation’s data.

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It is difficult for most organisations
to afford the resources they need
to analyse their data on a full-
time basis. Regardless of your
budget, technical skills are now in
such high demand it is difficult to
get quality resources. Moreover,
technology is changing at such a
rapid pace that it makes it difficult
to retain up-to-date skills within
an organisation.
Specialist data research businesses
can help fill the gaps in your team.
The question then remains: which
parts of your data strategy do you
perform in-house, and which parts
do you outsource?
THE IDEAL SYSTEM IS A COMBINATION
OF EXTERNAL AND INTERNAL RESOURCES
The ideal system is an internal system that everyone
can access and use to answer quick, straightforward
questions. This system can be stretched by an external
supplier who has more sophisticated tools and analysis
to perform complicated queries on your data.
For this ideal system to operate well, your internal team
needs to be knowledgeable enough to ask the right
questions, and understand what can and cannot be
drawn from the data and systems you are operating.
APPLY A STRATEGIC MINDSET
When you are deciding how to resource your data
function, you should approach the problem with
strategic intent.
Decide what you are going to analyse, and then choose
the system that most closely meets your needs. Don’t
be sold on a system first and then try to make it fit
your business needs.
Improve your existing resources where possible:
– Look at ways you can up-skill your existing talent
– Consider introducing more soft-skills training for
your data scientists
Where gaps exist in your data function, consider both
external and internal solutions.
Decide on your mix of in-house and external resources
on the basis of what is the best way to meet your
strategic goals, both data and organisational.
RESOURCING YOUR DATA FUNCTION
AN INTERNAL CENTRE OF EXCELLENCE
OR A NETWORK OF EXTERNAL SUPPLIERS.

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CASE STUDY
When should a business consider outsourcing parts
of its data function?
Every business is different, however, businesses benefit
the most from outsourcing when:
you’re looking at doing something new that requires
specialist technical skills. Predictive modelling and
establishing business triggers are areas where it often
makes sense to get external help.
you are setting up a new model that is complicated
and beyond the skills of your existing staff; temporarily
buying that expertise in makes a lot of sense.
Establishing processes on structured data or where
you’re performing a new type of analysis on your data
often benefits from expert help.
there are peaks of work. Rather than hiring an
additional full-time employee, it can be more cost-
effective to bring in temporary talent to get through
peaks in work flow. For example, if you have a number
of campaigns launching at the same time, additional
resources just at that time can be very helpful.
Data cleaning companies can come in and quickly
rectify gaps in your data, such as incomplete names
and addresses. Although you can to do this process
internally, it’s usually a lot more cost-effective to
outsource. Data companies also offer lead services,
where they identify other customers with characteristics
similar to your own, making them a useful source of
qualified leads.
Are there any particular types of organisation that
benefit more than most from outsourcing?
Small businesses and start-ups tend not to have the
specialist skills required for complicated data analysis
in-house. When you’re small, you need people who can
hit the ground running, with minimal training because
your staff often have less time for training others given
the frenetic pace of start-ups.
Which types of benefit can businesses expect
from outsourcing?
The right suppliers will bring with them up-to-date
knowledge of what is current market best practice
in their field. In addition to identifying gaps in your
team, they can often help you work out the best way of
organising your existing analytical resources.
When external suppliers work with your own team, they
share knowledge from other projects they have worked
on. This transfer of skills will benefit your in-house team.
Are there things you wouldn’t recommend
outsourcing?
Your high-level data strategy isn’t something you can
outsource.
However once you have your high-level data strategy in
place and you have quantified exactly what it will deliver,
you can then start to look at how you’re going to flesh
out and implement your data strategy, and explore the
internal and external resources available to help you
achieve those goals.
A combination of internal and external staff works well
for strategic projects to ensure internal guidance and
involvement.
Do you have any specific advice for companies
looking at outsourcing?
Outsourcing support with your data is no different from
outsourcing other strategic business functions; you
need to be clear about your objectives and manage your
suppliers carefully.
Make sure your supplier understands exactly what you
want to achieve –both strategically and tactically. You
don’t want them going off on tangents or analysing
things that aren’t commercially useful to you.
Ensure your data is protected:
– Check you have provided them with access to all the
data they need to perform their role
– Ensure there are clear rules around who can access
your data and how the data can be used
– Make sure the supplier understands which fields
in your data relate to privacy, so any extracts they
perform comply with your opt-out policies.
FINDING THE RIGHT BALANCE OF INTERNAL AND EXTERNAL RESOURCES
LAURA PROPHET, DIRECTOR AT BUSINESSMINDS AUSTRALIA, SHARES HER THOUGHTS AND EXPERIENCES AROUND FINDING
THE BEST MIX OF INTERNAL AND EXTERNAL RESOURCES.

30 31
In addition to strong communication skills, your data team needs
robust analytical skills to be effective. Managing these two diverse
sets of skills is a central challenge for leaders. Deciding which
skills to maintain in-house, and which to outsource requires careful
consideration. There is no single model that fits all organisations.
However, it can be said that at certain times, most organisations will
benefit from external specialist help.
As technology unfolds offering marketers more ways to monitor
consumer behaviour, managing data well will become increasingly
important. We are already seeing consumers deciding which
organisations they will provide patronage to on the basis of the benefits
their business’s data systems provide. Whether it’s as seemingly
impersonal as recommendations for similar items on Amazon, or
highly-targeted advertising on Facebook, managing your data function
well is fundamental to achieving your overall business goals.
AS THE MODERN PROXY FOR THE CUSTOMER’S VOICE,
YOUR ORGANISATION’S DATA HAS BECOME ONE OF
ITS MOST IMPORTANT ASSETS. THE WAY YOU MANAGE
YOUR DATA FUNCTION DIRECTLY AFFECTS YOUR
ABILITY TO UNDERSTAND YOUR CUSTOMERS AS
WELL AS THEIR NEEDS AND BEHAVIOURS.
Consumers understand the value of their data and are becoming
empowered with new ways of controlling how their online activities are
monitored and the ways their individual data is used. Marketers need to
think carefully about what information they collect. If you’re not able to
offer your customers a benefit or value in exchange for that information,
you might be better off not collecting it in the first place.
The primary purpose of your data function is to support your overall
business goals. Your data strategy should directly reflect your business
objectives, providing a link between business strategy and outcomes
through measurement. As a conduit of the organisation’s strategy, your
data team need to be highly effective at internal communications.
CONCLUSION

32 33
ACKNOWLEDGEMENTS
Jeff Evans
VP Digital, APAC
Epsilon
Matt Zimmerman
Director of Loyalty Marketing CRM,
Orbitz
Stuart Jarvis
Marketing Manager - CRM Insights,
David Jones
Michelle Sherwood
Head of Red Planet, Commercial,
Qantas
David Fong
Head of Analytics Strategy,
eBay Australia New Zealand
Andrew Newell
Head of Strategy,
Datalicious
Con Georgelos
Head of Analytics,
News Ltd
Branko Ceran
CIO,
Cancer Council NSW
Luke Brown
CEO Founder,
Affinity
Brad Martin
Head of CRM Consumer Analytics,
Tabcorp
Hamish Hartley
Data Strategist,
OgilvyOne Sydney
Alex Burrows
Analytics Senior Manager,
Accenture
Dan Richardson
Head of Data Targeting,
Yahoo7
Laura Prophet
Director,
BusinessMinds Australia
Marcelo Ulvert
Managing Partner,
Cohort Digital
Leanne Stagnitta
General Manager, Customer Analytics,
Research Development Technical,
Allianz Australia
Carl Oldham
Planning Director,
The Works
Simon Edwards
Head of Market Research and Insights Marketing,
Commonwealth Bank
Greg Nichelsen
Executive Manager Customer Analytics,
Suncorp Group
Michael Mocatta
Strategic Solutions Director,
Marketsoft
JJ Eastwood
Managing Director - Australia,
Rocket Fuel
This white paper is a result of the experience, ideas and thought leadership
generated by they ADMA data expert group think tank.
These invitation-only facilitated workshops explore topics related to our pillars: data, technology, content
and creative with customer experience at the centre.
With thanks to the members of the ADMA data expert group listed below.
WRITER AND RESEARCHER:
Charlotte Spencer-Roy
Copywriter

34 35
The Association for Data-Driven Marketing and Advertising is the principal industry
body for information-based marketing and advertising and is the largest marketing
and advertising body in Australia.
ADMA is the ultimate authority and go-to resource for creative and effective data-
driven marketing across all channels and platforms, providing insight, ideas and
innovation to advance responsive and enlightened marketing.
We represent the new era of marketing and advertising
We signify the full spectrum
– From marketing to advertising
– From effective to creative
– From above to below
– From measurable to engaging.
ADMA has over 550 member organisations including major financial institutions,
telecommunications companies, energy providers, leading media companies, travel
service companies, airlines, major charities, statutory corporations, educational
institutions and specialist suppliers to the industry including advertising agencies,
software and internet companies.
© 2016
ADMA WHITE PAPERS ABOUT ADMA
Designed to inform decision-making executives about the latest developments in
an area of best-practice marketing, we include examples of what can be achieved,
how it can transform the operations of an organisation, and the main issues you
need to consider when applying the principles, practices and technologies. To find
out more about ADMA and our market-leading insights, please visit us
at adma.com.au.

Association for Data-driven
Marketing and Advertising
ACN 002 909 800
ABN 34 002 909 800
Level 6, 50 Carrington St
Sydney NSW 2000
GPO Box 3895
Sydney NSW 2001
T +61 2 9277 5400
F +61 2 9277 5410
contact@adma.com.au
adma.com.au
Registered Office

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