BUSINESS SUCCESS THROUGH DATA-DRIVEN INSIGHTSUnleashing 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.

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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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.

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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.

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DATA HAS BECOME THE VOICE OF THE CONSUMER

MORE IS NOT ALWAYS BETTERWithout 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-SE RVICE 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.

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THE ARGUMENT FOR FREE-SE RVICE BUSINESS-MODELS

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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FEEDBACK

GOALS

TECHNOLOGY

TEST IMPLEMENTDATA

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.

SUCCESSFUL BUSINESS STRA TEGIES PRODUCE EFFECTIVE DATA ST RATEGIES

FOR A DATA STRATEGY TO BE SUCCESSFUL, IT MUST SUPPORT OVE RALL 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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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 STRA TEGIES PRODUCE EFFECTIVE DATA ST RATEGIES

FOR A DATA STRATEGY TO BE SUCCESSFUL, IT MUST SUPPORT OVE RALL BUSINESS GOALS. TOO OFTEN THERE IS ONLY SCANT ALIGNMENT BETWEEN THE OVERALL COMMERCIAL STRATEGY OF A BUSINESS AND THE DATA STRATEGY THAT SUPPORTS IT.

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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.

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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 MARKETINGData 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

EXTE

RN

AL

RES

OU

RC

ESIN

TERN

AL R

ESOU

RC

ES

THE COMMERCIAL LENS PROVIDES FOCUS FOR EFFECTIVE IMPLEMENTATION

DATA-DRIVEN ORGANISATIONS SUCCEED WITH THE RIGHT COMBIN ATION OF SKILLS. THEY HAVE AN ADEQUATELY RESOURCED INTERNAL TEAM OF TALENT, AND DRAW ON APPROPRIATE EXTERN AL SUPPLIERS TO FILL SPECIFIC GAPS.

SKILLS NEEDED TO IMPLEMENT YOUR DATA STRATEGY EFFECTIVELY

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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 COMBIN ATION OF SKILLS. THEY HAVE AN ADEQUATELY RESOURCED INTERNAL TEAM OF TALENT, AND DRAW ON APPROPRIATE EXTERN AL 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.

INTERNAL COMMUNICATION SKILLS REMAIN CRITICAL

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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.

SPEAK THE LOCAL LANGUAGE TO ACHIEVE ENGAGEMENTDifferent 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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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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THE BEST MARKETING IN THE WORLD CANNOT SELL BAD PRODUCTS OR SERVICESAlthough 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.

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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

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THE DATA SCIENTIST: WHERE ART AND SCIENCE MEETData 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

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.

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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HARDWIRING STRONG COMMUNICATIONS IN YOUR DATA STRATEGY

COMMUNICATERESULTS OF

ANALYSIS ANDCOMMERCIAL

OPPORTUNITIESIDENTIFIED

COMMUNICATION/ENGAGEMENT

FOR DATA CAPTUREAND EXTRACTION

COMMUNICATEDATA STRATEGY

DATAANALYSIS

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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

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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

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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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.

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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?

RESOURCING YOUR DATA FUN CTION

AN INTERNAL CENTRE OF EXCELLENCE OR A NETWORK OF EXTERNAL SUPPLIERS.

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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 FUN CTION

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.

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.

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CASE STUDY

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.

LAURA PROPHET, DIRECTOR AT BUSINESSMINDS AUSTRALIA, SHARES HER THOUGHTS AND EXPERIENCES AROUND FINDING THE BEST MIX OF INTERNAL AND EXTERNAL RESOURCES.

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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

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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.

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ACKNOWLEDGEMENTS

Jeff Evans VP Digital, APAC Epsilon

Stuart Jarvis Marketing Manager - CRM & Insights, David Jones

David Fong Head of Analytics & Strategy, eBay Australia & New Zealand

Con Georgelos Head of Analytics, News Ltd

Brad Martin Head of CRM & Consumer Analytics, Tabcorp

Alex Burrows Analytics Senior Manager, Accenture

Laura Prophet Director, BusinessMinds Australia

Leanne Stagnitta General Manager, Customer Analytics, Research & Development Technical, Allianz Australia

Simon Edwards Head of Market Research and Insights Marketing, Commonwealth Bank

Michael Mocatta Strategic Solutions Director, Marketsoft

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.

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Matt Zimmerman Director of Loyalty Marketing & CRM, Orbitz

Michelle Sherwood Head of Red Planet, Commercial, Qantas

Andrew Newell Head of Strategy, Datalicious

Branko Ceran CIO, Cancer Council NSW

Luke Brown CEO & Founder, Affinity

Hamish Hartley Data Strategist, OgilvyOne Sydney

Dan Richardson Head of Data & Targeting, Yahoo7

Marcelo Ulvert Managing Partner, Cohort Digital

Carl Oldham Planning Director, The Works

Greg Nichelsen Executive Manager Customer Analytics, Suncorp Group

JJ Eastwood Managing Director - Australia, Rocket Fuel

WRITER AND RESEARCHER:

Charlotte Spencer-Roy Copywriter

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ADMA WHITE PAPERS

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.

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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

ABOUT ADMA

Association for Data-driven Marketing and Advertising

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