Insight republic Presentation at the Chief Data Officer Forum - Examining the role of the Chief Data Officer

Why Data Matters

Ross Simson

Managing Director

ross@InsightrePublic.co.uk

07711 090230

1 ZB = 1000000000000000000000bytes = 10007bytes = 1021bytes = 1000exabytes = 1 billion terabytes.

0% 5% 10% 15% 20% 25% 30%

Contact lists

RSS Feeds

Other

Social media

Instant messages

Coporate web sites

Presentations

Customer Databases

Spreadsheets

Word Docs

Email

Where does the data come from?

Global Survey: Is Big Data Producing Big Returns? Avanade

Sources McKinsey Cityscope, Journal of advertising research, 2011

The Data Challenge

Asking the Right Question, Join the Right Data

with the Right Technology, to deliver the Right Benefit

Global Survey: Is Big Data Producing Big Returns? Avanade

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1212

68,020 Council

houses maintained

20,000 tonnes of

paper recycled

2,499 km of roads

maintained

2,675 acres of park

maintained

14,371,230 school

meals served

3,000,000 hours of home

care provided

4,174,716 library visits

176,495 pupils taught

The largest local authority in the UK, one of the largest in Europe

60,000 staff £3 billion budget

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It is all about detail and harnessing the power of what the analysis tells us

Some facts about TV Licensing

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Each year

£3.7bn is

collected

9m phone

calls

135m DD

transactions

4m visits

per year

25.5m

active

customers

2 web sites

handling 8m

transactions

40m cash

transactions

The TV licence accounts for over 90% of the BBC’s

income

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• A holistic picture of the state of TV Licensing on a monthly basis.

• Ability to define key customer groups – and define tailored strategies to maximise revenue.

Key features:

We can see all revenue received

Segmentation of addresses and licences by value – identify opportunity

New suite of meaningful and actionable KPI’s.

Track customer journeys – even between schemes and unlicensed periods.

Provides a base for predictive analytics – focus on proactive/preventative measures

Think of it as the map in a

WW2 ‘War Room’

All Addresses

N = 34,319,438

Net Income = £3,741,117,153.53

Average Value = £109.01

NO Payment Activity

N = 6,050,441 (20%)

Payment Activity

N = 24,922,795 (80%)

Net Income = £3,733,584,213.21

Average Value = £149.81

Over paid

N = 2,240,242 (9%)

Net Income = £571,871,225.22 (15%)

Average Value = £255.27

Full Fee

N = 20,176,075 (81%)

Net Income = £2,952,433,238.91 (79%)

Average Value = £146.33

Not Licensable

N = 3,346,202 (10%)

Net Income = £7,532,940.32 (<1%)

Average Value: £2.25

Licensable

N = 30,973,236 (90%)

Net Income = £3,733,584,213.21 (>99%)

Average Value: £120.54

Under paid

N = 2,455,987 (10%)

Net Income = £210,923,003.18 (6%)

Average Value = £85.88

Negative Payments

N = 50,491 (<1%)

Net Income = -£1,643,254.11

Average Value = -£32.55

Payment Activity

N = 35,934 (1%)

Net Income = £7,532,940.32 (100%)

Average Value = £209.63

NO Payment Activity

N = 3,310,268 (99%)

Demolished

N = 29786 (83%)

Net Income = £2,705,481.98 (36%)

Average Value = £90.83

Not Demolished

N = 6,148

Net Income = £4,827,458.34 (64%)

Average Value = £785.21

We can now analyse payment behaviour of a licence holder at a property..

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Their average value is…Volume Value

Over payers 9 £xxx

Full fee payers 61 £xxx.24

Under payers 9 £xx.06

Zero Payers 8 £0

Sum Value: £xx,xxx.25

Map of segment locations

And starting to uncover detailed Insights

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44 50% of long term zero payers are licensable

There is a division between old and new properties

Old builds (-2007) New builds (2008-2013)

Average value 1xx.21 1xx.70

% of underpayers x.57% 1x.56%

% of zero payers x.57% 1x.86%

No full fee payers paid by cash

The ‘Careers and Kids’ group are 2.6x more likely to not be full fee payers than ‘Professional Rewards’

And using the next generation of the Rubik’s Cube we will be able to delve even deeper

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Mosaic “Careers and Kids” cost-benefit analysis

Revenue Cost Profit per house

Field Visit ££££ ££££ £

Aggressive Call ££ ££ £

Gentle Call ££££ ££ ££

No Campaign £ £ £

Key thoughts

• Love your data and nurture it like a child

• Big data vs (near) real time execution

• Hire more mathematicians & psychologists

• “Customer First, Business Second”

• Answer the boards questions –

– “Why” and “So What”

Your Professional Development Partner

The IDM is Europe's leading training and qualifications organisation for the digital, direct and data-driven

marketing profession.

Our priority is professional development, not shareholder profit. The IDM is a UK charitable trust, and

profits are invested in EmployAbility programmes to help attract, inspire and get jobs for the next generation

of direct, data and digital marketers.

Not for profit, just for talent.

Leading networks and customers

Why Data Matters

Ross Simson

Managing Director

ross@InsightrePublic.co.uk

07711 090230

DataIQ - 2014 Data Strategy Survey

Where to next?

25th February 2014

Christine Andrews – Managing Director DQM Group

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Background to DataIQ

• Annual survey of Data Strategy

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Yes considerably46%

Only slightly47%

Not at all3%

Don't know4%

Has your organisations database grown over the last year?

Databases get bigger in 2014

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Data gets more social

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%

Don't know

Location Based Information (e.g check-ins, shares, posts)

None of the above

Social Media Transactions (e.g wall posts, shares, comments)

Loyalty Program Information (e.g card number, points, purchases)

Social Media Profile (e.g profile id, likes, interests)

Web Tracking (e.g link clicks, page views, transactions)

Email Behaviour (e.g open rate, click throughs, bounces)

Is your organisation collecting any of the following information?

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Data Plans

Key: Which of the following does your organisation have in place?

Which do you plan to introduce

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

Don't know

Big data strategy

Data quality programme

Customer insight team

Channel insight teams (i.e, web analytics, digital marketing…

Data governance processes

Data security programme

Single customer view

Which of the following does your organisation already have in place?

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IT and Business working together

Very well18%

Well36%

Occasionally37%

Not at all9%

How well do IT and Marketing work together when it comes to outreaching to customers?

31

Drivers of Investment

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0%

Don't know

Haven't seen any positive ROI from data

Need to cut costs

Reducing customer churn

Reducing marketing wastage

Need to become more customer-centric

Need to make more evidence-based decisions

Improving marketing performance

Need to integrate data across channels

Gaining better customer insight

What are the drivers of any change in investment in data during 2014?

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Preparedness for Data

Governance Changes

Very prepared8%

Well prepared28%

Slightly prepared44%

Not prepared at all12%

Don't know8%

How prepared for Data Governance changes is your Marketing department?

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Data Challenges in 2014

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

Don't know

Creating a single customer view

Increase in customer data

Threat of tighter data regulations

Building data and insight skills in house

Ensuring data security and data governance

Improving insight and analytics

Enhancing data quality

What data challenges do you foresee for you/your organisation in 2014?

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Marketing Skill sets changing

Rapidly19%

Steadily50%

Slowly23%

Not at all8%

Is your Marketing functions skill set changing?

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The importance of analysis and analysts

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Analysis Constraints

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0%

Don't know

Don't know

Reduced cycle time for use of insight

Increasing demand for insight from functions

Lack of skilled analysts

Poor data quality or lack of data feeds

Lack of insight tools and technology

Lack of funds

What are the main barriers to using/increasing your use of analytics?

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Importance of Data Quality

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

Don't know

Environmental policy or corporate social responsibility

Fraud detection

We don't have a data quality programme

Data warehousing/business intelligence programme

Risk mitigation

Customer data integration

Operational efficiency

Better sales performance

Compliance

Better customer relationships

Better business performance

Better marketing performance

What are the drivers for your data quality programmes?

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Data Security

39

Data Security Threats

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Conclusions

• Big Data - if you can see the value, start collecting (but make sure you give customers a reason…)

• Get the basics locked down (quality, integration) - drive value strategically (insight, governance)

• Don’t forget the data people - analysts, data stewards

• And don’t forget to train and support them…

• Security a worry so asset seed the database

• Establish a good data breach programme

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Contacts

• Christine.andrews@dqmgroup.com

• Call us on 0870 242 7788

• Huge range of content at www.dataiq.co.uk

• Linkedin group: “Data IQ”

• Follow us on Twitter @TheDataIQ

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