Why Data Matters Ross Simson Managing Director ross@InsightrePublic.co.uk 07711 090230
Insight republic Presentation at the Chief Data Officer Forum - Examining the role of the Chief Data Officer
Jul 21, 2015
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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
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
12
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
15
It is all about detail and harnessing the power of what the analysis tells us
Some facts about TV Licensing
16
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
17
• 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..
18
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
19
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
20
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
DataIQ - 2014 Data Strategy Survey
Where to next?
25th February 2014
Christine Andrews – Managing Director DQM Group
26
Background to DataIQ
• Annual survey of Data Strategy
27
Yes considerably46%
Only slightly47%
Not at all3%
Don't know4%
Has your organisations database grown over the last year?
Databases get bigger in 2014
28
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?
29
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?
30
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?
32
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?
33
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?
34
Marketing Skill sets changing
Rapidly19%
Steadily50%
Slowly23%
Not at all8%
Is your Marketing functions skill set changing?
35
The importance of analysis and analysts
36
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?
37
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?
38
Data Security
39
Data Security Threats
40
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
41
Contacts
• Call us on 0870 242 7788
• Huge range of content at www.dataiq.co.uk
• Linkedin group: “Data IQ”
• Follow us on Twitter @TheDataIQ
• Enter the IQTalent Awards
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