Analysis Greatest hits – the final countdown29 November 2011
Robbie BuscombeIndividual Giving Manager – Projects and Operations
Steven WhiteDirector of Operations
1
• The introduction– About Marie Curie Cancer Care– Data Objectives in 2009– Foundation Audit
• The final countdown– The top ten analytical
techniques
• The future
• The music quiz results
2
Agenda
IntroductionAbout Marie Curie Cancer Care and where we were in 2009
3
About Marie Curie Cancer CareMarie Curie Nurses• The charity is best known for its network of over 2,000
Marie Curie Nurses working in the community to provide end-of-life care, totally free for patients in their own homes.
• Last year we cared for more than 31,000 terminally ill patients in the community and in our nine hospices.
• There is a Marie Curie Nursing Service available to 96 per cent* of the UK.
• We mainly care for people with cancer but we also care for people with other life-limiting illnesses such as dementia, Motor Neurone Disease and heart failure.
• To access a Marie Curie Nurse, patients and/or their carers should speak to their GP or District Nurse.
4
About Marie Curie Cancer CareMarie Curie Hospices• Marie Curie has nine hospices• It is the largest provider of hospice beds outside the NHS• Marie Curie Hospices provide care for patients with cancer
and other illnesses and provide support for families and carers, all completely free of charge.
Research• Marie Curie’s pioneering programme of palliative care
research is showing how we can better care for cancer patients.
• The charity has two centres for palliative care research, The Marie Curie Palliative Care Unit in London and The Marie Curie Palliative Care Institute in Liverpool. It also funds seven fundamental scientific research groups which investigate the causes and treatments of cancer.
5
About Marie Curie Cancer CareSupporting the Choice to Die at Home• Research shows around 65% of people would like to die at
home if they had a terminal illness, with a sizeable minority opting for hospice care. However, more than 50% of cancer deaths still occur in hospital, the place people say they would least like to be.
• Since 2004 Marie Curie Cancer Care has been campaigning for more patients to be able to make the choice to be cared for & die at home.
Funding• Around 70%of the charity’s income comes from the generous
support of thousands of individuals, membership organisations and businesses, with the balance of our funds coming from the NHS.
• Our services are always free of charge to patients & their families, which means that in 2010-12, we will need to raise more than £140 million. We spend more than £83 million a year on our care and research activities.
6
Where Individual Giving was in 2009• Had developed four appeals and Shine On (quarterly supporter newsletter)
as core mailing activity• Supported regional and other fundraising departments but did not have
access to their data• Had a good base of skills across the organisation to facilitate growthBUT…• Some datasets where not centrally owned (i.e. not on the main database)• Used a complicated RFV selection model – mailing segments with very few
supporters• Had no structured selection model for non-core mailings e.g. pledger
acquisition mailing• Generally there was a poor understanding of the content/quality of the data
and how it could be used• There was a lack of skills across the organisation to handle the required
change7
Analysis Objectives in 2009• Due to the recent introduction of the new CARE database, and limited
analytical capacity of the previous database, little analysis has been undertaken
1. Provide some essential basic reporting for Direct Marketing campaigns to enable tactical decisions to be made
2. Provide a suite of regular reports that can inform (Fundraising Management Team) of the volume, recency, frequency and retention of supporters at a high level
3. To support the implementation of the MCCC strategic plan (2008-11) by providing robust data on which to base long term investment decisions
4. Ultimately this analysis should be the first step in developing audience segmentation to support development of MCCC’s Stewardship Strategy
8
9
I’m worried that the strategic thinkers in this organisation don’t know or aren’t involved in the database architecture/structure.
Everything is in the database - we just can’t get any information out quickly… I use Excel.
Everyone is so focussed on their own detail and work in their own silos.
Not allowed to say that things don’t work well. Defensive culture is too positive.
The 4 different teams that communicate with my mum have no idea of her overall enthusiasm and value to Marie Curie.
We are the least report focused organisation I’ve come across.
Foundation Audit Spring 2009 – some quotes
If we have one record for everyone – people will quickly understand the relevance of the base.
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
£0
£10,000,000
£20,000,000
£30,000,000
£40,000,000
£50,000,000
£60,000,000
£70,000,000
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Num
ber o
f sup
port
ers
(new
or
laps
ed)
Inco
me
£
Calendar Year
Income with overlay of the number of New and Lapsed Supporters1989 to 2008
Fundraising Income
Number of new supporters (first gave in that year)
Number of lapsed supporters (last gave in that year)
10
Example of audit – the number of supporters lapsing has exceeded the level of new supporters during the years 2004 to 2007
11
1. Hygiene
2. Education
5. Tactical Reporting
3. FundraisingCloser to the
Database
4. SingleSupporter View
6. Delivery Software
7. Strategy
Process
Legacies
Online
Audit outcome – where did MCCC want to be ?
The Final CountdownOur analysis top ten
12
At number 10 – categorisation• SQL roadmap – developing analysis summary tables
– Single Supporter View(s)– Financial History Merge– Mailing History Merge– Source Code mapping – Reports (LTV, MASt)
13
wft_mailing_history_merge
mailing_history
mailings
segments
contact_mailings
wft_financial_history_merge
financial_history
sources
segments
financial_history_details
products
rates
order_payment_history
segment_cost_centres
legacy_bequest_receipts
declaration_tax_claim_lines
orders
wft_first_transaction& wft_last_ transaction
wft_mast_report
wft_ssv_ltv
contacts
wft_ltv_report
wft_regional_report
wft_model_scoreswft_fnsplit
At number 9 – reporting
14
Lifetime Value Model 2,823 £56,400,198 0 2,104 £17,046,210 0 4
Recruitment Year Quarter
Total Legacy
Counts = 2,823
Total Legacy
Amount =
£56,400,198
Total Legacy
Pledge Counts = 0
Total High Value
Counts = 2,104
Total High Value
Amounts =
£17,046,210
Supporters
Recruited65,845
Supporters
Active Yr316,977
Yr3
Retention 25.8%
Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10
Active Supporters 64,879 22,372 16,977 13,877 11,441 9,817 7,462
Retention Rate 34.5% 26.2% 21.4% 17.6% 15.1% 11.5%
Average Donation £86.51 £45.97 £48.39 £47.02 £57.62 £56.07 £21.90
Total Donations £5,612,704 £1,028,442 £821,436 £652,465 £659,230 £550,480 £163,425
Acquisition costs of £0.00 £0
Retention costs £0 £0 £0 £0 £0 £0 £0
Total costs £0 £0 £0 £0 £0 £0 £0
Total Contribution £5,612,704 £1,028,442 £821,436 £652,465 £659,230 £550,480 £163,425
Cumulative Contribution £5,612,704 £6,641,147 £7,462,583 £8,115,048 £8,774,278 £9,324,758 £9,488,182
Lifetime value £85.24 £100.86 £113.34 £123.24 £133.26 £141.62 £144.10
LIFETIME VALUE MODEL
REPORT
Grand Total Grand Total
Grand TotalGrand Total
2004_2005
Grand Total
FRONT SCREEN
SAVE SCENARIO
RESET
EDIT
All
Grand Total
Grand Total
Grand Total
Grand Total
Grand Total
T1 Desc T2 Desc
T3 DescFirst Gift Type
T4 Code
Contact Type
Ownership Group
First Gift Origin
First Gift Purpose
First Gift Payment Group
First Gift Source
Grand Total
At number 8 – knowledge transfer• Transfer of skills / Mentoring• Examples of training given in 2011
– LTV Insights – Selection briefs– SQL– Updating reporting tools– Advanced Excel– SmartFocus
15
select contact_number, product, transaction_date, fhd.amount, rank() OVER (PARTITION BY contact_number, product order by transaction_date desc) AS r, row_number() OVER (PARTITION BY contact_number, product order by transaction_date desc) AS w, dense_rank() OVER (PARTITION BY contact_number, product order by transaction_date desc) AS d from financial_history fh join financial_history_details fhd on fh.batch_number = fhd.batch_number and fh.transaction_number = fhd.transaction_numberorder by contact_number, product, transaction_date desc
16
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Example of Excel – free tips guide!
At number 7 – Response Uplift
17
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
£4.00 £5.00 £7.50 £10.00 £12.50 £15.00 £17.50 £20.00 £25.00 £30.00 £40.00
Res
po
nse
Rat
e %
Ask Amount £
Response Rate sensitivities Versus Ask £
A
B
C
• RUM modelling looks at populations of the supporter base who respond with different elasticities
Business As Usual Ask amount Ask test
Number records
Number responses Mean £ Median £ Response Rate
ROI (assumes 40p per pack)
£12 £5 26,685 1,315 £8.81 £5.00 4.9% 109%£12 £12 79,914 3,000 £11.00 £5.00 3.8% 103%£12 £15 26,305 961 £10.85 £5.00 3.7% 99%
£15 £10 10,235 1,564 £10.46 £10.00 15.3% 400%£15 £15 30,854 4,006 £11.02 £10.00 13.0% 358%£15 £20 10,162 1,207 £11.74 £10.00 11.9% 349%
£25 £15 8,282 1,286 £19.32 £15.00 15.5% 750%£25 £25 24,655 3,549 £20.39 £20.00 14.39% 734%£25 £35 8,292 1,025 £22.24 £20.00 12.4% 687%
£50 £50 11,540 1,848 £53.33 £50.00 16.0% 2135%236,924 19,761 8.3%
BAU Ask Amount
Number Mailed
Amount if all BAU
Best Ask test (ROI)
Amount if all Best Ask test
Difference £ Difference %
£12 132,904 £54,860 £5 £57,696 £2,836 5.2%£15 51,251 £73,300 £10 £81,916 £8,617 11.8%£25 41,229 £121,025 £15 £123,705 £2,680 2.2%£50 11,236 £95,952 n/a £95,952 £0 0.0%
Total 236,620 £345,137 £359,270 £14,132 4.1%
At number 6 – Lifetime value
18
• Presented to Chief Executive• Updated in-house• Essential metrics and understanding of performance• But historical and dependent on costs• Introducing Projected LTV …
From Basics To Bottom Line
10 to 6 are prerequisites before we can truly influence the bottom line … what makes the biggest difference are 5 to 1
19
At number 5 – Projected ROI
20
• Identifies key drivers of long term ROI:– Volume– Cost per acquisition for regular givers– Average Direct debit value– Attrition Rates– Suppression rates & Gift Aid penetration
• Feeds these assumptions into a cash flow model:– plus other assumptions around upgrade, reactivation, cross sell, loyalty
costs, financial discount rates etc. but we can start simple!
• Projects cash flow over 5 year period and shows:– Return on Investment– Breakeven period– Net financial contribution (income – expenditure)
• Can be used to compare channels and understand sensitivities to key drivers. Many assumptions can be quantified using LTV outputs
At number 5 – Projected ROI cont.
21
Inputs: use sliders to modify assumptions Outputs: shows projected cash flow over 5 years<- Low volume High volume ->
Volume 20,000 Survivors Income Expenditure Net Income Cumulative Net<- Low CPA High CPA -> Yr1 10,769 1,715,238£ 2,189,027-£ 473,789-£ 473,789-£
CPA £100 Yr2 8,215 1,137,615£ 48,003-£ 1,089,612£ 615,824£ <- Low value High value -> Yr3 6,894 868,590£ 34,700-£ 833,891£ 1,449,714£
Average Value £100 Yr4 5,914 690,729£ 27,285-£ 663,443£ 2,113,158£ Yr5 5,400 579,671£ 22,105-£ 557,565£ 2,670,723£
Attrition profile 4. High <- High attrition Low attrition -> Yr1-5 4,991,843£ 2,321,120-£ 2,670,723£ Non-Starters 13% 5 Year Return on Investment: 2.15 Month 1 7%Month 2 6% Number of survivors: Cumulative Net Income - showing breakeven year:Month 3 5%Month 4 4%Month 5 4%Month 6 4%Year 1 40%Year 2 25%Year 3 17%Year 4 15%Year 5 10%
4 <- Low High suppression ->
% Suppressed 0% 0<-Low High Gift Aid ->
% Gift Aided 80% #
0% 20% 40% 60%
Year 1
Year 2
Year 3
Year 4
Year 5
-
2,000
4,000
6,000
8,000
10,000
12,000
Yr1 Yr2 Yr3 Yr4 Yr5 -£1,000,000
-£500,000
£-
£500,000
£1,000,000
£1,500,000
£2,000,000
£2,500,000
£3,000,000
Yr1 Yr2 Yr3 Yr4 Yr5
Return On Investment Projection Tool
• Shows possible H2H scenario (high churn, high average value). Net income of £2.7m over 5 years and ROI of 2.15– If Yr1 attrition reduced to 30% then income rises to 3.7m (£1m gain)– If Yr1 attrition rises to 55% then income falls to 1.3m (and 1.6 ROI with breakeven
delayed to year 3)
At number 4 – Retention
22
Filter Criteria: Summary Measures: Attrition Summary:Recruitment Year 2009 Gross recruits: 9,805 No-Show Rate: 10%Source Type Face to Face Starters: 8,810 Yr1 attrition 25%Payment Method (All) Active supporters: 5,571 Yr2 attrition #N/APayment Frequency (All) Active value pa: 69£ Yr3 attrition #N/ASonar Lifestage (All) Income to date: 98£ Yr4 attrition #N/ASonar Wealth (All)Contact Age (All)
1. Cumulative attrition curves over first 24 months: 2. Cumulative attrition at 3, 6, 12 months:
Shows cumulative attrition as percentage of starters. Monthly curves only shown where >100 starters. Shows cumulative attrition at 3, 6 and 12 months on file. Attrition only shown where >100 starters.
3. Average monthly attrition rate over first 24 months: 4. Annual attrition up to 5 years:
Shows average monthly attrition as percentage of those active at start of month Annual attrition by year on file as percentage of those active at start of year
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Months on file
Jan 09Feb 09Mar 09Apr 09May 09Jun 09Jul 09Aug 09Sep 09Oct 09Nov 09Dec 09Overall
-
200
400
600
800
1,000
1,200
0%
5%
10%
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25%
30%
35%
Jan 09 Feb09
Mar09
Apr09
May09
Jun 09 Jul 09 Aug09
Sep09
Oct09
Nov09
Dec09
Recruitment Month
Starters
No-Show Rate
3m attrition
6m attrition
12m attrition
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Months on file
Update Report
0%
5%
10%
15%
20%
25%
30%
Yr1 Yr2 Yr3 Yr4 Yr5Year on file
Regular Giver Retention Tool
This is the Marie Curie 'Regular Giver Retention Tool' developed by Wood for Trees. This tool will help you understand attrition rates for regular givers and the 'quality' of supporters recently recruited.
Use the filters to the right to select a recruitment year (and optionally other filters) The hit 'update report' button to refresh data for the selected cohort.
See 'Instructions' sheet for more detail on definition of report filters and measures.
See Instructions
• “The retention tool is fabulous. It allows me to track and monitor no show & attrition rates across all agency & in-house campaigns. This insight into which streams have the best retention & their best cost per acquisition in the long term is consequently a great help for budgeting & strategy.”
• “The tool identifies “hotspots” during the donor journey by showing attrition at months 3,6 and 12. This will prove extremely useful when reviewing methods, contents & timings of supporter communications. Monitoring other supporter information such as average gift, age, wealth & other sonar profiles will allow a greater insight into targeting regular givers”
Yr1 Attrition
0% 5% 10% 15% 20% 25% 30%Yr1 Attrition has increased over recent
years: from c.10% pre-2005
To c.25% in recentyears
2010 in particular is showing signs of early
high attrition
Trending towards 20%-30% driven by high proportion of F2F
Predictors0% 5% 10% 15% 20% 25% 30%
F2F
DM
TM
2008 Yr1 attrition low at 15% overall: Channel clearly
an important factor<25 25-35 35-54 55+
0%
10%
20%
30%
40%
Sonar and age also shown to be predictive
Affluent Less Affluent
0%
10%
20%
30%
40%
At number 4 – Retention cont.
At number 3 – prediction models …• “There seems to be little science applied from a segmentation or data modelling
standpoint when campaigns are being developed” Data IQ Autumn 2011 article on Closing the Fundraising Analysis Gap
24
8 out of 10 charities who expressed a
preference
– To simplify the SmartFocus selections and time taken to produce the segments - reduce the number of cells (52 segments for XMS 2008 wave 1)
• The XMS 2009 selection had 5 segments!
– To consider targeting other sub-populations of the database not previously “understood” from a data viewpoint, as likely candidates to respond.
• Identified ‘good prospects’ within committed givers and regional supporters
– To improve ROI - Analysis of the last 5 XMS mailings had shown:
• 11,745 supporters have responded to all 5 mailings!
• 23,650 supporters continually being mailed XMS and never responded. Equates to £10k per annum potential saving!
• Employment of prediction model has been one factor in helping DM maintain good results. A £200k net contribution gain Vs Budget
– To transfer knowledge back to MCCC
• Provision of scoring code
• Develop the audience selection briefs
25
Campaign Prediction - Background and objectives
2626
GDA 2008 GDA 2009 GDA 2010 GDA 2011
£586,861 £608,947 £668,425
£814,977
Net Income from Great Daffodil Appeal Mailing has grown substantially in line with the
use of the Wood for Trees Scoring Model
Model not used
Model used
Great Daffodil Campaign – Marie Curie’s most heard of campaign
August 2007 August 2008 August 2009 August 2010 £-
£100,000
£200,000
£300,000
£400,000
£500,000
£600,000
CNA 2008 CNA 2009 CNA 2010 CNA 2011 £-
£50,000
£100,000
£150,000
£200,000
£250,000
XMS 2007 XMS 2008 XMS 2009 XMS 2010 £650,000
£700,000
£750,000
£800,000
£850,000
£900,000
GDA 2008 GDA 2009 GDA 2010 GDA 2011 £-
£100,000
£200,000
£300,000
£400,000
£500,000
£600,000
£700,000
£800,000
£900,000
AWA Warm XMAS WARM
CNA WARM (CASH ONLY)
GDA WARM
Pre-model
Pre-model
Pre-model
Pre-model
Post-model
Post-model
Post-model
Post-model
Strength of model visible across all four major campaigns
At number 2 – Legacies• A word on the legacy pledger model …
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Equal Model Decile
Predicted Response
Rate
Observed Response
Rate1 6.8% 6.7%2 3.4% 3.6%3 2.4% 2.3%4 1.9% 1.9%5 1.7% 1.7%6 1.2% 1.5%7 1.0% 0.9%8 0.7% 0.7%9 0.5% 0.5%10 0.4% 0.4%
Average 2.0% 2.0%
Received Legacy Mailing
Model Decile
Predicted Response
Rate
Observed Response
Rate1 0.49% 0.48%2 0.21% 0.21%3 0.14% 0.15%4 0.09% 0.08%5 0.06% 0.06%6 0.03% 0.03%7 0.02% 0.02%8 0.02% 0.02%9 0.02% 0.02%10 0.02% 0.01%
Average 0.11% 0.11%
Not Received Legacy Mailing (exclude supporters with no donations)
And this weeks number 1 – duplicates!
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1 No of Groups 13,352
11627 No of Groups (1) -
No of Groups (2) 352 No of Groups (3+) 13,000
out of 13,352 groups No of Unique Records 13,352
No of Dupes 54,438
No of Uniques (matched to HOUSE) -
Show: No of Uniques (new records) 13,352
Group Number Ref Match Type Match Key Score TITLE INITIALS SURNAME11627 45732 Rule_7510_P_AnyGiven 50-59 Mrs White
11627 7858811 Rule_7510_P_AnyGiven 50-59 Ms R White
11627 45732 Rule_7510_P_AnyGiven <50 Mrs White
11627 8207272 Rule_7510_P_AnyGiven <50 Ms N White
4
GRO
UPS
REC
ORDS
Viewed Status
Match Type
Viewing Group
Key Score
MATCH
MATCH
MATCH
MATCH
MATCH ALL
ACCEPT
ALL
Definitions
ALL
ALL
ALL
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Garbage In = Garbage Out
-
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
July 2010 February 2011 May 2011 July 2011 September 2011
Number of duplicates
So pop pickers …a recap on our top ten
10. Single Supporter View / Categorisation11. Measurement12. Transfer Knowledge13. Response Uplift Testing14. Lifetime Value
15. Projected ROI16. Retention17. Prediction Modelling18. Legacies – any science!19. Data Integrity
10 to 6 are the foundation, 5 to 1 are more tangible and impact bottom line!
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What next for analysis
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Introduction
• More on …
– Projected ROI
– Legacies
– Simple segmentation + communications overlay• Reviewing the effectiveness of communications
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What next ?
Active Raffle Supporters
Lapsed Raffle Supporters
Active Regular Givers Tenure 0-1 year
Lapsed Regular Givers Lapsed 0-2 years
Active Cash Appeal Givers Tenure 0-1 year
Lapsed Cash Appeal Givers Lapsed 0-2 yearsShow
Show
Show
Show
Show
Show
Show
Show
Show
Show
Number of Supporters 8,430
Number of Communications 87,751
Number of Responses 813
Contactable Supporters 7,538
Average Number of Comms 12
Totals
Response Rate
Cash Appeal Total Communications 14,836 Total Responses 509 3.4%
Supporters Contacted Supporters 6,688 Number of Supporters who responded 342 5.1%
Received no cash appeals 1,742 Responded to no cash appeals -
Received 1 cash appeal 3,851 Responded to 1 cash appeal 96
Received 2-3 cash appeals 1,296 Responded to 2-3 cash appeals 76
Received 4-6 cash appeals 1,337 Responded to 4-6 cash appeals 71
Received 7-10 cash appeals 172 Responded to 7-10 cash appeals 67
Received over 10 cash appeals 32 Responded to over 10 cash appeals 32
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Step 1 – MACRO Simple
Segmentation
Step 2 – Communication
Propensity Modelling (MICRO)
Step 4 – Targeting
Step 3 – Establish some rules
On retention… communications
• Continue to use
– Lifetime Value (historic)
– Committed Retention
– Projected ROI (Future LTV)
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On acquisition …
Answers to our music quiz
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And finally…
Europe – The Final Countdown 10. The Foundations – Build Me Up Buttercup11. The Housemartins – Build12. Supertramp – School13. Pink Floyd – Money14. Foo Fighters – All My Life15. Kaiser Chiefs – I Predict A Riot16. The Faces – Stay With Me17. ABBA – Knowing Me Knowing You18. Wham – Wake Me Up Before You Go-Go19. Garbage – The World Is Not Enough
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The artists and titles are …
Questions?
Thank you…
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