Supporter Attrition within Regular Giving at PDSA
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Supporter Attrition within Regular Giving at PDSA Victoria Barham Senior Marketing Analyst [email protected]
description
Supporter Attrition within Regular Giving at PDSA. Victoria Barham Senior Marketing Analyst [email protected]. Regular Giving at PDSA. Multiple Regular Giving Products Traditional Regular Giving, Cashcascade and Sponsorship All with different Supporter Profiles - PowerPoint PPT Presentation
Transcript of Supporter Attrition within Regular Giving at PDSA
Regular Giving at PDSA
Multiple Regular Giving Products• Traditional Regular Giving, Cashcascade
and Sponsorship• All with different Supporter Profiles
Multiple recruitment channels• Direct Mail, Web, Door to Door
Multiple Payment Plans and Frequencies• Weekly, Monthly, Quarterly, Annual …• Any day of month• Annual Value Ranges from £1 to £2,700
Multiple Payment Methods• Direct Debit, Standing Order, Cash, Card…
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= 10 million rows of complex commitment payment data• room for mis-interpretation • the need for a robust, programmable, yet simple technique
Introducing Survival Analysis
• PDSA use Descriptive Survival Analysis to measure the cancellation of regular giving commitments over time, this produces a survival curve, that can be sliced and diced by any definable criteria.
• What is Survival Analysis?Allows analysis of time to (recurrent) events, lending itself perfectly to regular giving
• Why use Survival Analysis?– Can analyse commitments together, irrespective of signing date, date of first payment
etc. as all commitments are aligned together, back to time 0 ( date of first payment)– You do not need the same volume in your comparison segments– Consistent methodology that can be applied across multiple regular giving products
and produces output understood by non analysts– You don’t need to be a statistician to apply the method to your data– You can automate the calculations allowing the easy refresh of regular reports
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Tools for Descriptive Survival Analysis
• Began with SPSS Survival Analysis Module, but have successfully applied technique into regular reports using FastStats Discoverer, FastStats Excelsior and Microsoft Excel
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• Derive age of Commitment*• Date of First Payment• Date of Last Payment
(or date of analysis if still active)
• Run frequencies by age of commitment and required categorisation (campaign, product etc)
• Started commitments• Attrited commitments
• Import FastStats cubes and trees into Excel using FastStats Excelsior
• Calculate survival curve in excel
* We measure this in months rather than number of payments due to the mix of products and payment plans
1,000 57 5.70% 939 382 40.68% £72.101,500 54 3.60% 1,433 935 65.24% £77.082,000 240 12.00% 1,752 984 56.16% £33.812,500 518 20.70% 1,983 345 17.40% £79.573,000 660 22.00% 2,340 900 38.46% £98.82
%of Commitments Still
Paying
Average Annual Value
Non Starters Non Starter RateNumber of
Commitments Started
Product DProduct E
Number of Commitments Still
Paying
Number of Commitments
RecruitedProduct
Product AProduct BProduct C
Survival Analysis…. By Regular Giving Product(This is fictional data!)
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A misleading statistic that can not be used to compare products as not all commitments began at the same point in time
Non Starters are removed before analysis, but need to be considered in further applications
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Months from Initial Sign Up
Survival Analysis% of Commitments Surviving
Product A
Product B
Product C
Product D
Product E
Product C is an established product with
more history to analyse
Product E is a relatively new
product
Health Warnings : Know your data to make sure you are making fair comparisons…
•Has Product D poor survival because of the product, or because of the recruitment channel?
•Would we use this these survival curves to predict survival of newly recruited commitments?
(For forecasting, PDSA limit analysis to commitments recruited in last 3 years)
Survival Analysis…. By Demographics(This is fictional data!)
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Supporter Lifestage Comparison Report
1,000 74 7.40% 924 230 24.89% £66.351,500 90 6.00% 1,407 551 39.13% £76.802,000 130 6.50% 1,870 928 49.63% £64.922,500 175 7.00% 2,325 733 31.51% £66.213,000 177 5.90% 2,817 1,314 46.65% £62.02
Thriving & Thrifty Families (L)
Supporter LifestageNumber of
Commitments Recruited
Non Starters Non Starter RateNumber of
Commitments Started
Number of Commitments Still
Paying
Penny-wise Pensioners (S)
%of Commitments Still
Paying
Average Annual Value
Accomplished Singles (A)Unattached Traditionalists (E)Contemporary Elders (G)
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Survival Analysis% of Commitments Surviving
Accomplished Singles (A)
Unattached Traditionalists (E)
Contemporary Elders (G)
Thriving & Thrifty Families (L)
Penny-wise Pensioners (S)
Survival Analysis…. Applications
• Information and Insight– Regular Reports using excelsior update survival analysis with ease, providing up
to date information on performance of regular giving campaigns, products, segments
– Inform targeting decisions– Has been most useful in understanding the effect of economic climate of regular
giving
• Scenario Planning– If I had £50,000, where is it best spent?– Applying survival curves to assumed campaign performance statistics results in
an income stream and break even point
• Regular Giving Budgeting Process– Applying survival curves to existing commitments and expected acquisition has
proven to boost budgeting accuracy and streamline process
• Predicting Individual Supporters Likelihood to Attrite– PDSA currently use CHAID to identify Supporters at risk of attrition, but are
investigating the application of survival analysis
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