Maximising DataA hospice success story                          1
Saint Francis Hospice                        2
About Saint Francis Hospice •   Catchment of 750,000 people •   25,000 active supporters •   20,000 inactive supporters (l...
Objectives for the Project• Enhance existing relationships• Grow supporter base• More effective marketing• ThankQ• Skills ...
Drivers for the Project• Awareness levels patchy over such a large  catchment area• Three childrens’ hospices who compete ...
Other influencing drivers• Tried multiple approaches to engage  audiences – raffles, sponsor a nurse, light up a  life, ge...
Pulling together data• Source – where have they come from?• Length of time on database – when did they first  interact wit...
Supporter Segmentation?•   Different types of supporters•   Where are they now in their life cycle?•   Where do we want to...
Supporter Segmentation• Types of information to      • Social media –  collect to enable better       Facebook, Twitter.  ...
Assembli Supporter Profile             Analysis• Penetration assessment by Post Code• Socio demographic profile by Post Co...
Profile Model – closeness of fitSegment 4    (71<Tenure) AND (54<Age) AND (60<Urbanicity<=65)Segment 16   (85<Tenure) AND ...
Profile Model – closeness of fit                             Customers                    Base                  Penetratio...
Segment geographyClosest fit    Furthest fit                              13
Observations @SFH• Lots of supporters - lots of one off donations!• Supporters being silo’d – Once an IMO giver,  always a...
The ApproachThe                 proposal recommended threedistinct phases:Phase 1 – Profile the data & understand the curr...
Phase 2 - Step 1 – ‘As Is’Determined this via  • Workshops with teams to map ‘As is’ processes –    Events; Community; IMO...
17
Step 2 – ‘To be’Once ‘lie of land’ known, issues aired, and ‘bluesky thinking’ begun, investigated what waswanted via work...
The classic donor pyramid                            19
A key to success is…                       20
Three things…  1. I want  2. I give   3. I get                21
Individual Giver                                          Thank You                                                       ...
Sponsorer                                                                                    Thank You                    ...
Where next?• Partnership working to find an automated approach  to donor journey administration and management  via the da...
Individual Giver - DevelopmentJoe andJoanne       Enquirer     Passive Public                   Interest                  ...
Early Days – Outcomes so far•   IMO 50% give once – value £200k per annum•   50% made a repeat donation £100k•   70 IMO gi...
Outcomes continued• Tribute Funds 0 to 70 = £80k in first year – all  moved from IMO giving.                    “One way o...
Going forward• Donor Development Manager in budget to work across all  fundraising streams looking at cross fertilisation ...
Any Questions?                 29
Thank YouJane FrameDirector of Fundraising & Marketingjaneframe@sfh.org.ukDawn VarleyConsultantdawn.varley@purple-vision.c...
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Saint Francis & Purple Vision NAHF Presentation 24/3/12

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  • Saint Francis Hospice offers excellent care fore those with life limiting illnesses throughout outer East London. The catchment area of the hospice is just under one million people (750,000). The hospice works alongside 5 different primary care trusts, each with the own contract of care which is negotiated on an annual basis. The levels of service do not increase annually with the increasing levels of patient care and in fact over the last 3 years as the hospice has moved even further to home care and home nursing increase in patient care leavles have been absorbed. Saint Francis has a large team of clinical staff – 3 consultants, two of which are totally community facing and a team of 30 CNS and home care nurses working in patients homes. The PCT contracts overall are reducing slightly for this year – by about 4% £350,000 and voluntary giving has been tasked with making up this shortfall and growing income by a further £150k next year £500k growth in total. We therefore need to be efficient in our fundraising especially as our catchment area remains the same. Therefore we need to get more from existing supporters and retain them for much longer and we know that personal supporter journeys will help us achieve our goals.
  • Saint Francis & Purple Vision NAHF Presentation 24/3/12

    1. 1. Maximising DataA hospice success story 1
    2. 2. Saint Francis Hospice 2
    3. 3. About Saint Francis Hospice • Catchment of 750,000 people • 25,000 active supporters • 20,000 inactive supporters (lapsed 2 - 6 yrs) • 20,000 comatosed (not given last 6 years +) • Hospice needs £7.7 million • £10 per person (catchment) • CRUK £6 per person (catchment) 3
    4. 4. Objectives for the Project• Enhance existing relationships• Grow supporter base• More effective marketing• ThankQ• Skills and experience and time werelimited – Purple Vision 4
    5. 5. Drivers for the Project• Awareness levels patchy over such a large catchment area• Three childrens’ hospices who compete heavily• Cold recruitment difficult/costly particularly in low awareness areas• Cause creates a natural source of new supporters – but does it encourage them to keep on giving? 5
    6. 6. Other influencing drivers• Tried multiple approaches to engage audiences – raffles, sponsor a nurse, light up a life, general appeal- bit hit and miss.• Lots of supporters making one off donations.• Nature of cause – doesn’t assist with the need for continued support?• More than 70% of our IMO givers don’t give again – need a reason to repeat.• At least 20% of people affected are under 40! 6
    7. 7. Pulling together data• Source – where have they come from?• Length of time on database – when did they first interact with the hospice?• How do they support – what type of giving – IMO, regular, value?• What have they been asked to do?• What are the motivations for giving? 7
    8. 8. Supporter Segmentation?• Different types of supporters• Where are they now in their life cycle?• Where do we want to take them?• How old are they really?• How loyal are they really?• Is the hospice a mainstream charity for them?• 4000 people cared for – does that mean at least 4000 new supporters on the database each year? 8
    9. 9. Supporter Segmentation• Types of information to • Social media – collect to enable better Facebook, Twitter. segmentation: • Frequency of use• How would you like to • Know about hospice receive our newsletter/ facebook page?• Frequency • Cards and Gifts?• Format • Events –• Raffles – like to receive? Challenge/Corporate• Light up a Life – take (Ball, Golf ) part? 9
    10. 10. Assembli Supporter Profile Analysis• Penetration assessment by Post Code• Socio demographic profile by Post Code compared to region• Mapping of – Penetration – Concentrations of matched potential supporters• Assessment of potential supporter base• Implications for future strategy
    11. 11. Profile Model – closeness of fitSegment 4 (71<Tenure) AND (54<Age) AND (60<Urbanicity<=65)Segment 16 (85<Tenure) AND (54<Age) AND (65<Urbanicity<=83)Segment 7 (71<Tenure<=85) AND (54<Age) AND (65<Urbanicity<=83)Segment 10 (71<Tenure) AND (Age<=54) AND (72<Property) AND (60<Urbanicity<=83)Segment 8 (40<Tenure<=71) AND (56<Age) AND (62<Urbanicity<=83)Segment 3 (71<Tenure) AND (Age<=54) AND (Property<=72) AND (60<Urbanicity<=83)Segment 15 (32<Tenure<=71) AND (45<Spend) AND (Age<=56) AND (60<Urbanicity<=88)Segment 9 (40<Tenure<=71) AND (Education<=46) AND (56<Age) AND (83<Urbanicity)Segment 11 (71<Tenure) AND (63<Age) AND (83<Urbanicity)Segment 20 (11<Income) AND (Tenure<=40) AND (56<Age) AND (Children<=50)Segment 18 (71<Tenure) AND (82<Spend) AND (Urbanicity<=60)Segment 14 (32<Tenure<=71) AND (Spend<=45) AND (Age<=56) AND (60<Urbanicity<=88)Segment 19 (40<Tenure<=71) AND (46<Education) AND (56<Age) AND (83<Urbanicity)Segment 6 (40<Tenure<=71) AND (56<Age) AND (Urbanicity<=62)Segment 22 (Tenure<=32) AND (25<Spend) AND (Age<=56) AND (60<Urbanicity<=88)Segment 17 (Tenure<=40) AND (Education<=29) AND (56<Age) AND (50<Children)Segment 5 (Income<=11) AND (Tenure<=40) AND (56<Age) AND (Children<=50)Segment 2 (71<Tenure) AND (Age<=63) AND (83<Urbanicity)Segment 0 (Tenure<=71) AND (Age<=56) AND (Urbanicity<=60) AND (Retail<=43)Segment 1 (71<Tenure) AND (Spend<=82) AND (Urbanicity<=60)Segment 24 (Tenure<=40) AND (29<Education) AND (56<Age) AND (50<Children)Segment 13 (Tenure<=32) AND (Spend<=25) AND (Age<=56) AND (60<Urbanicity<=88)Segment 23 (Tenure<=71) AND (38<Age<=56) AND (88<Urbanicity)Segment 12 (Tenure<=71) AND (Education<=36) AND (Age<=38) AND (88<Urbanicity<=90)Segment 28 (Tenure<=71) AND (36<Education) AND (Age<=38) AND (88<Urbanicity<=90)Segment 27 (Tenure<=71) AND (38<Spend) AND (Age<=56) AND (Urbanicity<=60) AND (43<Retail)Segment 26 (Tenure<=71) AND (39<Occupation) AND (Age<=38) AND (90<Urbanicity)Segment 21 (Tenure<=71) AND (Spend<=38) AND (Age<=56) AND (Urbanicity<=60) AND (43<Retail)Segment 25 (Tenure<=71) AND (Occupation<=39) AND (Age<=38) AND (90<Urbanicity)
    12. 12. Profile Model – closeness of fit Customers Base Penetration Z-Score Index Assembli Model Counts % Counts % % 0 100 200Segments Segment 4 1582 11.7 10311 3.0 15.3 9 396 ██████████ >200 Segment 16 1206 8.9 10017 2.9 12.0 7 311 ██████████ >200 Segment 7 980 7.2 10008 2.9 9.8 6 253 ██████████ >200 Segment 10 958 7.1 10183 2.9 9.4 6 243 ██████████ >200 Segment 8 1418 10.5 16860 4.8 8.4 6 217 ██████████ >200 Segment 3 950 7.0 15953 4.6 6.0 3 154 █████ Segment 15 661 4.9 12749 3.7 5.2 2 134 ███ Segment 9 540 4.0 10787 3.1 5.0 2 129 ███ Segment 11 534 4.0 10760 3.1 5.0 2 128 ███ Segment 20 565 4.2 14191 4.1 4.0 0 103 Segment 18 377 2.8 10391 3.0 3.6 0 94 █ Segment 14 497 3.7 15365 4.4 3.2 -1 84 ██ Segment 19 385 2.8 12085 3.5 3.2 -1 82 ██ Segment 6 404 3.0 13376 3.8 3.0 -2 78 ██ Segment 22 267 2.0 10391 3.0 2.6 -2 66 ███ Segment 17 232 1.7 10003 2.9 2.3 -3 60 ████ Segment 5 228 1.7 10115 2.9 2.3 -3 58 ████ Segment 2 352 2.6 17560 5.0 2.0 -5 52 █████ Segment 0 215 1.6 12063 3.5 1.8 -5 46 █████ Segment 1 158 1.2 10053 2.9 1.6 -5 41 ██████ Segment 24 159 1.2 10856 3.1 1.5 -6 38 ██████ Segment 13 152 1.1 10429 3.0 1.5 -6 38 ██████ Segment 23 253 1.9 17591 5.0 1.4 -8 37 ██████ Segment 12 120 0.9 10061 2.9 1.2 -7 31 ███████ Segment 28 82 0.6 10053 2.9 0.8 -10 21 ████████ Segment 27 74 0.5 10014 2.9 0.7 -11 19 ████████ Segment 26 74 0.5 10316 3.0 0.7 -11 19 ████████ Segment 21 48 0.4 12971 3.7 0.4 -19 10 █████████ Segment 25 47 0.3 13458 3.9 0.3 -21 9 █████████ - - - 0 0 Total 13518 348,970 3.87 12
    13. 13. Segment geographyClosest fit Furthest fit 13
    14. 14. Observations @SFH• Lots of supporters - lots of one off donations!• Supporters being silo’d – Once an IMO giver, always an IMO giver?• Recruiting cold – becoming more costly• Need to keep the ones we have and keep their interest – 80/20 rule – need to maximise the 20%! 14
    15. 15. The ApproachThe proposal recommended threedistinct phases:Phase 1 – Profile the data & understand the currentsupporter basePhase 2 – The Supporter Journey – reviewing the ‘AsIs’ and understanding the aspiration for the ‘To Be’Phase 3 – The reality of the Journey – turning thetheory into practice via database and processes 15
    16. 16. Phase 2 - Step 1 – ‘As Is’Determined this via • Workshops with teams to map ‘As is’ processes – Events; Community; IMO; Individual Giving; LUAL • As part of this ‘known issues’ and ‘would like to have’ points came out • Documented & back to teams for review • Process allowed opportunity to get ‘buy in’ from all teams 16
    17. 17. 17
    18. 18. Step 2 – ‘To be’Once ‘lie of land’ known, issues aired, and ‘bluesky thinking’ begun, investigated what waswanted via workshop to:• Identify all audience types going forward (not same as past)• Identify all products to be taken forward (not same as past)• Discuss, refine and model into ideal journeys 18
    19. 19. The classic donor pyramid 19
    20. 20. A key to success is… 20
    21. 21. Three things… 1. I want 2. I give 3. I get 21
    22. 22. Individual Giver Thank You Product (& GA) Thank You Part of Saint Francis Product Other Hospice (& GA) ways to Family support, Appeals eg events Sponsor a Thank You Nurse (etc Legacy Letter RG) Pledger Raffle/ Lottery Super- Supporter Welcome Active Pack interest, Regular Gift Supporter I want…to eg web, keep helping request I want…to do Passive Repeat once I’m gone info more than Interest Supporter give money eg leaflet I want…to Supporter make this anJoe and on-goingJoanne I want…to thing Public give when I Consumer can and I want…to maybe get help something back Enquirer I want…to Newsletter and e-newsletter (with targeted content) know about ‘my local I want to…know hospice’ what this is all 22 about
    23. 23. Sponsorer Thank You Legacy & Eventer Distinct Event types, eg Challenges (opt-in) Thank You Lifetime Giving Engaged Event Happens Distinct Evening supporter Event with Saint Event Info types, eg Francis Online Treks Hospice Regular Welcome Giving eg Pack & Website SAN, Reg. Facebook Payroll Just Giving Event Event Addict & Lifetime Welcome Support Giving Ambassador Pack Event Pack Event Hero Website I want…to do Facebook this again, Twitter this was fun Info Pack/ Event Leaflet/ Participant and makes a I website/ difference want…people mag etc Event to recognise Thrill- Enroller what I’veseeker/go- done getter I want…to do /activist Event this and do Enquirer this well! I want…to know the Event Info details Enquirer I want…to Newsletter and e-newsletter (with targeted content) know more about what I can do *It is acknowledged that the motivation for a potential I want…to do eventer isn’t always to support Saint Francis Hospice – it something* can simply be to do the event offered, via Charity of the Year, etc
    24. 24. Where next?• Partnership working to find an automated approach to donor journey administration and management via the database.• Review thanking process• Phone thank – easy to gather more intelligence• Follow – up process (determine what information is the most appropriate to send)• Lapsing – monitor monthly and ask why? Record this information. 24
    25. 25. Individual Giver - DevelopmentJoe andJoanne Enquirer Passive Public Interest Sent within x eg leaflet 1. Code all days response Info Pack/ devices, Leaflet Active record all interest, interactions Consumer eg web, request info Welcome Sent within x Newsletter and e-newsletter (with targeted content) Pack weeks 2a. Record Gift Supporter 2b. Record Welcome Pack response & tailor & target comms accordingly Thank You 3. Record Sent within x gifts/response & weeks Repeat use to derive next 2nd Appeal Supporter prompt. If no gift in x months offer If Lottery have Lottery? delayed upgrade/ conversion plan Lottery
    26. 26. Early Days – Outcomes so far• IMO 50% give once – value £200k per annum• 50% made a repeat donation £100k• 70 IMO givers moved to tribute fund• 754 Raffle purchasers now signed up to new lottery = £40,354• 754 Raffle players were giving £7540• Variance £32,814• 1000 cash donors now signed up to Sponsor a Nurse = £60,000 a year• 1000 cash donors were giving £8000• Variance £52,000 26
    27. 27. Outcomes continued• Tribute Funds 0 to 70 = £80k in first year – all moved from IMO giving. “One way or another, we’ve raised over £10,000 for the Derek Bundy Tribute Fund and I know Derek would be proud of us. Like so many families who have got to know Saint Francis Hospice, we wanted to give something back.” 27
    28. 28. Going forward• Donor Development Manager in budget to work across all fundraising streams looking at cross fertilisation of information and giving opportunities.• Plans to move towards more sophisticated journeys for every income streams and every type of supporter• Really still in the early stages of donor journey development as so much more to do.• Benefits – we know more about our supporters and they know more about us• Lessons learned – it takes time and resources. We will be spending more time keeping the supporters we have. 28
    29. 29. Any Questions? 29
    30. 30. Thank YouJane FrameDirector of Fundraising & Marketingjaneframe@sfh.org.ukDawn VarleyConsultantdawn.varley@purple-vision.com 30
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