Donor Insights:
a dull name for getting the real
lowdown on what your donors want,
think, believe and will respond to
Donor Insights:
a dull name for getting the real
lowdown on what your donors want,
think, believe and will respond to
Data Insights:
a dull name for getting the real
lowdown on what your donors want,
think, believe and will respond to
Who we’ve worked with
Who we’ve worked with
What we’ll cover
1. Data: what’s that all about
2. How to use insights
3. Insights in action
4. Critical data you need
5. ...
One: Data
What’s that all about?
Types of data available
• Environmental
- how much is given, growth, competition
• Analytical
- your growth, your donor be...
Using Environmental data
to benchmark
$0
$5
$10
$15
$20
$25
$0
$5,000,000
$10,000,000
$15,000,000
$20,000,000
$25,000,000
...
Using Analytical data
to answer these questions
• What is the biggest variable driving
attrition?
• What is the best time ...
Using Personal data to get closer
Two: how to use insights
Some real examples
Second gift rates worsening
Taking too long to get back and ask
• Develop a 2nd gift strategy designed to:
– Thank quicker
– Include a ‘non ask’ feedback letter before next ask
– Find th...
They found the optimum
time to ‘convert’
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
2 3 4 5 6 7 8 9 10 11
Week...
• Determine the best time to approach new
donors with a monthly conversion request
What this allowed the Heart
Foundation ...
• Determine the best time to approach new
donors with a monthly conversion request
• Look at ways to increase average gift...
• Determine the best time to approach new
donors with a monthly conversion request
• Look at ways to increase average gift...
-$200
-$100
$0
$100
$200
$300
$400
Ave VTD by Channel by Year
Ave Year 1 Net
Ave Year 2 Net
Ave Year 3 Net
Ave Year 4 Net
...
• Say things like:
“A donor acquired in 2005 by <insert channel>
is worth $450 whereas a donor acquired in
2005 by <insert...
• Say things like:
“A donor acquired in 2005 by <insert channel>
is worth $450 whereas a donor acquired in
2005 by <insert...
• Say things like:
“A donor acquired in 2005 by <insert channel>
is worth $450 whereas a donor acquired in
2005 by <insert...
What really drives attrition of
street recruits?
• Recruitment
Source
• Gender
• Payment Method
• Payment
Frequency
• Age
• Amount
• Email Provided
• Home Phone
• Work Pho...
Some really ugly, but useful
analysis
• Age is the most significant factor in predicting
Year 1 attrition
• Payment type is significant, with credit card
payers...
• Predict future value of supporters
• Prioritize spend
• Identify high risk supporters and treat them
differently
What th...
Monthly Givers: to mail or not to mail
No. of
donors
Terminated
Attrition
Rate
Total months
since 2008/01
Avg months
given
Total Value since
2008/01
Included 3,4...
EXTRA DONATIONS GENERATED
No. of donors
responded to
Appeal
Resp.
Rate
No. of
gifts for
Appeals
TOTAL
AMOUNT
RAISED
No. of...
• Prove that monthly donors will continue to give
onetime gifts
What this allowed them to do
Three: Insights in action
Your turn,
helping the Lost Dog’s Home
The Lost Dogs’ Home
State of Play: 2002
Struggling for 2nd Gifts
Most only giving once
Struggling to recruit
Appeals program stagnant
*2003 based on 3 staff + Graeme raising $500k
Where staff spent their time
Your challenge:
• As Development Director, what decisions
would you have made?
A recap
• Large focus on a struggling cash program
• Lots of time spent on events that weren't
making money
• Had scaled b...
So, what did they do?
• They told it like it was – Crisis appeal
So, what did they do?
• They told it like it was – Crisis appeal
• Got personal with donors
So, what did they do?
What makes them tick?
Got really personal
Got really personal
• They told it like it was – Crisis appeal
• Got personal with donors
• Focused on areas of growth – monthly giving,
beque...
• They told it like it was – Crisis appeal
• Got personal with donors
• Focused on areas of growth – monthly giving,
beque...
• They told it like it was – Crisis appeal
• Got personal with donors
• Focused on areas of growth – monthly giving,
beque...
Did it work?
$0
$100,000
$200,000
$300,000
$400,000
$500,000
$600,000
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
This purpl...
Yes. In the medium term.
From 98 to 10,330 active
monthly donor’s
$1.5m CAD a year
Yes. In the long term.
5.7% of their active donors have confirmed
they are leaving a bequest – that’s 1,649
donors
Yes. In the long term.
Four: Critical data you need
Look beyond the simple measures
A Recap: Types of data available
• Environmental
- how much is given, growth, competition
• Analytical
- your growth, your...
A Recap: Data you must have
• Environmental
- how much is given, growth, competition
• Analytical
- your growth, your dono...
A Recap: Data you must have
• Environmental
– Understand where growth is coming from
– Look around at what others are doin...
A Recap: Data you must have
• Analytical
– Look deeper than top line measures
• Net Income v ROI
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
ROI
R…
Why...
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
ROI
Net
RO...
A Recap: Data you must have
• Analytical
– Look deeper than top line measures
• Net Income v ROI
• Net value to data v cos...
• You want to be able to say:
“A donor acquired in 2005 by <insert channel>
is worth $450 whereas a donor acquired in
2005...
A Recap: Data you must have
• Analytical
– Look deeper than top line measures
• Net Income v ROI
• Net value to data v cos...
Do you really know if your ask
really works?
A Recap: Data you must have
• Personal
– Find the ‘emotional triggers’
– Play it back. Getting closer builds long term val...
Data + Intelligence =
Insights
Remember..
Five: bringing it all together
What to do when you
leave the room
• Scan environmental data to look at what
others are doing
Final takeaways
• Scan environmental data to look at what
others are doing
• Dig deeper within your analytical data
Final takeaways
• Scan environmental data to look at what
others are doing
• Dig deeper within your analytical data
• Get personal with yo...
• Scan environmental data to look at what
others are doing
• Dig deeper within your analytical data
• Get personal with yo...
• Scan environmental data to look at what
others are doing
• Dig deeper within your analytical data
• Get personal with yo...
Ultimately,
let’s not forget…
Ultimately,
let’s not forget…
Data = People
Ultimately,
let’s not forget…
Data = People
And people are good.
Even at age 101,
Ethel Perrin is committed to helping
children in need.
This sprightly great-grandmother has
dedicated her life to helping
impoverished children nationally and
internationally.
This sprightly great-grandmother has
dedicated her life to helping
impoverished children nationally and
internationally.
E...
She then sponsored two aboriginal
boys in Canada. With five children
of her own, Ethel and her family
were more than happy...
She then sponsored two aboriginal
boys in Canada. With five children
of her own, Ethel and her family
were more than happy...
Since joining in 2004, Ethel has
continued to be a generous
supporter of Canadian Feed the
Children’s programs.
Since joining in 2004, Ethel has
continued to be a generous
supporter of Canadian Feed the
Children’s programs.
Nowadays, ...
Ethel explains her situation like this:
Ethel explains her situation like this:
“I can’t walk, I can’t sit up
too well, but my hands are fine,
and as long as my h...
This man by the name of Tony
called the Breast Cancer Foundation
of Singapore one day…
QuickTime™ and a
decompressor
are n...
…to say that he was auctioning a
collection of coins belonging to his
sister Cheryl, who had died of breast
cancer.
…to say that he was auctioning a
collection of coins belonging to his
sister Cheryl, who had died of breast
cancer.
Prior ...
Cheryl found great comfort from the
visit of the counsellor and the help
from the Breast Cancer Foundation.
Upon Cheryl’s death, Tony felt that a
good way of appreciating the service
and commitment of the Breast
Cancer Foundation…
Upon Cheryl’s death, Tony felt that a
good way of appreciating the service
and commitment of the Breast
Cancer Foundation…...
He raised $11,000...
Sue, a donor from Ohio,
demonstrated a high level of passion
and personal commitment to
Operation Smile.
QuickTime™ and a
...
Sue has recently helped more than
53 children receive new smiles
through per personal donations and
fundraising.
Sue has recently helped more than
53 children receive new smiles
through per personal donations and
fundraising.
Sue first...
At that time she called and made a
$240 donation for a single smile
surgery.
At that time she called and made a
$240 donation for a single smile
surgery.
Later, moved by what she had
learned, Sue car...
Sue is a hairdresser and with the
support of co-workers, she
established an “Operation Smile
Day” each month at her shop w...
But she didn’t stop there...
Sue then took the next step and
made a commitment to hold a
fundraising event and organized a
special evening in April.
Sue then took the next step and
made a commitment to hold a
fundraising event and organized a
special evening in April.
Al...
Sue and her friend raised $12,766…
Last year an old man walked into the
Princess Margaret Hospital
Foundation, straight off the street
and wanted to speak to...
In his hand he had an envelope.
He sat down and got straight
to the point.
In his hand he had an envelope.
He sat down and got straight
to the point.
He had just sold a home unit and he
didn’t need...
After making sure that he would
never be identified…
After making sure that he would
never be identified…
he took out of the envelope a bank
cheque for $375,000,
crossed out h...
He then said that he was
86 years old and that
“there will be more for you in the
future, but don’t give your hopes up
as ...
Ultimately,
let’s not forget…
Ultimately,
let’s not forget…
Data = People
Ultimately,
let’s not forget…
Data = People
And people are good.
The Pareto Group exists to make the world a
better place, by expanding the not-for-profit
sector's capacity worldwide to e...
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
Afp Congress Pres 2009 Jg Final
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  • Events 0%Appeals 20%Acquisiton 25%Trusts & grants 10%Corporate 0%Regular giving 25%Legacies 20%
  • Afp Congress Pres 2009 Jg Final

    1. 1. Donor Insights: a dull name for getting the real lowdown on what your donors want, think, believe and will respond to
    2. 2. Donor Insights: a dull name for getting the real lowdown on what your donors want, think, believe and will respond to
    3. 3. Data Insights: a dull name for getting the real lowdown on what your donors want, think, believe and will respond to
    4. 4. Who we’ve worked with
    5. 5. Who we’ve worked with
    6. 6. What we’ll cover 1. Data: what’s that all about 2. How to use insights 3. Insights in action 4. Critical data you need 5. Bringing it all together
    7. 7. One: Data What’s that all about?
    8. 8. Types of data available • Environmental - how much is given, growth, competition • Analytical - your growth, your donor behavior • Personal - transactions, bequest status, motivations
    9. 9. Using Environmental data to benchmark $0 $5 $10 $15 $20 $25 $0 $5,000,000 $10,000,000 $15,000,000 $20,000,000 $25,000,000 $30,000,000 $35,000,000 $40,000,000 2002 2003 2004 2005 2006 2007 2008 2009 Total Income Avg Gift
    10. 10. Using Analytical data to answer these questions • What is the biggest variable driving attrition? • What is the best time to ask for a 2nd gift? • Are my donors giving at the level I ask them? • Which acquisition source delivers the best value?
    11. 11. Using Personal data to get closer
    12. 12. Two: how to use insights Some real examples
    13. 13. Second gift rates worsening
    14. 14. Taking too long to get back and ask
    15. 15. • Develop a 2nd gift strategy designed to: – Thank quicker – Include a ‘non ask’ feedback letter before next ask – Find the best time to ask for a 2nd gift – Focus on monthly giving What this allowed BC Cancer to do
    16. 16. They found the optimum time to ‘convert’ 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0% 2 3 4 5 6 7 8 9 10 11 Weeks since Gift Converted
    17. 17. • Determine the best time to approach new donors with a monthly conversion request What this allowed the Heart Foundation to do
    18. 18. • Determine the best time to approach new donors with a monthly conversion request • Look at ways to increase average gift value at point of recruitment – As higher value recruits more likely to ‘convert’ What this allowed the Heart Foundation to do
    19. 19. • Determine the best time to approach new donors with a monthly conversion request • Look at ways to increase average gift value at point of recruitment – As higher value recruits more likely to ‘convert’ • Understand that initial cash value drives future monthly value What this allowed the Heart Foundation to do
    20. 20. -$200 -$100 $0 $100 $200 $300 $400 Ave VTD by Channel by Year Ave Year 1 Net Ave Year 2 Net Ave Year 3 Net Ave Year 4 Net Getting the real lowdown: Net Value to Date
    21. 21. • Say things like: “A donor acquired in 2005 by <insert channel> is worth $450 whereas a donor acquired in 2005 by <insert channel> is worth $200” What this allowed SickKids to do
    22. 22. • Say things like: “A donor acquired in 2005 by <insert channel> is worth $450 whereas a donor acquired in 2005 by <insert channel> is worth $200” • Focus on areas generating the best real return What this allowed SickKids to do
    23. 23. • Say things like: “A donor acquired in 2005 by <insert channel> is worth $450 whereas a donor acquired in 2005 by <insert channel> is worth $200” • Focus on areas generating the best real return • Understand implications of future program decisions What this allowed SickKids to do
    24. 24. What really drives attrition of street recruits?
    25. 25. • Recruitment Source • Gender • Payment Method • Payment Frequency • Age • Amount • Email Provided • Home Phone • Work Phone • Mobile Phone What really drives attrition of street recruits?
    26. 26. Some really ugly, but useful analysis
    27. 27. • Age is the most significant factor in predicting Year 1 attrition • Payment type is significant, with credit card payers more likely to attrite Insights: what we found
    28. 28. • Predict future value of supporters • Prioritize spend • Identify high risk supporters and treat them differently What this allowed Amnesty to do
    29. 29. Monthly Givers: to mail or not to mail
    30. 30. No. of donors Terminated Attrition Rate Total months since 2008/01 Avg months given Total Value since 2008/01 Included 3,434 287 8.36% 54,510 15.87 $14,334,329 Excluded 3,433 295 8.59% 53,979 15.72 $13,176,515 Monthly Givers: to mail or not to mail
    31. 31. EXTRA DONATIONS GENERATED No. of donors responded to Appeal Resp. Rate No. of gifts for Appeals TOTAL AMOUNT RAISED No. of Other Gifts Amount raised from Other Gifts Included 896 26.09% 1,184 $1,080,230 219 $574,841 Excluded 0 0.00% 0 0 273 $239,319 Monthly Givers: to mail or not to mail
    32. 32. • Prove that monthly donors will continue to give onetime gifts What this allowed them to do
    33. 33. Three: Insights in action Your turn, helping the Lost Dog’s Home
    34. 34. The Lost Dogs’ Home
    35. 35. State of Play: 2002
    36. 36. Struggling for 2nd Gifts
    37. 37. Most only giving once
    38. 38. Struggling to recruit
    39. 39. Appeals program stagnant
    40. 40. *2003 based on 3 staff + Graeme raising $500k Where staff spent their time
    41. 41. Your challenge: • As Development Director, what decisions would you have made?
    42. 42. A recap • Large focus on a struggling cash program • Lots of time spent on events that weren't making money • Had scaled back spend on acquisition • Elderly database • Spend or close their doors
    43. 43. So, what did they do?
    44. 44. • They told it like it was – Crisis appeal So, what did they do?
    45. 45. • They told it like it was – Crisis appeal • Got personal with donors So, what did they do?
    46. 46. What makes them tick?
    47. 47. Got really personal
    48. 48. Got really personal
    49. 49. • They told it like it was – Crisis appeal • Got personal with donors • Focused on areas of growth – monthly giving, bequests So, what did they do?
    50. 50. • They told it like it was – Crisis appeal • Got personal with donors • Focused on areas of growth – monthly giving, bequests • Were prepared to spend now, reap returns later So, what did they do?
    51. 51. • They told it like it was – Crisis appeal • Got personal with donors • Focused on areas of growth – monthly giving, bequests • Were prepared to spend now, reap returns later • Looked at what others were doing So, what did they do?
    52. 52. Did it work?
    53. 53. $0 $100,000 $200,000 $300,000 $400,000 $500,000 $600,000 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 This purple block represents income from the first appeal using the new strategy - to the same donors Yes. In the short term.
    54. 54. Yes. In the medium term. From 98 to 10,330 active monthly donor’s $1.5m CAD a year
    55. 55. Yes. In the long term. 5.7% of their active donors have confirmed they are leaving a bequest – that’s 1,649 donors
    56. 56. Yes. In the long term.
    57. 57. Four: Critical data you need Look beyond the simple measures
    58. 58. A Recap: Types of data available • Environmental - how much is given, growth, competition • Analytical - your growth, your donor behavior • Personal - transactions, bequest status, motivations
    59. 59. A Recap: Data you must have • Environmental - how much is given, growth, competition • Analytical - your growth, your donor behavior • Personal - transactions, bequest status, motivations
    60. 60. A Recap: Data you must have • Environmental – Understand where growth is coming from – Look around at what others are doing – Benchmarking is about more than comparative data
    61. 61. A Recap: Data you must have • Analytical – Look deeper than top line measures • Net Income v ROI
    62. 62. $0 $50,000 $100,000 $150,000 $200,000 $250,000 $300,000 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 ROI R… Why ROI alone can be dangerous
    63. 63. $0 $50,000 $100,000 $150,000 $200,000 $250,000 $300,000 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 ROI Net ROI Why ROI alone can be dangerous
    64. 64. A Recap: Data you must have • Analytical – Look deeper than top line measures • Net Income v ROI • Net value to data v cost to acquire
    65. 65. • You want to be able to say: “A donor acquired in 2005 by <insert channel> is worth $450 whereas a donor acquired in 2005 by <insert channel> is worth $200” Cost to acquire is just one measure
    66. 66. A Recap: Data you must have • Analytical – Look deeper than top line measures • Net Income v ROI • Net value to data v cost to acquire • What you asked for v what was given
    67. 67. Do you really know if your ask really works?
    68. 68. A Recap: Data you must have • Personal – Find the ‘emotional triggers’ – Play it back. Getting closer builds long term value
    69. 69. Data + Intelligence = Insights Remember..
    70. 70. Five: bringing it all together What to do when you leave the room
    71. 71. • Scan environmental data to look at what others are doing Final takeaways
    72. 72. • Scan environmental data to look at what others are doing • Dig deeper within your analytical data Final takeaways
    73. 73. • Scan environmental data to look at what others are doing • Dig deeper within your analytical data • Get personal with your donors Final takeaways
    74. 74. • Scan environmental data to look at what others are doing • Dig deeper within your analytical data • Get personal with your donors • Be disciplined with your direct marketing Final takeaways
    75. 75. • Scan environmental data to look at what others are doing • Dig deeper within your analytical data • Get personal with your donors • Be disciplined with your direct marketing • Apply the Pareto Principle. Spend time where you will get the greatest return Final takeaways
    76. 76. Ultimately, let’s not forget…
    77. 77. Ultimately, let’s not forget… Data = People
    78. 78. Ultimately, let’s not forget… Data = People And people are good.
    79. 79. Even at age 101, Ethel Perrin is committed to helping children in need.
    80. 80. This sprightly great-grandmother has dedicated her life to helping impoverished children nationally and internationally.
    81. 81. This sprightly great-grandmother has dedicated her life to helping impoverished children nationally and internationally. Ethel’s first donation was a child sponsorship of a little girl in Pakistan.
    82. 82. She then sponsored two aboriginal boys in Canada. With five children of her own, Ethel and her family were more than happy to give what they could.
    83. 83. She then sponsored two aboriginal boys in Canada. With five children of her own, Ethel and her family were more than happy to give what they could. Over the years, she supported dozens of children in many countries throughout the world.
    84. 84. Since joining in 2004, Ethel has continued to be a generous supporter of Canadian Feed the Children’s programs.
    85. 85. Since joining in 2004, Ethel has continued to be a generous supporter of Canadian Feed the Children’s programs. Nowadays, Ethel crochets and knits quilts, which she sells to raise funds for CFTC.
    86. 86. Ethel explains her situation like this:
    87. 87. Ethel explains her situation like this: “I can’t walk, I can’t sit up too well, but my hands are fine, and as long as my hands work, I will keep making quilts to help children in need.”
    88. 88. This man by the name of Tony called the Breast Cancer Foundation of Singapore one day… QuickTime™ and a decompressor are needed to see this picture.
    89. 89. …to say that he was auctioning a collection of coins belonging to his sister Cheryl, who had died of breast cancer.
    90. 90. …to say that he was auctioning a collection of coins belonging to his sister Cheryl, who had died of breast cancer. Prior to Cheryl’s death, a volunteer counsellor with the Breast Cancer Foundation who was a breast cancer survivor herself, had visited her.
    91. 91. Cheryl found great comfort from the visit of the counsellor and the help from the Breast Cancer Foundation.
    92. 92. Upon Cheryl’s death, Tony felt that a good way of appreciating the service and commitment of the Breast Cancer Foundation…
    93. 93. Upon Cheryl’s death, Tony felt that a good way of appreciating the service and commitment of the Breast Cancer Foundation… was to donate the sum raised from the auction of his coins.
    94. 94. He raised $11,000...
    95. 95. Sue, a donor from Ohio, demonstrated a high level of passion and personal commitment to Operation Smile. QuickTime™ and a decompressor are needed to see this picture.
    96. 96. Sue has recently helped more than 53 children receive new smiles through per personal donations and fundraising.
    97. 97. Sue has recently helped more than 53 children receive new smiles through per personal donations and fundraising. Sue first learned about Operation Smile on TV back in December 2004.
    98. 98. At that time she called and made a $240 donation for a single smile surgery.
    99. 99. At that time she called and made a $240 donation for a single smile surgery. Later, moved by what she had learned, Sue carried the message of Operation Smile to her co-workers, customers and friends.
    100. 100. Sue is a hairdresser and with the support of co-workers, she established an “Operation Smile Day” each month at her shop where her tips and contributions by customers are donated to Operation Smile.
    101. 101. But she didn’t stop there...
    102. 102. Sue then took the next step and made a commitment to hold a fundraising event and organized a special evening in April.
    103. 103. Sue then took the next step and made a commitment to hold a fundraising event and organized a special evening in April. All proceeds were donated to Operation Smile.
    104. 104. Sue and her friend raised $12,766…
    105. 105. Last year an old man walked into the Princess Margaret Hospital Foundation, straight off the street and wanted to speak to the boss.
    106. 106. In his hand he had an envelope. He sat down and got straight to the point.
    107. 107. In his hand he had an envelope. He sat down and got straight to the point. He had just sold a home unit and he didn’t need the money.
    108. 108. After making sure that he would never be identified…
    109. 109. After making sure that he would never be identified… he took out of the envelope a bank cheque for $375,000, crossed out his name and endorsed it to the foundation.
    110. 110. He then said that he was 86 years old and that “there will be more for you in the future, but don’t give your hopes up as we live to a really old age!”
    111. 111. Ultimately, let’s not forget…
    112. 112. Ultimately, let’s not forget… Data = People
    113. 113. Ultimately, let’s not forget… Data = People
    114. 114. And people are good.
    115. 115. The Pareto Group exists to make the world a better place, by expanding the not-for-profit sector's capacity worldwide to ensure as many beneficiaries are helped as possible. jonathon.grapsas@paretofundraising.com www.jonathongrapsas.blogspot.com twitter: jonathongrapsas www.paretofundraising.com

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