analytics
Tired of the Same Results? Look at Data Differently! How our Advancement Services team helped our Fundraisers grow the Donor Societies.
Tired of the Same Results? Look at Data Differently! Elana Mendelson Prospect Researcher
Mark Mathyer Manager, Development & Membership Services
Title
We can't solve problems by using the same kind of thinking we used when we created them. - Albert Einstein
Giving Structure at MSI (Traditional)
Casual Givers
Regular Givers • Members hips
$50 to $200 range
• ???
$250 to $999 range
• Donor Societies
$1000 and up range
“There are no donors in that range.”
“There are no donors in that range.”
How to fill the Gap?
Members • 45% to 50% of Donor Societies • Members retention in Donor Societies
But they didn’t respond…
Branding was different • Society vs. Membership
Renewal Cycle was different • Yearly by Calendar vs. 12 months
Message was different • Support vs. Access
So, we changed something…
Made Donor Levels look like Memberships • $250 - $499 became Explorers • $500 - $999 became Catalyst
Special Asks to Members • Benefits aligned to traditional memberships • Renewal cycle like traditional memberships
So, we changed something…
The longer view:
Title
Learning Objectives 1. What is ANALYTICS? And, understand how it is used in fundraising. 2. How to get ANALYTICS buy-in from your fundraising staff. 3. Get ideas about how to make ANALYTICS work for your organization.
How do we think about analytics Analytics: It’s made up of 3 primary components 1. The process of gathering data 2. Analyzing the data 3. Turning into actionable information to make fact based decisions
What can analytics be to you?
Time consuming Worth the effort Expensive* ROI A process An Experience Risky* Rewards FUN!* Rewarding!
*Caveat: a warning or proviso of specific stipulations, conditions, or limitations.
3 Ways to engage w/analytics Outsource In
House A Little
of Both
Isn’t this just reporting? “(Please) give me a list of all donors from the XYZ Campaign.”
Instead, let’s analyze by asking
What is the objective? Do you want to know?: • Who in the database shows the most promise as a potential donor? • Who is the best group of people to invite to a high-end event? • What prompts a $1K donor to give that amount? Cultivation? Event? Nothing? • What does our reactivation rate look like?
See other sample questions in the appendix
Predictive modeling and how it works •Patterns •Variables •Correlation •Causation (& using your brain)
Before You Begin Truths & Lies •Expect that analytics cannot happen overnight •Most of the development staff will not understand •You may think you are a dimwit •Mistakes WILL occur
Draft a Plan Buy and/or Build? Data Appends
Buy In & Compromise
Present Plan Revise Plan Champions Testing The proof is in the….
What’s Next?
More Analysis of Donor Behavior
Find more Gaps
New Research Tools
New Data Sets
THANK YOU!
This presentation can be found:: http://aasp13datadifferent.weebly.com/ OR http://tinyurl.com/datadifferent
Elana Mendelson [email protected]
Mark Mathyer [email protected]
Analytics Related Resources Websites/Blogs
Web Address
APRA International
www.aprahome.org
The Helen Brown Group Blog
www.helenbrowngroup.com
npENGAGE – Analytics Blog
http://www.npengage.com/analytics/
Articles
Web Address
Here’s to the Skeptics: Addressing Predictive Modeling Misconceptions
http://tinyurl.com/pzaqxav
Analytics: Taking the First Step
http://www.npengage.com/analytics/analyticstaking-the-first-step/#sthash.8XGS0pJ9.dpuf
Books
Author
Fundraising Analytics: Using Data to Guide Strategy
Joshua Birkholz
Appendix Sample questions for analysis What annual events can be cut from our budget? Who in the database shows the most promise as a potential donor? Who is the best group of people to invite to a high-end event? What prompts a $1K donor to give that amount? Cultivation? Event? Nothing? What does the ideal direct mail calendar look like?
Transition Slide
Tired of the Same Results? Look at Data Differently! Elana Mendelson Prospect Researcher
Mark Mathyer Manager, Development & Membership Services
Title
We can't solve problems by using the same kind of thinking we used when we created them. - Albert Einstein
Giving Structure at MSI (Traditional)
Casual Givers
Regular Givers • Members hips
$50 to $200 range
• ???
$250 to $999 range
• Donor Societies
$1000 and up range
“There are no donors in that range.”
“There are no donors in that range.”
How to fill the Gap?
Members • 45% to 50% of Donor Societies • Members retention in Donor Societies
But they didn’t respond…
Branding was different • Society vs. Membership
Renewal Cycle was different • Yearly by Calendar vs. 12 months
Message was different • Support vs. Access
So, we changed something…
Made Donor Levels look like Memberships • $250 - $499 became Explorers • $500 - $999 became Catalyst
Special Asks to Members • Benefits aligned to traditional memberships • Renewal cycle like traditional memberships
So, we changed something…
The longer view:
Title
Learning Objectives 1. What is ANALYTICS? And, understand how it is used in fundraising. 2. How to get ANALYTICS buy-in from your fundraising staff. 3. Get ideas about how to make ANALYTICS work for your organization.
How do we think about analytics Analytics: It’s made up of 3 primary components 1. The process of gathering data 2. Analyzing the data 3. Turning into actionable information to make fact based decisions
What can analytics be to you?
Time consuming Worth the effort Expensive* ROI A process An Experience Risky* Rewards FUN!* Rewarding!
*Caveat: a warning or proviso of specific stipulations, conditions, or limitations.
3 Ways to engage w/analytics Outsource In
House A Little
of Both
Isn’t this just reporting? “(Please) give me a list of all donors from the XYZ Campaign.”
Instead, let’s analyze by asking
What is the objective? Do you want to know?: • Who in the database shows the most promise as a potential donor? • Who is the best group of people to invite to a high-end event? • What prompts a $1K donor to give that amount? Cultivation? Event? Nothing? • What does our reactivation rate look like?
See other sample questions in the appendix
Predictive modeling and how it works •Patterns •Variables •Correlation •Causation (& using your brain)
Before You Begin Truths & Lies •Expect that analytics cannot happen overnight •Most of the development staff will not understand •You may think you are a dimwit •Mistakes WILL occur
Draft a Plan Buy and/or Build? Data Appends
Buy In & Compromise
Present Plan Revise Plan Champions Testing The proof is in the….
What’s Next?
More Analysis of Donor Behavior
Find more Gaps
New Research Tools
New Data Sets
THANK YOU!
This presentation can be found:: http://aasp13datadifferent.weebly.com/ OR http://tinyurl.com/datadifferent
Elana Mendelson [email protected]
Mark Mathyer [email protected]
Analytics Related Resources Websites/Blogs
Web Address
APRA International
www.aprahome.org
The Helen Brown Group Blog
www.helenbrowngroup.com
npENGAGE – Analytics Blog
http://www.npengage.com/analytics/
Articles
Web Address
Here’s to the Skeptics: Addressing Predictive Modeling Misconceptions
http://tinyurl.com/pzaqxav
Analytics: Taking the First Step
http://www.npengage.com/analytics/analyticstaking-the-first-step/#sthash.8XGS0pJ9.dpuf
Books
Author
Fundraising Analytics: Using Data to Guide Strategy
Joshua Birkholz
Appendix Sample questions for analysis What annual events can be cut from our budget? Who in the database shows the most promise as a potential donor? Who is the best group of people to invite to a high-end event? What prompts a $1K donor to give that amount? Cultivation? Event? Nothing? What does the ideal direct mail calendar look like?
Transition Slide
