This document discusses how larger and better data can help non-profits identify more major donors. It notes that while bigger data presents opportunities, data integrity is key to finding new donors. Data-driven philanthropy allows organizations to be innovative in tracking donor behaviors and metrics that matter, like affinity, and in managing the donor pipeline more effectively. Data can also help measure the impact of donations and guide investment decisions. Overall, data analysis has significant potential but must be done carefully and ethically to truly help organizations in their missions.

1. Will Bigger & Better Data Help Deliver More
Major Donors?
Ben Rymer &
Azadi Sheridan
Blackbaud Higher Education Summit
July 2016

2. Value of 2016
ST Rich List:
£575bn
A Huge Opportunity

3. ● Uncover patterns of behaviour
● Help us be timely, relevant & responsive
● Identify competitive advantages
● Say who will give
What Bigger and Better Data Can Do

4. ● Maintain or analyse itself
● Describe anything but the past
● Make decisions
● Say why donors give (yet!)
“What information consumes is rather obvious: it consumes the attention of its
recipients. Hence a wealth of information creates a poverty of attention” Professor
Herbert Simon
What Bigger and Better Data Can Do

5. What is Big Data?

7. Quiz
• Data Warehouse
• Data Analyst
• Data Scientist
• Data-Driven Decision
• Algorithm
• SQL
• No SQL

8. • High data volume,
variety, and/or
velocity ("3Vs")
• Expensive and
difficult

10. Big Data!
• 149 million players playing 1.5
billion levels per day
• > 1PB of data per year

12. What is big data?
• What are the most
popular items?
• How near is the
stock to the buyer?
• What will the most
popular items next
be?

15. BIG
DATA
SMALL
DATA

16. BIG
DATA
SMALL
DATA
EXPENSIVE TO FEED.
SOMEONE ELSE HUNTS FOR HIM.
KITTENS STILL MOST POPULAR
ANIMAL ON INTERNET

17. Proper Analysis
• Stats not gut instinct
• Bad Science – Ben Goldacre
• <10,000 = prone to statistical error
• Jeremy Corbyn is 14% more popular now than when elected leader
• Data is all around you
• But maybe not where you are looking for it

18. AARRR!!!

22. Back to Ben

23. Data in Philanthropy
Vertical:
Identifying ‘missing’ wealth
Targeting communications & activities
across the quantum of wealth
Internal:
Tracking performance
Pipeline management
Improving conversion ratios
Measuring donor engagement
Increasing donor retention
External
Benchmarking against leaders
Scoping opportunities
Innovative products
Horizontal:
Choosing frequency & channel of
communication
Being relevant, responsive & timely

24. Data’s role:
Identify more George Soros’s sooner!
Plan strategically once identified
Boost value by targeting asks
A Relationship Case Study

25. Summary
● Significant potential for growth in philanthropy
● Data integrity key to finding more major donors. Bigger data a
distraction?
● Data-driven Philanthropy is innovative. Try it, test it, improve it
● Above all, inspire and earn the respect of your alumni & donors

26. Back to Azadi

27. “Look for the One Metric That Matters”
Alistair Croll, Lean Analytics

28. British Airways
- Data Values

29. Data Drive Pipeline Management
• Manage by exception
• What is outlying data?
• What data indicates future good or bad performance?
• What is the one metric that matters?

30. Prospect Management vs
Performance Management
Performance Management
• Acquisition
• % First Mtg  Second Meeting
• Activation
• Event Sign-Ups %
• Retention
• Rolling Donor Duration Avg
• Revenue
• Referral
• Closed Proposals By Source
Prospects
• Propensity
• Capacity
• Affinity

31. Affinity

32. https://www.thinkwithgoogle.com/tools/customer-journey-to-
online-purchase.html#!/the-uk/people-and-
society/large/generic-paid-search

33. https://www.thinkwithgoogle.com/tools/customer-journey-to-
online-purchase.html#!/the-uk/people-and-
society/large/generic-paid-search

34. Digital Fundraising Data
• Social, viral or advertising drivers to website/ Track wider website
behaviour. (YouTube/ Facebook video is huge – don’t forget subtitles)
• Re-marketing to encourage conversion to Facebook like or Twitter
follower
• E-mail responsiveness
• Content engagement
• Calls to action
• Conversion to small asks – perhaps non-financial

36. Leading vs Trailing Indicators
Trailing
• Survey Results
• E-mail Opt-Outs
• Donation
• Addressee Goneaway
• Repeat Donation
Leading
• Survey Trends/ Comparisons
• Reduced Click-Throughs
• Event Attendances / Event
Apologies
• No Change of Address Info
• Gratitude for Stewardship
gifts/ Social Sharing

37. Data and…. Impact Investment
• $2m donation 
• $2m spent on Internet services 
• 4000 jobs created = Outcome
• 4000 * tax rate * average salary = Economic Impact (plus VAT)
• Supported by Randomised Control Tests =  and 
• Donation OR Payment/ Refunds by Results

38. BIG
DATA
SMALL
DATA
EXPENSIVE TO FEED.
SOMEONE ELSE HUNTS FOR HIM.
KITTENS STILL MOST POPULAR
ANIMAL ON INTERNET

39. Thanks!
Questions?
Answers?
Further reading:
http://customerinsightleader.com/opinion/whats-matter-metadata/
http://www.datasciencecentral.com/profiles/blog/show?id=6448529%3ABlogPost%3A379084
http://read.nxtbook.com/1to1media/customerstrategist/winter2015/perspectives_marketingdata.html
https://www.timeshighereducation.com/blog/know-your-geography-quantitative-skills-arent-just-about-maths
http://afpfep.org/wp-content/uploads/2015/02/Forget-About-BIG-Data-AFP-Journal-Winter-2015.pdf
http://npengage.com/nonprofit-news/5-troubling-nonprofit-statistics/
@martin_squires
@EdwardTufte
https://fundraisingvoices.wordpress.com/
https://tdwi.org/Articles/2015/10/06/Top-4-Myths-about-Big-Data.aspx?Page=2
https://www.ted.com/talks/ben_goldacre_battling_bad_science/transcript?language=en
https://www.oreilly.com/learning/analytics-frameworks-for-the-startup-lifecycle
rymer.ben@gmail.com
Azadi@Productle.com