The document discusses optimizing online fundraising through testing variations of webpage elements. It advocates testing all aspects of the fundraising process, from email subject lines and copy to landing page design, to maximize results. Several case studies are presented where split testing revealed significant lifts in key metrics like conversion rates and donations. The author argues that incremental improvements across the entire user journey, from awareness to conversion, can have large cumulative impacts on overall revenue. Regular testing is positioned as key to continuously improving performance and "leaving money on the table" by not optimizing processes.

1. Optimizing your online
fundraising
Nathaniel Ward
September 19, 2013

2. Let’s test your gut instincts

3. Version A …?

6. … or version B?

10. Here they are side by side

11. Version B outperforms version A
44.4% increase in conversion rate
95.14% confidence
3.3% increase in average gift
95.14% confidence
49.3% increase in revenue per visitor
From $4.76 to $7.11; 95.14% confidence

12. Let’s try another one

13. Version A … ?

15. … or version B?

17. Here they are side by side

18. Version B has a huge lift
134.1% increase in conversion rate
99.9% confidence
43.4% increase in average gift
99.9% confidence
236.3% increase in revenue per visitor
From $7.45 to $25.06

19. And these test results compound
49.3% increase in revenue per visitor
From $4.76 to $7.11
236.3% increase in revenue
From $7.45 to $25.06
Test 2: Donation form design
Test 1: Overall page design
426.4% increase in revenue
From $4.76 to $25.06
Cumulative

20. The bottom line: if we hadn’t
tested, we would have left about
$400,000 on the table

21. How I arrived at this way of
thinking—a journey
me in 2005

22. My old way of doing things
• Follow best practices
• Measure against industry benchmarks
• Execute online marketing “mechanically”

23. Then we asked an important
question: can we do better?

24. Gut instinct is a bad approach
“Many of the e-​​mails sent to supporters were
just tests, with different subject lines, senders
and messages. Inside the campaign, there
were office pools on which combination
would raise the most money, and often the
pools got it wrong.”
—Michael Scherer
Time, 11/7/12

25. The 3 drivers of online donations
1. Traffic to your donation page
2. Conversion rate on that page
3. Average gift

26. The Flux Capacitor of
Online Revenue Maximization

27. How this model works
Baseline
+ 26.2 %
in 1 area
+ 26.2 %
in 2 areas
+ 26.2 %
in 3 areas
Traffic 1,000 1,260 1,260 1,260
Conversion % 1.00% 1.00% 1.26% 1.26%
Average gift $100 $100 $100 $126
Revenue $1,000 $1,260 $1,588 $2,000
Lift 0% 26% 59% 100%

28. Think in terms of funnels
• Your funnel is a series of interrelated steps
that move someone to conversion
• No step is independent of another
Subject
line
Email
copy
Landing
page

29. Event registration funnel, version A
Subject: You are Cordially
Invited to a Town Hall Event in
Indianapolis

30. Event registration funnel, version B
Subject: Don't Miss the Heritage
Action Town Hall Meeting in
Indianapolis

31. Here’s how version B compares
within the funnel
5.6% decline in open rate
From 21% to 20%; 100% confidence
59.6% increase in click-through rate
From 12% to 19%; 100% confidence
50.8% decrease in RSVPs per visitor
From 23% to 11%; 100% confidence

32. But it’s not the parts that matter.
It’s the sum of the parts
126.2% increase in RSVPs per send
From 12% to 19%; 100% confidence

33. To maximize the sum of the parts,
you need to test each element
• Use A/B testing, not sequential testing
• It starts with planning, thinking, and learning
• Technology comes last
• Don’t test just to check a box

34. 6 steps to set up a successful test

35. 1. Start with a clear hypothesis
• What do you want to learn?
2. Identify your metrics
• What counts as a win?
3. Design your test
• Control for external factors, including time

36. 4. Identify tools to measure results
• Your ESP; Google Analytics; Optimizely; Omniture
5. Run the test, and be patient
• Results could take days or weeks to come in
6. Aim for statistical significance
• Helps ensure your results are repeatable
• http://www.mystatscalc.com/

37. Too small a sample can mean
unhelpful data
You want 90%+

38. Unless you have a huge lift, you’ll
need dozens of results

39. A few mini-cases

40. Hypothesis: changing the default
gift to $50 amount boosts $50 gifts
Control Treatment 1
+44% $50 gifts
Treatment 2
+64% $50 gifts

41. Version B
Hypothesis: a timer will drive more
revenue than a thermometer
Version A

42. The countdown timer outperforms
the thermometer
8.64% increase in click-throughs
96.65% confidence
11.8% increase in gifts
7.5% increase in revenue per e-mail sent
100% confidence

43. Hypothesis: adding a renewal
button will increase revenue

44. The renew-donate combo
outperforms just a donate button
83.95% increase in site conversion rate
0.05% to 0.09%; 99.9% confidence
62.5% increase in revenue per site visitor
$0.06 to $0.09; 98.8% confidence

45. So to review . . .
• Don’t trust your gut
• Test everything
• Always ask, “Can I do better?”

46. Questions?
@nathanielward