How the reader's motivation behind the call to action impacted the donor conversion rate | NextAfter
Americans for Prosperity

How the reader’s motivation behind the call to action impacted the donor conversion rate

Experiment ID: #40343

Americans for Prosperity

Experiment Summary

Timeframe: 09/04/2020 - 10/02/2020

As a part of experimenting with motivation on post-eBook signup donation pages for Americans for Prosperity, we decided to experiment with a “give” vs. “get” call to action.

Research Question

How does the “give to others” call to action compare to the “get more” call to action?

Design

C: Get the info out CTA
T1: What we offer CTA

Results

  Treatment Name Conv. Rate Relative Difference Confidence
C: Get the info out CTA 0.70%
T1: What we offer CTA 5.0% 605.0% 97.0%

This experiment has a required sample size of 116 in order to be valid. Since the experiment had a total sample size of 283, and the level of confidence is above 95% the experiment results are valid.

Flux Metrics Affected

The Flux Metrics analyze the three primary metrics that affect revenue (traffic, conversion rate, and average gift). This experiment produced the following results:

    0% increase in traffic
× 605.0% increase in conversion rate
× 0% increase in average gift

Key Learnings

With a 97% level of confidence, we observed a +607% increase in donor conversion rate by setting up the problem and outlining our offer to help the reader solve it.

The difference between the two treatments was so wide and no further promotion of this offer is expected, after having achieved only about 16% of the minimum number of conversions we would normally like to see with an experiment of this type.

Therefore, further experimentation is required. With that said, the learning here might be that focusing on what you offer to the audience as a solution to a common problem they feel they are experiencing instead of getting information to other people might be more motivating moving forward.


Experiment Documented by Greg Colunga
Greg Colunga is Executive Vice President at NextAfter.

Question about experiment #40343

If you have any questions about this experiment or would like additional details not discussed above, please feel free to contact them directly.