How lower cost premiums impact donor conversion Experiment ID: #10544

Museum of the Bible

Experiment Summary

Timeframe: 12/21/2018 - 1/1/2019

The Museum of the Bible was running the early part of their year end campaign. Since the urgency and motivation is relatively low in the middle of December, they decided to utilize a premium as part of the appeal. The original idea was to offer a DVD the documented the building of the museum for a gift of $150 or more. However, there was also concern that such a high price for the premium may dissuade many potential donors from making a gift. We decided to run an experiment where we offered the same DVD but for a gift of $50 or more. We would then measure both donor conversion and overall net revenue to the organization.

Research Question

Will a premium offered at $50 instead of $150 increase the number of donors and amount of revenue to the organization?


C: $150 Premium
T1: $50 Premium


Treatment Name Conv. Rate Relative Difference Confidence
C: $150 Premium 0.05%
T1: $50 Premium 0.10% 102.6% 99.3%

This experiment has a required sample size of 22,735 in order to be valid. Since the experiment had a total sample size of 84,721, 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
× 102.6% increase in conversion rate
× 0% increase in average gift

Key Learnings

The $50 premium resulted in a 102% increase to donors acquired and a 183% increase to revenue for the organization. Even with the lower donation ask, we actually saw an increase in average gift too. The $50 ask increased the donors giving but did not decrease the gift amount of the donors that would have given anyway.

For future experiments, we may want to test offering a premium such as this for $75. Finding the optimal “price” for a premium such as this would allow us to maximize our potential revenue.

Note: since the difference between the two emails was in the content itself, the sample size is based upon the number of subscribers that opened the email.

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Experiment Documented by...

Kevin Peters

Kevin is the Chief Technology Officer at NextAfter. If you have any questions about this experiment or would like additional details not discussed above, please feel free to contact them directly.