Media Research Center

How removing a challenge grant affects conversion

Experiment ID: #11606

Media Research Center

The Media Research Center (MRC) is the nation’s premier media watchdog. The sole mission is to expose and neutralize the propaganda arm of the Left: the national news media.

Experiment Summary

Ended On: 04/08/2013

As part of a fundraising campaign, MRC had the opportunity to utilize a challenge grant. When comparing one campaign to the next, we have often seen campaigns with a challenge grant significantly increase both average gift and conversion rate.  However, this doesn’t give us an accurate understanding of the exact impact a challenge grant has since there can be many other factors influencing two different campaigns.

As a result, we wanted to create a treatment for a campaign that did not mention the challenge grant to see what kind of impact this would have on giving.

Research Question

How does the presence of a challenge grant affect giving?

Design

C: Challenge Grant Language
T1: No Challenge Grant Language

Results

 Treatment NameConv. RateRelative DifferenceConfidence
C: Challenge Grant Language 2.1%
T1: No Challenge Grant Language 1.6%-24.1% 97.9%

This experiment has a required sample size of 5,502 in order to be valid. Since the experiment had a total sample size of 15,149, 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
× 24.1% decrease in conversion rate
× 0% increase in average gift

Key Learnings

The treatment with no challenge grant language saw a 24% decrease in conversion rate. Language around “doubling your gift” appears to provide increased incentive for potential donors to make their gift since they believe that the impact is incrementally more valuable.


Experiment Documented by Tim Kachuriak
Tim Kachuriak is Chief Innovation and Optimization Officer of NextAfter.

Question about experiment #11606

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