How framing the audience for an offer affects conversion rate Experiment ID: #7390

Buckner International

Buckner International is a global ministry dedicated to the transformation and restoration of the lives we serve. We are a Christ-centered organization that delivers redemptive ministry to the most vulnerable from the beginning to the ending of life.

Experiment Summary

Timeframe: 8/23/2017 - 9/12/2017

Buckner International ran an offer focused on helping your children learn how to react to poverty. They wanted to know if refocusing the offer copy around the person receiving the ebook, rather than how their children would benefit, would impact conversion rate. The ads that preceded these landing pages also reflected this reframing of copy. The other page elements remained the same.

Research Question

Are people more likely to download an offer if they personally benefit from it, rather than that offer . benefiting someone else?


C: Control
T1: Parent Focused


Treatment Name Conv. Rate Relative Difference Confidence
C: Control 11.1%
T1: Parent Focused 15.4% 39.1% 99.0%

This experiment has a required sample size of 471 in order to be valid. Since the experiment had a total sample size of 1,623, 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
× 39.1% increase in conversion rate
× 0% increase in average gift

Key Learnings

The treatment with parent-focused copy produced a 39% lift in conversion rate. What we learned from this test is that people are inherently more likely to download something that immediately betters their own understanding or helps them grow personally, rather than benefiting another person (their children, in this case.) Framing copy with this in mind increases the value to the person downloading the offer.

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Experiment Documented by...

Allison Jones

Allison is an Optimization Associate 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.