How different imagery affects the conversion rate from a Facebook ad Experiment ID: #6334

NextAfter

Experiment Summary

Timeframe: 3/13/2017 - 3/20/2017

When launching a new research study, we wanted to ensure that we were getting the most out of our Facebook advertising.

Our control used typical imagery with a picture of the eBook, and text on the ad saying “Get the Free eBook.”

We developed a treatment with the hypothesis that more people might download the study if the ad introduced the nature of the content, rather than making an overt offer right in the news feed.

A 2nd treatment was developed with the hypothesis that an infographic could more accurately convey the value of the research than the book’s artwork, prompting more downloads.

Research Question

Which ad will generate more eBook downloads?

MECLABS Conversion Factors Targeted

C = 4m + 3v + 2( i - f) - 2a ©

Copyright 2015, MECLABS

Design

C: eBook Image
Mid-Level Crisis Ad - Control
T1: Cover Art and Title
Mid-Level Crisis Ad - Artwork
T2: Infographic
Mid-Level Crisis Ad - Infographic

Results

Treatment Name Conv. Rate Relative Difference Confidence
C: eBook Image 0.19%
T1: Cover Art and Title 0.89% 360.0% 100.0%
T2: Infographic 0.54% 178.3% 94.1%

This experiment has a required sample size of 1,591 in order to be valid. Since the experiment had a total sample size of 10,346, 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
× 360.0% increase in conversion rate
× 0% increase in average gift

Key Learnings

This experiment conveys that likely NextAfter subscribers aren’t motivated enough in the Facebook newsfeed to download an eBook. But an ad that conveys a relevant message can capture their attention, and get them to a landing page where they are more likely to download the offer.


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Experiment Documented by...

Nathan Hill

Nathan is an Optimization Evangelist 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.