How perceived value, clarity, and congruence affect email acquisition Experiment ID: #6996
Founded in 1844, Hillsdale College is an independent liberal arts college with a student body of about 1,400. Hillsdale’s educational mission rests upon two principles: academic excellence and institutional independence. The College does not accept federal or state taxpayer subsidies for any of its operations.
Timeframe: 7/11/2017 - 7/21/2017
Hillsdale College was offering a single-issue download of their popular publication Imprimis. They had typically offered Imprimis as a full subscription, and had used an image of a stack of issues, with the most recent on top. However, they wondered if this “multi-issue” image was making the actual “single-issue” offer unclear. This could be a risk, as showing multiple issues might increase the perceived value of the offer. They created an identical ad with a single issue and launched an A/B test to determine a winner.
Will aligning the image of the offer with the details of the offer increase conversion?
MECLABS Conversion Factors Targeted
C = 4m + 3v + 2( i - f) - 2a ©
Copyright 2015, MECLABS
|Treatment Name||Conv. Rate||Relative Difference||Confidence|
This experiment has a required sample size of 15,323 in order to be valid. Since the experiment had a total sample size of 116,843, 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
× 52.7% increase in conversion rate
× 0% increase in average gift
The treatment, which aligned the image with the offer, produced a 52.7% increase in conversion, though there was no discernible increase in clickthrough rate. This revealed an interesting learning—although the single-issue version didn’t increase the likelihood to click (meaning that it didn’t increase perceived clarity at the initial point of contact), it had a big increase on the likelihood to convert by aligning and increasing clarity at the point of decision.
This is a great example of how experiments must be measured along the entire funnel. If Hillsdale just measured an advertising experiment at the advertising level, then they would not make any changes. However, there were significant effects downstream—only discovered by measuring the entire funnel.