Pattern #127: Vague Or Specific Benefits

Pattern #127  Tested 1 timesTested by Ognjen Bošković on Jun 27, 2022

Based on 1 Tests, Members See How Likely Version B Wins Or Loses And By How Much

LOSSES
-5
-4
-3
-2
-1
FLAT
+1
+2
+3
+4
+5
WINS

Measured by the sum of negative and positive tests.

A B
Vague Or Specific Benefits (Variant A) Vague Or Specific Benefits (Variant B)

Expected Median Effects Of B

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Progression

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Leads

?

Signups

(1 tests)

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Engagement

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Sales

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Revenue

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Retention

-

Referrals

?

ANY PRIMARY

(1 tests)

Tested on

Tests

Replaced

Confounded

Test # 417 on Cxl.com by $conducted_test->test->user_->first_name . ' ' . $conducted_test->test->user_->last_name Ognjen Bošković    Jun 27, 2022 Test link

Find Out How It Did With 8,974 Visitors

  • Measured by newsletter subscriptions

Zoom In
  • ?% (? successes out of ? visits)
A
  • ?% (? successes out of ? visits)
B
Signup

CXL ran an interesting experiment that (1) added more specificity on a newsletter subscription page as well as (2) reinforced it consistently. Most visibly, an abstract or vague headline statement (control) was changed to a benefit oriented one - hinting that subscribers will eventually receive valuable case studies. This message was further reinforced with supporting copy that explained where these case studies are obtained from along with the frequency of the delivery. This same message was also reinforced with an image of actual case studies. The call to action button was also adjusted to mimic the benefit.

Impact on newsletter signups was measured.

Get Access To See The Test Results

For each pattern, we measure three key data points derived from related tests:

REPEATABILITY - this is a measure of how often a given pattern has generated a positive or negative effect. The higher this number, the more likely the pattern will continue to repeat.

SHALLOW MEDIAN - this is a median effect measured with low intent actions such as initiating the first step of a lengthier process

DEEP MEDIAN - this is derived from the highest intent metrics that we have for a given test such as fully completed signups or sales.