Pattern #115: Pricing Comparison Table

Pattern #115  Tested 2 timesFirst tested by Arthur Sparks Recently tested by Lars Skjold Iversen on Apr 23, 2020

Based on 2 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
Pricing Comparison Table (Variant A) Pricing Comparison Table (Variant B)

Expected Median Effects Of B

?

Progression

(1 tests)

-

Leads

-

Signups

-

Engagement

?

Sales

(1 tests)

?

Revenue

(1 tests)

-

Retention

-

Referrals

?

ANY PRIMARY

(2 tests)

Tested on

Tests

Pattern #115: Pricing Comparison Table
Was Tested On Umbraco.com by Lars Skjold Iversen

Isolated

Test #294 on Umbraco.com by $conducted_test->test->user_->first_name . ' ' . $conducted_test->test->user_->last_name Lars Skjold Iversen    Apr 23, 2020 Test link

Find Out How It Did With 18,623 Visitors

  • Measured by clicks on any purchase button

In this experiment, plan properties on a pricing page were horizontally aligned (for easier comparison). More so, labels and values were also broken on separate lines.

Get Access To See The Test Results

The Same Pattern Was Also Tested Here

Replaced

Isolated

Test #277 on Prepagent.com by $conducted_test->test->user_->first_name . ' ' . $conducted_test->test->user_->last_name Arthur Sparks    Jan 03, 2020 Test link

Find Out How It Did

  • Measured by total sales

  • Measured by total revenue

In this experiment, side-by-side plan features were aligned and changed to a comparison table with checkmarks for easier comparison.

Get Access To See The Test Results

Leaks

Leak #40 from Netflix.com   |   Jan 10, 2020 Pricing

Netflix Keeps Its Older Price Comparison Table And Rejects Their New Layout In This A/B Test

Netflix has been experimenting with the layout of their pricing plans. Challenging the more traditional pricing comparison table, instead they a/b tested three self-contained pricing plan tiles. This newer version however ended up being rejected as we noticed. View Leak

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.