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 Prepagent.com by Arthur Sparks

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

The Same Pattern Was Also Tested Here

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

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.