Pattern #80: Persistent Filters

Pattern #80  Tested 2 timesFirst tested by Vinicius Barros Peixoto Recently tested by Melina Hess on Jul 21, 2023

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
Persistent Filters (Variant A) Persistent Filters (Variant B)

Expected Median Effects Of B

-

Progression

?

Leads

(1 tests)

-

Signups

-

Engagement

?

Sales

(1 tests)

-

Revenue

-

Retention

-

Referrals

?

ANY PRIMARY

(2 tests)

Tested on

Tests

Pattern #80: Persistent Filters
Was Tested On Vivareal.com.br by Vinicius Barros Peixoto

Replaced

Isolated

Test # 196 on Vivareal.com.br by $conducted_test->test->user_->first_name . ' ' . $conducted_test->test->user_->last_name V. Barros Peixoto    Aug 14, 2018 Test link

Find Out How It Did With 441,738 Visitors

  • Measured by lead form submits on property page

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

The experiment goal was automatically applying filters the users have already done in our result page, during their navigation to the site. The variation always applied the filters in the same session and asked users on new sessions.

Get Access To See The Test Results

The Same Pattern Was Also Tested Here

Replaced

Isolated

Test # 484 on Snocks.com by $conducted_test->test->user_->first_name . ' ' . $conducted_test->test->user_->last_name Melina Hess    Jul 21, 2023 Test link

Find Out How It Did With 920,166 Visitors

  • Measured by completed purchases

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

In this experiment, the variation remembered and prefilled user's size choices for the duration of the session. The control version always started with a fixed product size value (ex: XS). The variation prefilled them between products or screen refreshes. Impact on sales 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.