Pattern #80: Persistent Filters

Pattern #80  Tested 3 timesFirst tested by Vinicius Barros Peixoto Recently tested by Jakub Linowski on Dec 22, 2024

Based on 3 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

(1 tests)

?

Leads

(1 tests)

-

Signups

-

Engagement

?

Sales

(2 tests)

-

Revenue

-

Retention

-

Referrals

?

ANY PRIMARY

(3 tests)

Tests

Pattern #80: Persistent Filters
Was Tested by Jakub Linowski

Isolated

Test # 568 Dec 22, 2024 Test link

Find Out How It Did With 81,116 Visitors

  • Measured by add to cart

  • Measured by completed sales

In this experiment, "persistence" of 4 product choices was added in the variation. When users made a product selection such as: duration, payment terms, starting month or shipping frequency, their choices were remembered and defaulted on next visits, reloads or when viewing other products. Impact on adds to cart and sales was measured.

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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

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.

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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

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.

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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.