Pattern #55: Conversational Filters

Pattern #55  Tested 1 timesTested by Craig Kistler on Apr 29, 2024

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
Conversational Filters (Variant A) Conversational Filters (Variant B)

Expected Median Effects Of B

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Progression

(1 tests)

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Leads

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Signups

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Engagement

?

Sales

(1 tests)

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Revenue

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Retention

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Referrals

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ANY PRIMARY

(1 tests)

Tested on

Tests

Replaced

Isolated

Test # 529 on Jared.com by $conducted_test->test->user_->first_name . ' ' . $conducted_test->test->user_->last_name Craig Kistler    Apr 29, 2024 Test link

Find Out How It Did With 189,872 Visitors

  • Measured by add to cart

  • Measured by completed purchases

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

In this experiment, conversational filters were tested at the top of some listing pages. Instead of showing one set of product filters, customers were shown three sets of product questions. After selecting each answer, product results would narrow and update further down on the page. Impact on adds to cart and sales were 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.