Pattern #109: Required Field Labels Save Pattern Bookmark

Pattern Author: Julian Gaviria - Director of User Experience @thomasnet

Based on 3 Tests, Members See How Likely This Pattern Will Win Or Lose And Its (?) Median Effect

Almost Certain Loser
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0
+1
+2
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Almost Certain Winner
Required Field Labels
  1. Showing Required Fields Explaining

    The idea of this pattern is to let users know about which fields are required (ex: using an asterisk).

Median Effects

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Engagement

Ex: Any Action / Visit

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Conversions

Ex: Signups, Leads

(3 tests)

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Sales

Ex: Transactions, Upsells

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Revenue

Ex: AOV, LTV

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Retention

Ex: Return Visits

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Referrals

Ex: Social Shares

Tests

Pattern #109: Required Field Labels
Was Tested by Alex James

Test #256 Tested on An Anonymous Site Aug 23, 2019

Find Out How It Performed With 116,470 Visitors

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  •  

  • Measured by successful registrations   |   p-val (?)

The original had no fields marked as required. The variant had all fields marked as required with an asterisk (and a reference note).

Get Access To See The Test Results

The Same Pattern Was Also Tested Here

Test #257 Tested on Thomasnet.com by Julian Gaviria Julian Sep 09, 2019

Find Out How It Performed With 5,739 Visitors

Signup Desktop, Mobile
  •  

  • Measured by successful registrations   |   p-val (?)

In this followup experiment, field labels without and with a marked asterisk were tested.

Get Access To See The Test Results

Test #255 Tested on Thomasnet.com by Julian Gaviria Julian Aug 22, 2019

Find Out How It Performed With 5,977 Visitors

Signup Desktop, Mobile
  •  

  • Measured by successful registrations   |   p-val (?)

In this experiment, field labels without and with a marked asterisk were tested.

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.