Pattern #2: Icon Labels

Pattern Author: Jakub Linowski - Founder & Editor @ GoodUI.org

Based on 7 Tests, Members See How Likely This Pattern Will Win Or Lose And Its (?) Median Effect

Almost Certain Loser
-5
-4
-3
-2
-1
0
+1
+2
+3
+4
+5
Almost Certain Winner
Icon Labels
  1. Show icon labels

    To make icons less ambigous, this pattern suggests to augment them with text labels.

Median Effects

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Engagement

Ex: Any Action / Visit

(7 tests)

?

Conversions

Ex: Signups, Leads

?

Sales

Ex: Transactions, Upsells

(2 tests)

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Revenue

Ex: AOV, LTV

?

Retention

Ex: Return Visits

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Referrals

Ex: Social Shares

Tests

Pattern #2: Icon Labels
Was Tested On Support.microsoft.com by Ronny Kohavi

  • Test 216
  • Tested on Support.microsof... by   Ronny Kohavi
  • Dec 21, 2018

Find Out How It Performed
Screen: Home & Landing
Devices: Desktop

  • Measured by survey completions

Microsoft ran an experiment on their Customer Satisfaction Survey at both support.microsoft.com and answers.microsoft.com (Desktop). The treatment contained two icon labels at the opposite sides of the star rating range (ex: Very Dissatisfied and Very Satisfied) - providing it with additional meaning.

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The Same Pattern Was Also Tested Here

Find Out How It Performed
Screen: Navigation
Devices: Mobile

  • Measured by calls being made

Microsoft Skype ran an experiment for the mobile segment of the Skype application with a treatment having combined icons with corresponding labels. The control only showed icons.

Get Access To See The Test Results Now

  • Test 190
  • Tested on Diamondcandles.c... by   Peep Laja
  • Jul 26, 2018

Find Out How It Performed
With 95,776 Visitors
Screen: Sitewide
Devices: Mobile

  • Measured by sales

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

  • Measured by clicks on menu

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

This test has explored numerous hamburger menu variations and has been covered in detail over at https://conversionxl.com/blog/testing-hamburger-icon-revenue/ - Thanks Peep Laja for sharing. Here we reported on a consistent increase in both menu clicks and sales.

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  • Test 191
  • Tested on Diamondcandles.c... by   Peep Laja
  • Jul 26, 2018

Find Out How It Performed
With 96,195 Visitors
Screen: Sitewide
Devices: Mobile

  • Measured by sales

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

  • Measured by clicks on menu

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

Get Access To See The Test Results Now

  • Test 16
  • Tested on Caffeineinformer... by   James Foster
  • Jul 01, 2016

Find Out How It Performed
Screen: Home & Landing
Devices: Mobile

  • Measured by clicks on button

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

Get Access To See The Test Results Now

  • Test 17
  • Tested on Caffeineinformer... by   James Foster
  • Jul 01, 2016

Find Out How It Performed
Screen: Home & Landing
Devices: Mobile

  • Measured by clicks on button

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

Get Access To See The Test Results Now

  • Test 18
  • Tested on Caffeineinformer... by   James Foster
  • Jul 01, 2016

Find Out How It Performed
Screen: Home & Landing
Devices: Mobile

  • Measured by clicks on button

    (?)% Converted ((?) of (?) visits)
    (?)% Converted ((?) of (?) visits)

This is a retest of Test017 with a lengthier testing duration.

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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.

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I am 100% focused on getting positive results for people willing to put in the work to improve their conversion rates. At the core I share two beliefs: 1) that the more something works, the greater its probability for working again and 2) running controlled experiments is a great way of validating your ideas.

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