Pattern #42: Countdown Timer

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

Based on 3 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
Countdown Timer
  1. Add: Countdown Timer Urgency

    Show a timer rolling backwards which communicates how much time remains before a given action should be taken. It's probably good practice that the shown urgency is authentic and not just made up.

Median Effects

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Engagement

Ex: Any Action / Visit

(2 tests)

?

Conversions

Ex: Signups, Leads

(1 tests)

?

Sales

Ex: Transactions, Upsells

(2 tests)

?

Revenue

Ex: AOV, LTV

?

Retention

Ex: Return Visits

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Referrals

Ex: Social Shares

Tests

Find Out How It Performed
With 2,258 Visitors
Screen: Checkout

  • Measured by visits to thank you page

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

  • Measured by visits to billing screen

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

This test was run on a 3 step checkout process. The first screen was asking for contact information, and the second screen asked for credit card details. The change was shown on both first two steps as shown on the image below.

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Find Out How It Performed
Screen: Product

  • Measured by successful sales

De Nieuwe Zaak (a Dutch ecommerce agency) tested a countdown timer on an ecommerce site. The variation showed how many hours and minutes were left in order to be eligible for next day delivery. The variation beat the control which did not have this element of urgency.

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  • Test 127
  • Tested on Glass.net by Mark Freedle
  • Nov 23, 2017

Find Out How It Performed
With 61,034 Visitors
Screen: Listing

  • Measured by final quote submissions

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

  • Measured by visit to next confirmation step

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

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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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