Pattern #24: Visible Availability

Pattern Author: Rodrigo Maués - Head of Product Design @ Anheuser-Busch InBev

Based on 5 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
Visible Availability

  1. Add: Response Time Indication Reassurances

    This pattern is measuring the effect of showing availability more visibly. For situations where people might expect a human interaction (ex: people trying to qualify as leads or waiting to receive a quote), some tests have displayed response times. Other experiments in this pattern have simply stated that some listing, product or offer is "available". 

Median Effects

?

Progression

Ex: First Action

(2 tests)

?

Leads

Ex: Leads, Quotes

(4 tests)

?

Signups

Ex: Trials

?

Engagement

Ex: Future Action

?

Sales

Ex: Transactions

(1 tests)

?

Revenue

Ex: AOV, LTV

?

Retention

Ex: Return Visits

?

Referrals

Ex: Social Shares

Tests

Pattern #24: Visible Availability
Was Tested On 3dhubs.com by Rob Draaijer

Test #98 Tested on 3dhubs.com by Rob Draaijer Rob Nov 30, 2020

Find Out How It Performed With 48,771 Visitors

Listing Desktop, Mobile

  •  

  • Measured by placed quotes   |   p-val (?)

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

In this experiment, the variation showed a listing's owner online status as a badge, instead of showing their average "response time". More specifically, an "Online Now" badge was shown beside individual listings of a 3D printing marketplace site. The experiment measured completed quote / lead requests (a few steps further).

Get Access To See The Test Results

The Same Pattern Was Also Tested Here

Test #99 Tested on Vivareal.com.br by Rodrigo Maués Rodrigo Sep 23, 2020

Find Out How It Performed With 249,954 Visitors

Product Desktop, Mobile

  •  

  • Measured by form submits   |   p-val (?)

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

In this experiment, a lead form on a listing page showed whether an agent was recently online or not. The diplayed had two statuses: either indicating that someone is online now, or the most recent time they were online in minutes.

Get Access To See The Test Results

Test #292 Tested on Backstage.com by Stanley Zuo Stanley Apr 13, 2020

Find Out How It Performed With 180,098 Visitors

Listing Desktop, Mobile

  • Measured by application process starts   |   p-val (?)

  • Measured by premium membership completions   |   p-val (?)

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

The core hypothesis of this experiment was that by showing clear availabiltiy (in green text) beside each casting call, more users would apply and become premium members. The experiment reports on two metrics: application starts (the first progression metric), and premium membership sales (merasured a few steps further in the funnel).

Get Access To See The Test Results

Test #97 Tested on 3dhubs.com by Rob Draaijer Rob May 03, 2017

Find Out How It Performed With 13,441 Visitors

Listing

  • Measured by company page visits   |   p-val (?)

  • Measured by orders placed   |   p-val (?)

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

Get Access To See The Test Results

Test #102 Tested on Vivareal.com.br by Rodrigo Maués Rodrigo May 02, 2017

Find Out How It Performed With 250,533 Visitors

Product

  •  

  • Measured by form submits   |   p-val (?)

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

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.