Conversion Optimization

Chris Dayley – Dayley Conversion

Agenda

Agenda

• Background• A/B Testing Overview• Case Study Reviews• Live Page group analysis• Individual variant outlines

Background

Background

• Spent 4 years in the SEO/PPC/Social Media industry• Began A/B testing to try to convert all the traffic I was

generating• Spent the next 3 ½ years doing testing & optimization in

multiple industries and won an award from WhichTestWonfor best e-mail landing page test of the year

• Started Dayley Conversion in November 2014 to offer expert-level services to companies

Problem

What?

What is A/B Testing?

Data Driven Website Improvement

Why? A/B Testing

• A/B testing allows user behavior data to continuously drive design and performance improvements

• Data driven approach helps avoid opinion driven design

• Multiple variant tests allow for greater efficiency with existing traffic, and finds improvements faster than running a single design at a time

How well do you know

web design?

Which Design Won?

Control

Why?

Control

Conversion:

8.4%

Winner

Conversion:

17.1%

104%

Which design won?

Which design won?

Winner

11.02%

Iterative Testing

Control

ResultsE-mail Traffic: Purple/Purple 92.97%Affiliate Channels : Orange/Purple 77.73%Search Traffic: Blue/Blue 43.48%

Image Treatment

Control Variant 1 Variant 2

Winner

52.10%

Runner Up

38.07%

Mobile Vs. Responsive

Control

Conversion:4.6%

Winner

Conversion:7.31%

59%

Mobile Mobile Variant Responsive Variant

Runner-Up

Conversion:5.92%

29%

Mobile Vs. Responsive

Control

Variant – 89.97% Lift

Avoid Pitfalls

Common Testing Pitfalls

1. Low impact tests

1. How to learn from tests that fail and tests that work

2. Thinking that a failed test isn’t worth trying again

3. Stopping tests too early

1. Not testing everything

Live Pages Analysis