What is A/B Testing?
A/B testing is a marketing analysis technique where two or more variations of a web page is tested against one other in order to find out the best performing one. It is also known by the name if split testing. It can be used as a testing platform for determining the success of web pages, email campaigns, advertisement campaigns (like adwords) etc.
Areas Where A/B Testing is Used?
A/B testing can be used in almost any area where customer interaction needs to get tracked. Businesses always look for successful leads and tries to find out what is the best way to engage customer interaction and persuade them to buy their products and services. Some of the areas where A/B testing finds a place are given below:
Identifying the best converting landing page
Tracking E-Commerce check out page for finding the best possible combination
Improve product pages to improve sales
Testing a page before introducing it for all the audience
Experimenting content variations
Testing different versions of mobile apps etc.
How to Carry Out A/B Testing Content Experiments Using Google Analytics?
With Google Analytics, you can start tracking the performance of every variation of your page for FREE. All you need is a Google Analytics account and a small piece of JavaScript code to track the performance of original vs variation pages. Here is the step by step guide to create content experiments using Google Analytics.
Step 1: Sign in with your Google Analytics Account.
Step 2: Click on Behavior tab and move to Experiments section as shown in the figure below:
Step 3: Now, enter the URL of the page you want to improve goal conversion and click on start experimenting.
Step 4: Enter the details of content experiments. Provide a name for your experiment, select an objective, select the percentage of traffic where you want to experiment and set the email notifications.
Step 5: Configure the details and choose all the variation URL’s which you want to test against the original URL.
Step 6: Insert the experiment code in the original page and make sure the analytics code is inserted into the variation pages. Now, you may start the experiment.
You can also have a look at the video below:
Increasing Conversions and ROI
Every business wants to increase the return on investment (ROI) and A/B testing is one of the best ways to find out the best combination which helps to get more conversions. Content experiments can be run by any business having a Google Analytics account and properly planned and executed experiments gives excellent results.
Is A/B Testing Right for Me?
Yes, A/B testing is perfect for your business because it does not allows you to lose something but instead it helps your business to get a winning combination which comes after successful and thorough testing. All this comes at a no cost to the company because A/B testing experiments can be run for FREE using Google Analytics. All you need is a little bit of coding knowledge and admin access to install the tracking code.
Example of Split Testing
One good example of A/B testing would be to create 2 different versions of product page and see which page gets the most referrals to the checkout page. For this, one new product display page is created which is slightly different from the original one. Texts, images, buy buttons, videos, product descriptions etc are all changed slightly in order to persuade the buyer to click on the “buy now” button.
Now, a content experiment is created using Google Analytics and both the references of original URL and variation URL are specified in order to find out the best converting page. The experiment runs for a few days or weeks until a clear winner emerges.
This A/B testing experiment is great for identifying the best page which initiates conversions and helps to improve the ROI for the company.
Significance of A/B Testing
Online controlled experiments are a great way to determine the winning combination that is leading to more conversions. You can actually increase your rate of conversions and raise your profits simply by testing one or more variants of your marketing material. The best part of this type of testing is that its FREE and does not costs any extra for the company. Some of the great advantages of A/B testing are as follows:
Advantages of Split Testing
1- It unleashes the human mind as to why people convert to certain pages.
2- It helps to test conversion rates for specific pages based on colors, fonts, catchy headlines, navigation options etc.
3- Split testing is FREE and requires minimal effort.
4- Instead of predicting things, tests can be carried out to identify the best possible combination which provides results.
5- It helps to measure the actual customer behaviour.
6- It helps your business to survive in a competitive environment by quickly providing the best solution for your business.
7- A/B testing is quick and provides results at a faster rate than expected.
Tools to Test the Success of Your Experiment
A great tool for testing the success of your A/B content test experiment is http://getdatadriven.com/ab-significance-test. This tool allows you to calculate the success ratio of Page A compared to Page B. You can compare both your original and duplicate pages here and get the results yourself.
Some other tools for calculating conversion rate optimization out of your split test are shared below:-
http://www.houseofkaizen.com/conversion-rate-optimisation/resources/calculators/split-test-significance/
http://www.usereffect.com/split-test-calculator
http://abtester.com/calculator/
http://www.thumbtack.com/labs/abba/
http://visualwebsiteoptimizer.com/split-testing-blog/ab-testing-significance-calculator-spreadsheet-in-excel/
http://www.peakconversion.com/2012/02/ab-split-test-graphical-calculator/
http://tools.seobook.com/ppc-tools/calculators/split-test.html
http://www.measuringusability.com/ab-calc.php
http://elem.com/~btilly/effective-ab-testing/g-test-calculator.html
Top Tools for A/B testing
Loves Data Measures Dance Moves Using GA
Acquisition, Behavior and Channels in GA
Exit Rate vs Bounce Rate
Understanding Goal Flow in Google Analytics
Google Tag Manager
How to Decrease Bounce Rate?
Multi Channel Funnel
Regular Expressions
