[TUTORIAL] Quantitative Data A/B Testing
2016-04-24, 01:39 PM,
#1
A/B Testing is a technique used to determine if a specific change made on a webpage can influence conversions in a positive way. It is implemented through the creation of a variation page (page B) whose results are compared with the ones of the original version (page A). The one that performs better in terms of conversions wins the challenge.

A/B tests or multivariate tests?

A/B tests are quantitative tests that work with a single variable. However, this variable doesn’t have to have only two versions. The change can be implemented on a series of pages: A/B/C/D/E/F/G/H/I/J. For example, you can test up to 10 versions of a call to action, by splitting the traffic to 5 versions of the same page, each one with a different call to action.

In contrast to A/B tests, Multivariate tests use multiple variables find out which combination of variables converts more. For example, on one variation you can change the title, the call to action button and the price at the same time.

A/B tests are recommended in the situation where you can point exactly to the element that could be the key to increasing conversions.

How does univariate testing and analysis work?

Though apparently a simple technique, A/B Testing is a process that includes an in depth data analysis and gives essential insights into the way visitors perceive and interact with the site. Results will appear only if the test is implemented correctly, using the right variable, on relevant pages, at the right time.

Here are 4 unavoidable steps for great results:

1. Setting a conversion goal. The whole purpose of conducting an AB test is to improve elements that will drive more customers to accomplish a desired action. As a result, conversion rate will improve. You can use AB tests to find a way to maximize different types of conversions:

Completed acquisitions

Requests for quotation

Digital documents downloads

Newsletter subscriptions

Clicks on ads or banners
Any other strategic action on site

2. Hypothesis. Testing starts with analyzing the conversion funnel and identifying what page needs to be improved in order to lead more customers further in the process of converting. Moreover, you have to identify exactly the element which, once it’s been changed, will make a real difference in customer engagement . A good understanding of customer behavior combined with knowledge in website ergonomics, can point to this key element.

A/B testing ideas or What to test

Marketing: prices, offers, call to action

Copywriting: headlines, copy style, lenght of text

Design: layout, colors, background, pictures

The hypothesis should imply a goal achievement. For example, you can create a hypothesis that states “Addressing directly to customers through the website’s content will increase conversion rate up to 5%” or “Removing one field of the contact form will increase leads with 4%”.

3. Testing. Experiments must be conducted under strict rules. For the results to be accurate and precise, there are a few factors to be taken into account:

Timing: both page versions must be displayed to the website’s visitors during the same time, for the same period of time. Otherwise, results could be influenced by seasonality, trends and other external events.
Traffic: Traffic must be split equally between the different versions of the page. You can choose different segments of users to apply the test to and make changes that would be relevant only to these users.
Test duration: The variation pages should run for a period of time that enables the test to give accurate results. Relevance is determined by the total number of visits, the number of visits included in the test and the settled goal.

4. Data analysis. The test can have neutral results or it can show a significant increase in conversion rate. You might have had a theory for the winning page, but tests are a scientific method and it is their results you should trust, no matter how surprising they sometimes seem.

Challenges of A/B tests

Due to the fact that A/B testing may involve the creation of very similar pages in terms of content, some SEO challenges may arise.

Nevertheless, if you follow Google’s advice on the matter and you conduct the tests properly, all risks can be eliminated. Also, if you use the right AB testing tool, necessary precautions will be taken automatically.

If you don’t want your page versions to be perceived as duplicates or very similar content, use rel=”canonical” to indicate that there is only one original version of the page, and that’s the one that should be taken into account by robots.

Also, to redirect traffic to a selected version of the page, use a 302 redirect, rather than a 301. This tells robots, that the variation page is only temporary and it’s probably part of a test.

A/B testing software – the easy way to test

Using an A/B Testing software is a great way to find out which site changes will determine customers to make the desired actions on site. In an ever changing environment where websites have to keep up with consumers' preferences and ways of using the internet, tests should be conducted regularly.

When using the right A/B testing tool, experiments can be simple to create and to implement, without any fastidious changes in the content of the website or in the website’s source.

A/B Testing tools enable you to obtain high value information about customer behavior and to take the right decision when it comes to changing an element of the site.

Marketizator – A/B testing made easy

Continue reading the guide: https :// w w w .marketizator. c o m/what-is-ab-testing

Hope this helps some of you! :)
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