A B testing (sometimes called split testing) is comparing two versions of a web page to see which one performs better. You compare two web pages by showing the two variants (let's call them A and B) to similar visitors at the same time. Showing them to similar visitors and at the same timeis very important.
What is A/B testing?
All websites on the web have a goal - a reason for them to exist. News websites want visitors to click on ads, ecommerce websites want people buying products, personal blogs want people reading, interacting with, and finally respecting the author. Every website wants visitors converting from just visitors to something else. The rate at which a website is able to do this is its "conversion rate". Measuring the performance of a variation (A or B) means measuring the rate at which it converts visitors to goal achievers.
Why is A B testing useful?
Let's suppose you own an eCommerce store where you sell widgets. Your current conversion rate is 2% and average monthly traffic is 100,000 visitors. This means that in a month, you sell 2000 (2% of 100,000) widgets. Now if you want to increase sales by 10% to 2200 widgets, you'll have to increase the number of visitors by 10% to 110,000. To increase your monthly visitors, you'll have to run a marketing campaign or spend time on SEO. Assuming Customer Acquisition Cost (CAC) is $50, your total cost to acquire 200 new customers is $10000 ($50 x 200).
However, let's suppose you run an A/B test on your product pages. Visual Website Optimizer starts at $49 and you can have a test up and running in 30 minutes. After a week of running the test, you see an increase in conversions and sales to the tune of 107% or 41% or 27% . Depending on how much you increase your sales and conversion rate, the ROI case for A/B testing is massive, the kind that puts collective smiles on CMOs, CFOs and CEOs.
What can you test?
On the web, almost anything that influences user behavior can be A/B tested. Some of the elements that you can easily test:
- Headlines
- Sub headlines
- Paragraph Text
- Testimonials
- Call to Action text
- Call to Action Button
- Links
- Images
- Content above or below the fold
- Social proof
- Media mentions
- Awards and badges
How does A/B testing effect SEO?
Google cleared the air on the SEO implications of A/B testing in their blog post titled "Website Testing And Google Search".
The important bits from that post are:
- No cloaking.
Cloaking—showing one set of content to humans, and a different set to Googlebot—is against our Webmaster Guidelines, whether you’re running a test or not. Make sure that you’re not deciding whether to serve the test, or which content variant to serve, based on user-agent. An example of this would be always serving the original content when you see the user-agent “Googlebot.” Remember that infringing our Guidelines can get your site demoted or removed from Google search results—probably not the desired outcome of your test.- Use rel=“canonical”.
If you’re running an A/B test with multiple URLs, you can use the Rel=“Canonical” link attribute on all of your alternate URLs to indicate that the original URL is the preferred version. We recommend using rel=“canonical” rather than a noindex meta tag because it more closely matches your intent in this situation. Let’s say you were testing variations of your homepage; you don’t want search engines to not index your homepage, you just want them to understand that all the test URLs are close duplicates or variations on the original URL and should be grouped as such, with the original URL as the canonical. Using noindex rather than rel=“canonical” in such a situation can sometimes have unexpected effects (e.g., if for some reason we choose one of the variant URLs as the canonical, the “original” URL might also get dropped from the index since it would get treated as a duplicate).- Use 302s, not 301s.
If you’re running an A/B test that redirects users from the original URL to a variation URL, use a 302 (temporary) redirect, not a 301 (permanent) redirect. This tells search engines that this redirect is temporary—it will only be in place as long as you’re running the experiment—and that they should keep the original URL in their index rather than replacing it with the target of the redirect (the test page). JavaScript-based redirects are also fine.- Only run the experiment as long as necessary.
The amount of time required for a reliable test will vary depending on factors like your conversion rates, and how much traffic your website gets; a good testing tool should tell you when you’ve gathered enough data to draw a reliable conclusion. Once you’ve concluded the test, you should update your site with the desired content variation(s) and remove all elements of the test as soon as possible, such as alternate URLs or testing scripts and markup. If we discover a site running an experiment for an unnecessarily long time, we may interpret this as an attempt to deceive search engines and take action accordingly. This is especially true if you’re serving one content variant to a large percentage of your users.
How should you A/B test?
The correct way to run an AB testing experiment (or any other experiment for that matter) is to follow the Scientific Method. The steps of the Scientific Method are:
- Ask a question: "Why is the bounce rate of my website lower than industry standard?"
- Do background research: Understand your visitors' behavior using Google Analytics and any other analytics tools running on your website.
- Construct a hypothesis: Adding more links in the footer will reduce the bounce rate.
- Calculate the number of visitors/days you need to run the test for:Always calculate the number of visitors required for a test before starting the test. You can use ourA/B Test Duration Calculator.
- Test your hypothesis: You create a site wide A/B test in which the variation (version B) has a footer with more links throughout the site.
- Analyze data and draw conclusions: If the test results in reduced bounce rate, then you can conclude that increased number of links in the footer is one of the factors that reduces bounce. If there is no difference in bounce, then go back to step 3 and construct a new hypothesis.
- Report results to all concerned: Let the others who're involved know of the test results and insights generated.
Visual Website Optimizer to A/B test
Conversion optimization with Visual Website Optimizer is incredibly easy. Essentially, it is just four simple steps.
1) Include the Visual Website Optimizer code snippet on your website
Including the code snippet means we are now ready to run the tests you create on your website. For further ease, we have plugins for Wordpress,Drupal and Joomla that make the process hassle free.
2) Create variations using the WYSIWYG Visual Editor
Load your website in the Visual Editor and create any changes using the simple point-and-click interface. Advanced users can even make CSS and JS code changes.
3) Choose your goals
All A/B tests have goals whose conversion rate you want to increase. These goals can be straightforward (clicks on links, visits page) or could use advanced custom conversion code.
4) Start the test
And that's it, your test is ready to go live. Reporting is real-time so you can start seeing reports as soon as visitors arrive on a live test.
0 Comments