There are several ways that you can generate inbound traffic to your website or landing pages. Some of these options involve either paid or free advertising and promotional campaigns intended to attract a particular type of web visitor. These are done so with the intent of converting these web visits into leads or sales. Among the paid advertising avenues available, PPC (Pay Per Click) proved to be among the most popular digital marketing methods and accounts for up to 64.6% of clickthroughs on keyword searches highly intended for commercial and business purposes.
PPC ads in general are effective for driving highly targeted traffic to a particular landing page where most conversion efforts occur. However, not all landing pages are created equal. A particular landing page variation may generate higher conversion rates than another page promoting the same product or service. Changes in certain page elements can be a big factor in the effectiveness of the page for generating conversions and it’s up to the business owner or the digital marketer to select which elements to use.
To validate which of these variations prove effective, A/B split testing can be conducted as part of the overall optimization process to improve the performance of your PPC campaign. The following provides an overview of what A/B split testing is and how it is a vital tool to ensure the success of your digital marketing campaign.
What is A/B Split Testing?
In its most basic sense, A/B split testing is a form of hypothesis testing involving two variants, particularly A and B thus the name A/B testing. A series of randomized experiments are performed involving these two variants, with all factors and elements the same except for where variations of one particular factor or element, in this case that of a landing page or a web page, which is subjected for performance comparison.
Two Main Uses for A/B Split Testing?
Many digital marketers believe that A/B split testing is basically just a tool for optimization, which in this particular case involves PPC ads and landing pages. Contrary to this belief, A/B split testing can be used not only for optimization but also for validation, which is important during the initial stages of a particular PPC campaign.
- Using A/B testing for Optimization
A/B split testing is primarily used for the optimization of an ongoing PPC campaign, particularly in testing which particular variation in page element likes the headlines, image, layout, form, call-to-action and other factors that will affect conversion rates. This tool is intended to increase known conversion rates of a PPC campaign after it has already been rolled out for a particular length of time.
- Using A/B testing for Validation
A/B testing is good for optimizing an already ongoing PPC campaign. However, it is not the only use where you can apply A/B split testing. You can also use it to validate which particular variation will be the best one to use for your campaign before you even roll out. A good example is when you want to roll out an ebook or a whitepaper as part of your PPC campaign. You can test different variations of these materials and validate which one will generate the best results – and use it for the main campaign.
Impact of A/B Split Testing on SEO
A/B split testing is important if you want to validate which particular PPC campaign to use and optimize it to get the best results in terms of higher conversion. However, many digital marketers are afraid of the negative implications A/B split testing may have on the main website’s SEO. The fear emanated from the speculations that A/B testing may affect rankings because of the variants in content.
“We’ve gotten several questions recently about whether website testing—such as A/B or multivariate testing—affects a site’s performance in search results. We’re glad you’re asking, because we’re glad you’re testing! A/B and multivariate testing are great ways of making sure that what you’re offering really appeals to your users.”
The statement about is Google’s clarifications that they actually welcome A/B and other testing methods as long as the processes follow the guidelines they’ve outlined in their central blog. These guidelines are outlined and explained in brief below:
- Do Not Perform Content Cloaking
It is against Google’s guidelines if your website shows a different content to their crawling Googlebots than what humans may actually see from the site. Original content should always be shown to the user-agent “Googlebot” as manipulating this may result in your penalization and removal from search results
- Use the link attribute rel=“canonical”
This is applicable when you are running A/B split testing experiments using multiple URLs. This link attribute will tell the search engines that the preferred version of a particular page is the original and not the alternate URL used for testing. The attribute will tell the search engine that variations should be grouped together as merely duplicates, with the original page marked as the canonical URL. This is different and better than using a noindex meta tag as you would of course want Googlebots to crawl and index your home page.
- Set only a specific duration for you’re A/B split testing
Gather only enough data for you’re A/B split testing and specify the length of time you will need to run the experiment. Once you’ve identified how you can optimize your website and landing pages, it would be best to conclude your test and remove alternate URLs, markups, scripts and other elements you have used during the experiment
The A/B Split Testing Process
A good experiment is based on the guidelines and processes used in scientific methods and the same can be used in the A/B Split Testing Process. The following describes the basic flow of a scientific step-by-step process that you can use for A/B Split Testing.
- Identify the Problem – ask yourself what particular problem or issue with your PPC campaign would you like to address
- Get Insights on Targeted Audiences – Using Google Analytics or any other available analytical tools that you can use to understand the online behavior of your targeted audiences
- Formulate a Hypothesis – Make assumptions on probable results that may come out from your testing
- Calculate the Required Number of Visitors per Day – you will need to calculate and identify the required number of website visitors per day to make your test runs more reliable and statistically valid
- Test Your Hypothesis – create variations based on your hypothesis and then test these against the original. Check out the impact of your variations based on measurable metrics like bounce rates, conversion rates, etc
- Data Analysis – at this point, data collected from tests are measured based from the original. If no significant changes or improvements were generated, you may need to perform additional tests
- Report – The results, insights and conclusions of your testing should be reported to concerned departments and decision makers if you will need their concurrence on what to do next
Metrics for A/B Split Testing
When perform A/B split testing to improve the overall performance of your PPC campaign, you need to identify what particular metrics your will be using to measure success. These metrics will tell you if your tweaks and adjustments to factors and elements that affect conversion rates are making any positive progress or not.
Monitoring, measuring and adjusting these metrics based on A/B test results will move your sites to optimization and maximum results. The following describes some of these metrics:
- Bounce Rates – Even if you are generating huge amounts of traffic but are getting only miniscule conversions from all these visits, your PPC performance will still not be as optimum or even favorable as you would want it. Bounce rates will tell you how many percentage of your traffic actually convert, so you can identify good high-traffic + high-conversion campaigns.
- Unique Visitors – This may be a simple metric to track but it will tell you how effective your campaign is in reaching new markets and new-customer possibilities
- Time Spent on Page – Traffic volume is an important metric, but how much time people spend on your pages per visit will give you an insight of how targeted audiences are accepting and consuming your content
- Conversion Rate – Of course, measuring every completed conversions per unique visit would be the ultimate metric you’ll need to test and monitor with you’re A/B Split Testing experiment. Conversion depends on the actual goal of your landing page, whether to generate leads and get valuable information from web visitors, or an actual sale
Performing an A/B Split Test using proven scientific methods is not an endeavor that only large corporations can afford. As a business owner or digital marketer, you can perform A/B Split Testing to improve the performance of your Pay-Per-Click campaign. PPC is an effective marketing tool, but it can also be a very expensive one if all the basics and key strategies are not performed to the letter. Using A/B Split Testing, digital marketers can further improve and optimize their campaigns to generate better and more targeted results.