SEO A/B testing is different from typical UX/CRO testing. No matter how quickly search evolves and best practices change, some changes should be tested before being rolled out.
Testing can help justify further investments or prevent potential negative effects.
Why you need to test your SEO strategy
As companies look very carefully at the ROI of marketing in general and SEO in particular, it's more important than ever to test and prove your strategy.
Decision makers are looking for ways to justify spending. When it comes to SEO, ROI is pretty vague. Are you trying to predict the impact of a recommendation, or are you trying to report on the impact after the fact?
As SEOs, we rely on KPIs like organic traffic, organic share of voice, and rankings. However, looking at these indicators in isolation misses the point. No single data point reflects the full picture of how our efforts have impacted expertise, authority, credibility, etc.
To make matters worse, with the rollout of GA4 and all-new attribution models, numbers and historical data are more complex than ever.
Testing is your ticket to certainty and confidence in the new age of search.
How to get buy-in
The uncomfortable truth is that even SEO experts don't always know what's best. We throw around phrases like “best practices” rather than specific terms or rules for a reason. Algorithms are secret and constantly changing and evolving.
Testing your SEO strategies and tactics can help you avoid failure, or at least reduce the risk of potential damage. This means fewer requests for engineering support and fewer deployments and subsequent rollbacks. This gives you more time to optimize your growth opportunities.
It also provides us with hard data about our impact, which most stakeholders want, and allows us to better communicate about our SEO efforts.
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Methodology and growth framework
A typical (admittedly simplified) SEO process looks like this.
- Recommendation to: Make recommendations based on best practices or past experience.
- embed: Implement changes to your live site.
- analyse: Report on the impact if it is detected.
But SEO testing is all about repetition. Ideate, optimize, test, and improve. repeat.
In SEO split testing, the process evolves as follows.
- come up with an idea: Create a hypothesis to test.
- group: Categorize and define page sets of controls and variables.
- embed: Implement changes to variable groups.
- monitor: Monitor changes and progress over time.
- analyse: Evaluate the effectiveness of the test.
- Refine: Based on data and analysis, make further adjustments and analyzes as necessary.
- embed: If the results are good, roll out the variant to the entire page set.
It's important to emphasize the second step: groups.
SEO A/B testing differs from CRO/UXO testing because it requires groups of pages. CRO testing splits users into two versions of a single page. SEO A/B testing cannot be implemented on a single page. SEO split testing involves splitting an entire group of templated pages or very similar pages into A and B groups.
You can test almost any page element. It all depends on your specific business and website goals. If you're working on increasing click-through rates, increasing overall organic traffic, or positively impacting your site's user experience, your tests may change.
A simple SEO A/B test might include testing title tags and meta descriptions to increase click-through rates. Or maybe you can test H1s and CTAs to improve engagement and conversions. More advanced testing may include changes to page layout, site structure, internal linking, and more. Things like breadcrumbs, product filters, and naming conventions can also be great for testing SEO effectiveness.
However, not all websites are suitable for A/B testing. Your site should have a lot of traffic and a significant number of template pages. Many tools require a threshold of at least 100,000 organic visits per month or at least 500,000 total visits per month. For example, e-commerce websites are great to test with lots of category pages and product-specific pages. A multi-location website is another good example for testing given the large number of similar location-specific pages.
Framework for running manual tests
To get started on whatever you decide to test, follow this scalable workflow:
- come up with an idea: Formulate your hypothesis as a testable statement, but keep it simple. Let's think about this in terms of three important factors: IF + THEN + BECAUSE.
- group: Define groups of pages with the same template, the same traffic, and the same user behavior. The more similar your pages are in format and purpose, the better. And the more historical data you have to work with, the more accurate your hypothesis will be and the more successful your results will be.
- It is essential that the page being tested has enough traffic evenly distributed across the group. For example, for an e-commerce site, all product pages included in the test must have at least 1,000 visits per day, evenly distributed across the set.
- Identify key areas for testing based on business goals and user behavior. Prioritize your tests to maximize impact and minimize risk.
- Define the methodology: Set clear expectations for all aspects of testing, including implementation method, duration, and definition of success. Divide a subset of pages into control and variant groups.
- monitor: Set up tracking dashboards using tools like Google Data Studio. This is your secret testing weapon. Easily access data to streamline test monitoring and analysis. Google Data Studio also has the added benefit of making it easy to clone and customize each dataset and test.
- Embed: Give your pages some SEO and make them shine.
- analyse: It may take some time for the full impact of the changes to be felt. Continuous monitoring may seem like a hassle, but it's worth it. Leave the test running for at least a few weeks to see statistically significant improvements. The effects of SEO testing are unlikely to be immediate and will take time.
- Deciding on next steps: Compare the results to the level of effort and resources required to deploy the update to determine the best action.
- Determine the winner by demonstrating the impact of your tests on SEO performance and business outcomes. Was this variant more successful than expected? Was the variant more successful than the actual outcome of the control?
- Don't be afraid to keep iterating to improve performance.
Let's dig deeper: Framework for running manual SEO testss
Advanced SEO testing with Google Ads
If you have a little extra budget, SEOs can use Google Ads to test their strategies quickly and efficiently.
Testing metadata
Title tags and meta descriptions are basically organic ad copy. Testing organic ad copy (metadata) has traditionally been a lengthy process. Whether you implement best practices site-wide or approach it through A/B testing, it just takes time. Paid search advertising can speed up the process.
To test metadata in Google Ads, follow this step-by-step process.
- Identify which pages to test. A great starting point for this test is to identify pages that are underperforming in terms of organic click-through rates or rankings.
- Once you know which pages you want to focus on, you can start testing. Responsive search ads allow you to test different title tag/heading variations and different description/ad copy variations. The landing page for every ad should be an optimization testing page.
- Creating an organic sandbox campaign for all your SEO tests keeps them in one place for easier management. This metadata test will be a single ad group within your campaign.
- A minimum of 3 headings is required, but you can enter up to 15 headings. The number you use depends on the breadth of your keyword theme, but we recommend at least five variations. The more unique each title tag/heading is, the better.
- Avoid using dynamic keyword insertion or fixed positions in headings, as the goal is to test specific copy.
- At least two descriptions are required, but you can enter up to four. For a more comprehensive test, you should use all four available.
- Similar to A/B testing, this method tends to work better with high-volume queries so that your ads are shown on priority pages on sites targeting high-volume keywords.
- According to Google, “Over time, Google Ads tests the most promising ad combinations and learns which combinations are most relevant to different queries.”
- Once you have a winner, you can use the key elements of your ad copy to influence your title tag and meta description. Which keywords performed better in the headline? Which descriptive terms and messages perform better in the ad copy?
There are many popular tools for CRO testing, but not all of them are equally effective for SEO testing. Below are some great options that focus on SEO considerations.
SearchPilot is a personal favorite as far as SEO testing tools go. Unlike other options, SearchPilot is designed exclusively for his SEO tests. It boasts easy-to-implement server-side tests that require no engineering or development. There is also integration with almost any platform, CMS or CDN.
SplitSignal is now part of Semrush Enterprise, and is another great option made specifically for SEO. SEO A/B testing is made easy and requires no development or engineering. It's easy to set up and uses Google's causal influence model to analyze results and determine winners.
Optimizely isn't designed specifically for SEO, but it's another solid option for A/B testing for SEO. Optimizely Experiment allows you to run tests focused on optimization or personalization. The interface is easy to use, and the tool requires little or no development or engineering resources.
Gain confidence in your SEO strategy
SEO split testing doesn't have to be complicated or difficult.
Embracing a culture of experimentation and iteration means SEOs can better adapt to changing trends and validate strategies. finally. You can take the basic approach outlined here and extend it to more advanced tests and techniques, with or without advanced tools. We can give people what they want: healthy ROI data.
Gone are the days of the typical SEO answer: “It depends…”
Today, we are entering a new era of “test results…”.
The opinions expressed in this article are those of the guest author and not necessarily those of Search Engine Land. Staff authors are listed here.