A/B Testing for Optimising Internal Linking

A/B Testing For Optimising Internal Links

Internal linking can get your website where you need it to be.

And running some well done A/B testing for internal linking can help move things along by being backed up by statistics.

Before you know how to do the tests, and interpret the data, you need to know how it links to internal linking.

Let’s improve your SEO and fine-tune your linking strategy.

Understanding Internal Linking


What is Internal Linking?

Internal linking is connecting one page on your website to another by linking to and from each other.

These links help users navigate your site, discover related content, and access valuable information.

They can be seriously influential in supporting and improving your SEO, so don’t forget to link responsibly.

This is something that can take time, so why not speed it up with WILO?


The Benefits of a Well-Structured Internal Linking Strategy

A well-thought-out linking strategy offers several key benefits:

Improved User Experience: Internal links guide users, making finding the information they want easier.

  • Enhanced SEO: Search engines use internal links to understand your site’s hierarchy, which can lead to higher rankings in the results.
  • Reduced Bounce Rate: Effective internal linking keeps users interested in the site’s content, reducing the likelihood of bounce after only viewing one page.
  • Increased Page Authority: Internal links can distribute the authority of highly ranked pages to others, boosting their visibility.


Examples of Effective Internal Linking

To better understand the concept, let’s look at a few examples of effective linking practices:

  1. Contextual Links: Within a blog post about “Digital Marketing Strategies”, a contextual link may lead readers to another relevant post by clicking on the anchor text.
  2. Breadcrumb Navigation: Breadcrumb links at the top of a page can help users navigate back to a main category or home page easily.
  3. Related Posts: At the end or the sidebar of an article, suggesting related or new posts with hyperlinks can help keep readers engaged on your site.


Now that you understand more about the importance of internal linking, let’s explore how A/B testing can be a game changer in optimising your strategy.

A/B Testing Basics


Defining A/B Testing

This, or split testing, compares two versions of a webpage or element to see which performs better.

In SEO, A/B testing involves making controlled changes to your site and measuring their impact on user behaviour and key metrics.


The Testing Process

It follows a structured process:

1. Identify a Goal:

Determine what you want to achieve with your tests.

For internal linking, this could be increasing the click-through rate (CTR) on specific links.


2. Create Variants:

Develop two versions of the element you want to test.

In our case, it might be different anchor text for an internal link or varying link placement within a page.


3. Set Up the Experiment:

Use A/B testing tools or platforms to configure the test.

These tools help you evenly split your website’s traffic between the control (A) and the variant (B) groups.


4. Collect Data:

Monitor user interactions and collect data over a predetermined time frame.

Track metrics such as CTR, bounce rate and time spent on page.


5. Analyse Results:

Once you’ve collected enough data, analyse it to determine which variant performs better.

This step often involves statistical analysis to make sure the results are reliable.


6. Change:

If the variant outperforms the control, change the site.

If not, go back to the drawing board and test another hypothesis.

Setting Up A/B Tests for Internal Linking


Preparing for an A/B Test

Before you can start testing your internal linking strategy, you need to lay the groundwork:

1. Identify the Page or Content to Be Tested:
  • Decide which page or content you want to optimise through internal linking.
  • It could be a cornerstone article, a product page, or a landing page.


2. Define Goals and Metrics:
  • Clearly state your objectives.
  • Define the metrics you’ll use to measure success.


Choosing the Right A/B Testing Tool

Selecting the right tool is important for the success of your experiments.

Some popular tools include:

  • Google Optimise: A free tool with integration into Google Analytics for in-depth data analysis.
  • Optimizely: Offers robust testing, including multi-page tests and personalisation.
  • VWO (Visual Website Optimiser): Known for its user-friendly interface and comprehensive testing features.

Whichever tool you choose, make sure it aligns with your objectives and technical skills.


Creating Clear and Distinct Variants

When conducting these tests, it’s essential to create variants that are clear and different from each other.

Here’s why:

  • Clarity ensures that any changes in user behaviour can be attributed to the specific change you’re testing.
  • Distinct variants make it easier to analyse the results accurately.

Key Elements to Test

Now that you’ve set the stage for your A/B testing process, let’s look at the key elements that can be effectively tested.


Anchor Text Optimisation

Anchor text plays a significant role in how search engines perceive the relevance of a link.

By testing variations, you can determine which phrases or keywords drive the most engagement.

For example, you might test whether using specific keywords in anchor text increases CTR compared to using generic phrases.


Link Placement within Content

Where links are on a page can impact user engagement.

Try A/B testing different locations, like an article’s beginning, middle or end.

You might also experiment with using images as links versus text links.

The goal is to identify the placement that maximises user interaction.


Number of Internal Links on a Page

This can affect how certain users navigate your website.

Some pages may benefit from more internal links, while others may perform better with fewer distractions.

A/B test different link densities to find the balance that keeps users engaged without overwhelming them.


Link Relevance and Context

A/B test the impact of linking related content versus unrelated content.

For instance, on an e-commerce product page, you can test whether linking to complementary products improves user engagement.

Compare this to linking to unrelated content and measure the metrics around it.


Why Test Each Element Separately?

It’s good practice to test each individually rather than all at once.

This approach allows you to attribute any changes in user behaviour to a specific change.

If you test anchor text and link placement simultaneously and see improved CTR, you won’t know which made the improvement.

Is it the anchor text, link placement, or both?

By testing one at a time, you gain precise insights.

Conducting A/B Tests

With a clear understanding of what to test, let’s dive into the process:


1. Creating the Control and Variant Groups

You need two groups: one is the control, and the other is the variable.

  • The control group (A) remains the same and is the baseline.
  • The variant group (B) changes based on what you want to test.

For example, let’s say you want to test anchor text for a particular internal link.

In this case:

  • A: Uses the existing anchor text.
  • B: Uses the new, optimised anchor text.


2. Making Changes to Internal Links

Make the necessary changes to your website based on the variant group’s specifications.

Ensure these changes are made correctly and consistently throughout the variant group’s pages.

For anchor text optimisation, this means updating the anchor text for selected links across certain pages.


3. Tracking User Interactions and Engagement

Once the changes are live, it’s time to collect data.

Use analytical tools and your chosen A/B testing platform to monitor user interactions.

Track relevant metrics, such as:

  • Click-Through Rate (CTR): the percentage of users who click on the internal link.
  • Bounce Rate: the percentage of users who leave your site after viewing only one page.
  • Time on Page: how long users spend on the page after clicking the internal link.


4. Monitor Over a Sufficient Time Frame

Make sure you collect data over a period of time to account for fluctuations.

Short-term data can be misleading, so it’s important to monitor the test for an appropriate duration to draw meaningful conclusions.

The Importance of Statistical Significance

This ensures the observed differences between the control and variant groups are not due to random chance.

Tools we’ve listed above often provide built-in statistical analysis to help you decide whether the results are significant.

However, try to avoid premature conclusions based on small sample sizes.

Your data collection should be solid enough to draw valid conclusions.

Optimising Internal Linking

After you’ve spent time analysing your A/B testing results, it’s time to put the findings into action:


Summarise the Insights

Identify the changes that produced positive results and contributed to better engagement and SEO performance.



  • Update anchor text: Apply the optimised text to relevant internal links.
  • Adjust link placement: If certain placements performed better, change them to it.
  • Refine link density: Find the right balance of internal and external links for each page.
  • Enhance link relevance: Links need to link to related, valuable content.

Best Practices and Tips

Start with Clear Objectives
  • Clearly define your goals and objectives for each test.
  • This will guide your testing strategy.


Prioritise High-Traffic Pages
  • Begin testing on pages that are the most popular on your site.
  • It will allow you to collect data more quickly and make informed decisions sooner.
  • Once you’ve refined your approach, think about applying it to lower-traffic pages.


Segment Your Audience
  • Different user groups may respond differently to changes in internal linking.
  • Segmenting allows you to tailor your strategies to specific demographics and user behaviours.


Use Heatmaps and User Recordings
  • These help you understand user interactions and how they engage with your internal links.
  • It also allows you to see any obstacles or distractions they may face.


Multivariate Testing
  • Instead of sticking to just two versions, you have the ability to test multiple versions simultaneously.
  • This is useful when assessing the combined impact of changes to various elements.


Mobile-Friendly Testing
  • Show mobile users some love.
  • Changes that work well on desktops may not have the same positive effects on mobile devices.


Maintain a Control Group
  • Always keep an unchanged group.
  • This serves as a benchmark, helping you accurately gauge your changes’ impact.

Potential Challenges and Pitfalls

While A/B testing for internal linking offers valuable insights, you must be made aware of the difficulties:

1. Limited Sample Size

If you have a small website or low-traffic volume, it may take longer to get enough data for meaningful results.

Consider extending the test duration or focusing on high-impact pages.


2. Seasonal Variations

Websites often experience seasonal variations in traffic and user behaviour.

Be cautious when looking at test results during these lulls, as external factors may influence the outcomes.


3. Misinterpretation of Data

Seek assistance from experts or use reliable A/B testing tools to get the clearest interpretation of the data.


4. SEO Implications

Changes to internal linking can affect your SEO.

Be mindful of how modifications affect your website’s rankings, and monitor any fluctuations accordingly.

Final Thoughts

Didn’t think internal linking was this big a deal, huh?

Well it is, and it’s even more important to check back on what you’re trying to achieve with it.

A/B testing every so often is a great way to keep an eye on your methods and if they’re actually working.

But improve your internal linking structure first, then go onto the more hardcore bits.


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Last updated: November 27, 2023