RegEx for SEO: 12 Uses of Regular Expressions

Website developers and content marketers know that data is gold. It can provide the basis of deep insights that you use to revamp or refine a digital strategy. 

But how do you get the most out of your data? 

You probably have a Google Search Console and know its major query functions: "equals" and "contains." These can give you ways to aggregate data information in a way that you can use to create meaningful reports with strategic insights.

What if you could perform more powerful searches than just those built-in connectors like "equals" and "contains"? That's the promise of RegEx, a coding tool that's easy to implement and use. 

Here we'll give you the basics about RegEx, how it's different, and how you can use it to elevate your SEO game. 

What Is a RegEx and What Does It Look Like?

RegEx has been an open secret among developers for a long time. It offers immense flexibility in how you search and structure your data, allowing you to customize reports with in-depth insights that aren't available with built-in Google Search Console tools alone. 

RegEx stands for Regular Expression. It is a coding tool that acts as a search function. "Find and Replace," which almost everyone who's used a text document recently has probably used, is actually a RegEx. 

Indeed, RegEx is everywhere, including in tools people use every day like Microsoft Word, Notepad, and the Google search engine. So even though it's code, and integrates seamlessly into many programming languages, its potential and functionality are easy to understand. 

Its benefits in developing your SEO strategy are vast, in particular by helping you to identify search patterns and access the data that's hiding underneath the surface in Google Search Console.

Before we go on to discuss RegEx in SEO, let's take a minute to define a RegEx string and what it looks like. A simple example is this series of characters:

• /t[aeiou]+/g

This RegEx looks for all instances of the letter "t" followed by a vowel. Let's imagine you apply this pattern to the following sentence:

• I ate some toast while sitting at Greg's table.

The RegEx would pick up the following results:

• I ate some toast while sitting at Greg's table.

This is a relatively straightforward example of an application of RegEx. It can have a longer and more complex sequence of characters. Certain symbols also provide "instructions" for how the RegEx functions, such as the square brackets identifying the range of characters that can follow the "t" in the example. Punctuation marks including question marks and asterisks are also fundamental to RegEx strings.

For this blog post, we're going to focus on just one attribute of RegEx filters that is important to know before you use RegEx to optimize your SEO reporting and technical SEO audits. That's the difference between "greedy" and "lazy" in a regular expression match. In RegEx, you can apply quantifier code that helps you to choose a "greedy" RegEx pattern or a "lazy" RegEx pattern.

Greedy RegEx Pattern

It might be easy to see that the possible matches for a RegEx search string vary depending on the exact parameters of the RegEx filter. In our example, the expression picked up the longest possible search string to fit the pattern. The "t" followed by any vowel that the regular expression pattern leads to a result that picks up both the "te" in "ate" as well as the "toa" in "toast."

Because this RegEx pattern looks for the longest possible string, it's known as "greedy." In fact, the results of "toast" would be not just "toa" but more precisely "to" and "toa." The fact that you'll get these kinds of results is important to know so you can fully understand your RegEx pattern matches.

Lazy Pattern

In a lazy pattern, RegEx looks for the shortest matches possible to a string. In our example, a lazy RegEx pattern would no longer pick up "toa" in "toast" as a separate result; it would stop with "to," as that is the shortest possible string that matches the RegEx query.

Let's use the example of a RegEx search that looks for the letter "y," followed by any number of characters, followed by an "l."

• In a greedy pattern, the RegEx would pick up "yell" and "yellow" in a data set that includes those words.
• In a lazy pattern, the RegEx would pick up only "yel" in the same data set. 

What Are the Benefits of Using Regular Expression?

RegEx is a powerful tool for producing reports on your search data. By looking deeply into your digital activity, you can harness insights you can use to optimize content, perform keyword research, and more. When you're diving into Google Analytics, RegEx can help you go beyond the platform's simple introductory functions.

Let's break it down: how Google Analytics and regular expressions work together for SEO and how a Google regular expression search can optimize your data.

Top 12 Uses of RegEx for Search Engine Optimization

RegEx has its obvious uses: identifying duplicate content, for instance, as well as finding the best anchor text most likely to match up with a search query. But there are at least a dozen ways RegEx can help with your SEO. Here are some of the best uses of regular expression.

1. Analyzing URLs

It might seem odd to want to analyze URLs with RegEx, but think of the e-commerce scenario: It's likely you have thousands of individual URLs that all correspond to product pages. The ability to take a deep dive into your conversion data and filter the specific URLs that correspond to consumer activity is invaluable. 

You can use this data to identify the URLs customers see and respond to — and those they don't. RegEx allows you to use strings like product category or name inside the URLs to pick up activity for that URL group. You can also perform some smart URL analysis where you track the list of URLs a user visits to develop a clear sense of the customer journey.

2. Conducting Keyword Analysis

You can use RegEx to dive deeper into the keywords people search and use to find and engage with your site. This is a powerful tool that allows you to identify niche searches, high-converting strings, and key phrases whose ability to drive conversions you can harness with your content strategy. 

RegEx allows you to look for strings, using a greedy or a lazy pattern, that can be difficult to visualize using the simple existing Google Search Console tools of "contains" or "equals." Here you can find those high-performing but sometimes difficult-to-spot long-tail keywords that can help drive your sales.

3. Creating Custom Channel Groupings and Events

Google also likes to offer categories when it comes to traffic sources and activities. The platform has preset channel groupings that let you identify what traffic came to your site through these channels. It also sets up events like "page views" that you might track in a basic analytics strategy. 

With RegEx, you can customize all of this analytic info. You can create a channel group that's relevant to your strategy, such as "traffic sourced from app users in continental Europe." The benefits of this are clear: You can set your groups to whatever criteria are most important for you to understand the success of your digital marketing strategy.

4. Identifying Underperforming Pages

Remember our note about the e-commerce site with thousands of URLs? That's a common state for many website developers: a long index of website pages and a need for customizable analytics to see which ones are providing the best returns. But it doesn't stop there, because some URLs might have errors. The activity pattern of users might be different than for other pages. Maybe visitors don't convert or don't click through to other pages.

RegEx allows you to dive deep into the activity that's linked to each one of these pages. You can use this data to start correcting errors or to do a page-level analysis. 

This is useful for ongoing maintenance. It can also be the first step to see if a modification in your strategy can help to optimize what's working well and remedy what's falling short.

5. Excluding Referrals

Your traffic reports in Google Analytics 4 typically capture all referral sources, but you might actually want to exclude some traffic referrals from your reporting. Let's say you're running a pay-per-click campaign. The traffic pattern that helps you track campaign performance might be as follows:

• Ad URL → Purchase Confirmation URL

In this example, the URL of the ad is the traffic source. But more commonly, the pattern that arises in analytics is as follows:

• Ad URL → Payment Gateway → Purchase Confirmation URL

Instead of identifying the ad URL as the referral source for the purchase traffic, the analytics identify the payment gateway. This is obviously not ideal from an analytics standpoint as your customers can arrive at the payment gateway from a number of different sources.

By using referral exclusions, you can remove potential referral sources, like the payment gateway in this example, from your analytics.

Referral exclusion is achievable by using RegEx in GA4:

• Find the option to "Configure tag settings." 
• Choose the option to exclude referrals based on "Referral domain matches RegEx." 
• Enter your RegEx string.

The advantage of using RegEx in this way is that you don't have to list out multiple domains to exclude in your reporting; you can simply identify the RegEx string.

6. Segmenting Users Based on Behavior To Create Audiences

Much as you use RegEx to create custom channels, you can drill down into your analytics data to uncover a picture of user behavior. This process, called behavioral segmentation, allows you to divide users who fit particular criteria into segmented audiences. 

This is a comprehensive analysis that encompasses the customer journey, the channels these users frequent, and the messaging to which they respond. Segmenting your audiences allows you to develop individually targeted digital marketing strategies for each group. 

7. Carrying Out Index Consistency Checks

A task often left to developers, the index consistency check makes sure a local site index matches the index of the related database. RegEx offers superior ease and functionality with this task, as you can use greedy RegEx or lazy RegEx patterns to identify any mismatches between the two and remedy them accordingly.

8. Evaluating Content by Identifying HTML Elements

Part of technical SEO is ensuring that your website's code is easy for search engines to crawl. Code should generally be well-structured and well-organized. Having code that's too cluttered might negatively impact SEO. RegEx can help you to identify strings of "clunky" code across your website so you can clean it up in the process of optimization.

Developers can assess the "back end" quality of content by searching for deficiencies. RegEx commands can help you to identify elements of poor code style, like redundant blank lines, missing white space, or code line lengths that might be too long. 

This is another incident where RegEx is an invaluable time-saving tool when you have a website with hundreds, or perhaps thousands, of pages. 

9. Creating Smart Redirects From '.Htaccess' Files

An ".Htaccess" file is a hidden file that causes an automatic redirect from one page to another. Let's say you've developed two pieces of content around your new product line: One is an interview with your CEO about the development process and the other is a breakdown of the product's specifications. 

Perhaps you want to take down the CEO interview a month after the launch. Using RegEx, you can identify the search strings that led people to that piece of content and offer smart redirects to the content you actually want them to see. 

10. Finding Client Queries After They Purchase

Digital marketers might assume their work ends at the point of conversion. But the after-purchase data can offer deep insight into customers' post-purchase concerns and experiences. What's on the mind of a recent customer can tell you a lot about whether the product works and how you can respond proactively to those concerns.

Let's imagine you sell a state-of-the-art vacuum cleaner. You might want to know if people are looking for information on key terms like "warranty," "return period," "doesn't work," "replacement parts," and "complaints." 

A RegEx query can help you identify the key terms your customers might look up after purchase so you can be ready with a response. That response might be a set of Q&As for your customer service team or relevant pages on your website that provide return and warranty information. 

11. Comparing Brand and Non-Brand Traffic

One important question for digital marketers is which segment of users search by brand identity versus product, service, or industry. Think of "Coca-Cola" as the brand, while "soft drinks," "carbonated drinks," "soda," or "sweetened" are all examples of terms related to Coca-Cola. In search traffic, "Coca-Cola" and "soda" are both potential key terms, but one is brand-specific and the other is not.

Marketers can use RegEx to distinguish between visitors searching for the brand and brand-related terms and visitors searching for non-brand-related terms. In this example, "Coca-Cola," "Coke," and "Diet Coke" are all brand key terms. One example of a RegEx report in Google Search Console that distinguishes between traffic types is a RegEx query that "includes" or "excludes" branded terms that you specify. 

Depending on how you use RegEx, your "includes" report might only have these branded terms, or it might have all terms. If you use a lazy RegEx pattern, you can capture only branded traffic; with a greedy RegEx pattern, you can capture everything. 

12. Conducting Log File Analysis

Suppose you want to extract key terms from your log files. RegEx can help you do this efficiently, even if the values appear in each log line in a different order or don't appear in each log line at all. By using RegEx, you can identify the logs relevant to your data analysis and use them to create a cohesive report. 

Because of the flexibility of RegEx, you can adopt a lazy pattern to eliminate duplications in repetitive logs. By default, RegEx patterns are greedy. Use special characters to confine your searches to a lazy pattern if necessary, such as by using "*?" instead of "*". One tip is to start with a simple RegEx query that offers transparency into the structure of your logs before implementing a more complex RegEx pattern.