Perform SEO A / B tests in Google Search Console
Perform SEO A / B tests in Google Search Console: -
Use SEO A / B testing to measure the impact of specific website optimizations on keyword rankings.
SEO A / B testing allows site owners to understand if the changes they make to their website are having a positive impact on keyword rankings.
Anything on a website can be A / B tested, but the best variations to test are those that have a direct relationship with Google's ranking algorithm.
Site owners can best run an SEO A / B test will depend on the size of their website and their ability to easily roll back changes.
If an A / B test proves that a specific optimization is effective, a site owner can more confidently incorporate the same or similar changes to other pages on their website.
For SEO strategists, it is sometimes difficult to know which of the many changes we make to our websites are actually impacting their overall SEO performance.
Moving websites from page 10 to page 2 can usually be done by following SEO best practices.
Requires much more specific attention to the specific changes we make to our landing pages.
Get into SEO A / B testing, one of the best ways to narrow down and understand the effectiveness (or ineffectiveness) of specific optimizations.
Many digital marketers are comfortable with A / B testing features in their PPC campaigns or analyzing user behavior in Google Analytics, but fewer are incorporating this powerful strategy to better understand which of their On-page optimizations have the most impact on keyword rankings.
SEO A / B testing can seem daunting, but with the right tools, it's actually pretty straightforward to perform.
A / B testing not only helps SEOs identify the most impactful optimizations but also gives them a way to quantify their efforts.
Although SEO A / B testing is more often used by advanced SEO strategists, there is a great opportunity for site owners who are comfortable working on the backend of their website to elevate their SEO strategy through well-structured A / B tests.
When it comes to controlled experiments, testing two variants is the cornerstone from which all other tests are built.
A / B testing simply measures the impact of a single variation on an outcome.
In the case of SEO, the results are better, worse or static.
One needs Google Search Console for one (the absolute truth of the SEO ranking), plus two clearly defined variants that one wants to test.
Site owners should have a staging or staging environment where they can save a version of their website prior to SEO A / B testing in case the changes do not produce the desired results.
Best use cases for SEO A / B testing:
Everything can be A / B tested on our websites, but for SEO purposes certain elements of the site are more likely to lead to improvements in keyword rankings due to the weight they carry in Google's algorithm. .
Title tags:
The choice of title tags is so important and has a huge impact on search results.
Title tag changes have a very big impact from a ranking standpoint, as they directly influence the click-through rate (CTR).
Google has a standardized expected CTR for searches, and if landing pages continually fall under the brand, it will negatively impact the overall ranking chances.
Meta descriptions:
For websites that already have a lot of keywords on the first page and therefore get a lot of impressions, A / B testing meta descriptions can be really beneficial.
Like title tags, they have a direct impact on CTR, and improving them can lead to many more clicks and therefore higher rankings.
Schema markup:
If one can, it's good to add schema markup to all web pages, but if there are some pages on the site that still don't have schema.org markup, adding it can be a great use case for one. A / B test.
Internal links:
Internal links communicate with the architecture of the Google site and also distribute PageRank on our websites.
Getting good internal links can produce dramatic improvements in keyword rankings, especially for larger websites with thousands of landing pages.
Focus on header and footer links due to their PageRank lag.
For websites with product pages, one can use A / B testing to find the best anchor text for internal links.
New content:
Adding good content to landing pages is always beneficial because longer content implies topical depth.
Using a landing page optimization tool can help improve the semantic richness of the content, and subsequent A / B testing measures whether Google is responding positively to these quality signals.
Large groups of pages:
For e-commerce sites or those that can add a large group of pages at once, A / B testing can be used to measure whether those pages are crawled and indexed in a way that positively or negatively harms existing rankings.
Information architecture:
Some elements of the information architecture are more specific to SEO.
Google loves page experience features like referral links and carousels, so understanding the impact of adding these features to web pages is another reason to perform SEO A / B testing.
Site migrations:
Anytime fundamental technical changes are made to the website, A / B testing is a great way to measure the impact of those changes on keyword rankings.
Also helps to prevent the site from experiencing a significant drop in rankings in the long run.
Types of SEO A / B tests:
There are different types of A / B testing that one can run on the website.
Much will depend on the number of landing pages as well as the category of variations one is testing.
A then B:
The most basic form of A / B testing, this type of testing will simply compare the performance of a single page with a different variation.
This type of A / B testing is better for smaller sites and easier to implement, especially if there is the confidence that the changes are going in the right direction.
Several pages:
This type of A / B testing provides much more statistically significant results and can be performed on large sites with hundreds to thousands of landing pages.
Instead of measuring a single variation on a single page, choose two-page groups of similar pages and edit the variation on all of those pages.
Multivariate:
This common form of experimentation has the same basic mechanisms as an A / B test, but it increases the number of variants tested.
Multivariate testing can be great for measuring user behavior, but it's less effective at measuring search performance when trying to find out if a specific optimization has a direct impact on keyword rankings.
Performing SEO A / B testing is the easiest way to do A / B testing using snapshots and site restores.
Take a site snapshot, make the change to the site, and sit down for a week and watch what happens.
Here's a simple step-by-step process of an SEO A / B test:
Take a site snapshot or back up the site before implementing the changes so that one can revert to a previous version of the website if the change is not effective.
Determine which variant one is testing (e.g. title tag, schema.org, and others) and make the change to a similar page or cohort of pages.
7 to 14 days to determine the impact of the change.
Compare the keyword rankings of the variant page (s) to the original, which can be done in Google Search Console or in a Google Search Console dashboard.
If the optimizations have an impact, we can make similar changes on other pages of the site.
More targeted edits, such as adding keyword-rich title tags and meta descriptions, won't necessarily translate directly to other pages.
More technical optimizations like schema.org and information architecture can be implemented across the entire website with more confidence if an A / B test proves them.
Version control is like tracking changes on a Word document, but the history is never deleted.
With version control, even if one deletes or changes something, there is a timeline of all the changes that have been made - when a line of code was created, when it was changed - and one can go back at any time.
Important to make sure that all pages under development and test environment pages on the site do not contain index tags for bots.
Adding pages to the blocklist in robots.txt or with canonical rel tags on the page would be enough, but at LinkGraph I have seen many examples where pages or sub-domains were added to robots and have continued to be.
Adding a canonical tag is insufficient to prevent crawling and indexing of the development domain.
The best strategy is to use robots without indexes.
The even better strategy is to use both indexless bots and rel canonic for additional protection.
If one changes the top pages that Google crawls frequently, one can probably see if those optimizations had an impact within 7-14 days.
When evaluating the effectiveness of the optimizations, beware of confounding variables.
Multiple backlinks over a short period of time, the addition of Javascript, and of course, algorithm changes, can have a big impact on keyword rankings.
Any kind of experimentation is more accurate when one can weed out variables, so try the best not to schedule A / B tests during link-building campaigns, base algorithm updates, or any timeframe. high volatility in research.
When done correctly, A / B testing can be a powerful way to refine the SEO strategy towards optimal results.
A / B testing can not only help site owners make more data-driven decisions, but it can also help SEO strategists prove the value of their work to clients or executives who may be reluctant to invest in it. SEO.
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