Google clarifies Hreflang Implementation for multilingual websites

On July 25, 2024, just six days ago, Google's Search Relations team released a new episode of their Search Off the Record podcast, focusing on the implementation of hreflang tags and internationalization best practices for multilingual websites. The podcast, featuring Martin Splitt, Lizzi Sassman, and Gary Illyes, delved into the complexities of managing websites that serve different languages and countries, offering insights into Google's approach to handling multilingual content.

According to the podcast, hreflang tags continue to play a crucial role in helping search engines understand the language and regional targeting of web pages. However, the implementation of these tags is not always straightforward, and many website owners struggle with the complexities involved. The discussion aimed to clarify common misconceptions and provide a deeper understanding of how Google processes hreflang information.

One of the key points addressed in the podcast was the prevalence of hreflang usage across the web. Citing data from the Web Almanac, the team revealed that in 2022, approximately 9% of websites were using hreflang tags. This figure surprised the Google team, with Gary Illyes expressing that it was "way more than expected." The higher-than-anticipated adoption rate underscores the importance of hreflang in the current multilingual web landscape.

The podcast also touched on the technical aspects of hreflang implementation. Gary Illyes explained that hreflang annotations can be provided in three different ways: through HTML tags, HTTP headers, or XML sitemaps. While all three methods are supported, the team suggested that including hreflang in HTML or HTTP headers might lead to faster processing by search engines compared to XML sitemaps, which are processed separately from individual page crawls.

An interesting revelation from the discussion was that Google does not rely on the HTML lang attribute for language detection. Gary Illyes mentioned that this attribute is often set incorrectly or left as a default value in content management systems, making it an unreliable indicator of a page's language. Instead, Google uses its own language detection algorithms to determine the content's language.

The concept of "x-default" in hreflang implementations was also explored. This value is used to specify a default page when no other language/region combination matches the user's preferences. The team clarified that the x-default page doesn't necessarily need to be a language version of the content; it could be a country selector page or any other page that helps users navigate to the appropriate language version.

A significant portion of the conversation was dedicated to discussing the challenges of implementing hreflang on large websites with complex structures. The team acknowledged that while hreflang is conceptually simple for small sites, it becomes increasingly complex for large e-commerce platforms or websites with multiple country-specific domains. This complexity often leads to implementation errors and misunderstandings about how search engines process the information.

The podcast also addressed the issue of similar content across different language versions, particularly for e-commerce sites where product pages might differ only in price, currency, and minor details. Gary Illyes explained that hreflang helps prevent de-duplication issues in such cases, ensuring that the appropriate language version is shown to users in different regions.

An important clarification was made regarding the reporting of hreflang in Google Search Console. The team explained that Search Console only reports on canonical pages, which can lead to confusion when alternate language versions appear to drop out of the index. This limitation in reporting is due to storage constraints and the need to handle data for extremely large websites efficiently.

The discussion also touched on the lack of an official Google tool for validating hreflang implementations. While Google doesn't provide its own validator, the team recommended several third-party tools that have been tested and found reliable, including Aleyda Solis' hreflang tags generator and the Merkle hreflang testing tool.

Throughout the podcast, the Google team emphasized the importance of correct hreflang implementation for improving user experience and ensuring that the right content is served to the right audience. They also hinted at potential future developments, suggesting that as language detection algorithms improve, the reliance on explicit hreflang annotations might decrease over time.

In conclusion, the podcast provided valuable insights into Google's handling of multilingual and international websites. It highlighted the complexities involved in implementing hreflang correctly, especially for large websites, while also offering clarifications on common misunderstandings. As the web continues to become more globally interconnected, understanding these internationalization concepts remains crucial for webmasters and SEO professionals aiming to serve diverse, multilingual audiences effectively.

Key facts from the Google Search Off the Record podcast on hreflang and internationalization

The podcast was released on July 25, 2024, featuring Martin Splitt, Lizzi Sassman, and Gary Illyes.

Approximately 9% of websites were using hreflang tags in 2022, according to the Web Almanac.

Hreflang can be implemented via HTML tags, HTTP headers, or XML sitemaps.

Google does not rely on the HTML lang attribute for language detection.

The x-default hreflang value can point to any page helping users navigate language versions, not necessarily a specific language version.

Google Search Console only reports on canonical pages, which can cause confusion in hreflang reporting.

There is no official Google tool for validating hreflang implementations.

Hreflang helps prevent de-duplication issues for similar content across language versions.

The podcast suggests that reliance on explicit hreflang annotations might decrease as language detection algorithms improve.