Can you really use French text in image geotags for local SEO?

What does Google mean by "geotags" exactly?

This refers to the EXIF, IPTC, or XMP metadata embedded in image files. More specifically, the Location, GPS Position, City, Country, and other geographic descriptors that can be included in JPG, PNG, or WebP files. These tags are often automatically filled by cameras or manually through software like Lightroom, ExifTool, or image optimization scripts.

Mueller's statement addresses a specific point: until now, some practitioners believed it was mandatory to use English in these fields for Google to understand the location. The idea that Google Maps serves as a language resolution reference changes the game. If you write "Lyon" or "Лион" or "リヨン", and Maps identifies that string as the French city, Google can extract the implicit coordinates.

How does Google extract the location from non-English text?

Google relies on its multilingual mapping database. Each place in Maps has linguistic synonyms and spelling variations. When the indexing bot analyzes an image, it reads the EXIF/IPTC fields, detects geographic text, queries Maps to resolve the entity, and then extracts the implicit GPS coordinates or confirms those already present.

The process is not perfect: it depends on the quality of the Maps reference in the target language. For well-covered languages (French, Spanish, German, Japanese), recognition works reliably. For less-supported languages or very obscure place names, there is a risk of confusion. An obscure village in Brittany written in dialectal Breton might not be resolved, where its French translation passes without issue.

Why is Google communicating about this now?

Because image indexing has advanced and non-English SEO practitioners have long unnecessarily translated their metadata into English. This clarification avoids redundant work and paves the way for simpler production flows. Teams managing thousands of localized images can now keep the source language in geographic fields without fearing a loss of signal.

This also fits into Google's overarching effort to improve multilingual understanding of its systems, notably via MUM and the language models integrated into search. Geolocation is becoming a semantic signal like any other, processed through NLP rather than just strict numerical coordinates.

• EXIF/IPTC/XMP tags can contain geographic text in the local language without penalty.
• Google Maps serves as a linguistic resolution reference for identifying places.
• Well-covered languages in Maps: reliable recognition. Rare languages or obscure place names: risk of confusion.
• Digital GPS coordinates remain the most reliable signal, but text alone is sufficient if Maps recognizes it.
• Simplified production flows: no need to systematically translate geographic metadata into English.

Is this statement consistent with field observations?

Yes, and it even confirms practices already observed. For several years, tests on multilingual sites have shown that Google correctly associates images tagged with city names in French, Spanish, or German to local search results. The novelty is that Mueller makes this mechanism explicit and attributes it to the use of Google Maps as a resolution layer.

However, it needs nuance: digital GPS coordinates (latitude/longitude in decimal or sexagesimal) remain the most direct and least error-prone signal. When present in the EXIF, Google does not need to go through a textual resolution step. The text alone only becomes determinative if the coordinates are absent or inconsistent. [To verify]: Does Google specify how it arbitrates in case of conflict between GPS coordinates and the City/Location field? Mueller does not say.

What limitations should be anticipated with this approach?

First point: not all image formats support EXIF/IPTC metadata in the same way. JPG and TIFF are well covered, PNG partially (through textual chunks), while modern WebP files can contain EXIF but not always depending on the encoder used. If you serve aggressively optimized WebP images, ensure that the metadata survives the conversion.

Second point: the quality of the Maps reference in your language matters. For a French site targeting mainland France, there are no issues. For a site in Wolof targeting rural Senegal, Maps may have gaps in its toponymic coverage. In this case, combining local text and GPS coordinates becomes essential, and text alone will not suffice.

Third point: be cautious with geographical homonyms. If you write "Paris" without specifying the country, Google might hesitate between Paris (France) and Paris (Texas). Tags should be as precise as possible: "Paris, France" or "Paris, Île-de-France" rather than just "Paris". A well-filled Country or Region field eliminates ambiguity.

Should GPS coordinates be abandoned in favor of text?

No. It's actually a bad idea if you have the technical means to integrate both. GPS coordinates are a unique signal, instantly usable by Google and all other engines or tools that read the EXIF. Geographic text adds redundancy and robustness, but it introduces an additional interpretation step.

The best practice remains to double the signal: precise GPS + clear local text. Thus, if one fails to be read or interpreted, the other takes over. This approach is particularly useful for tourism, real estate, event, or local e-commerce sites where image geolocation plays a key role in local ranking and visibility in Google Images.

What should be done practically with this information?

If you manage a multilingual or localized site, start by auditing your image metadata. Use ExifTool, Lightroom, or a Python script (Pillow + piexif) to list the EXIF/IPTC fields of your key images. Check if the geographic fields are filled, in what language, and if they are consistent with the page content.

Next, define a production workflow that integrates this metadata from the creation or import of images. For a tourism site in Spain, ensure that each location photo includes "Barcelona, Cataluña, España" in the City/State/Country fields, along with GPS coordinates if available. Automate this filling through your CMS, your DAM, or a post-processing script.

What mistakes should be avoided in implementation?

Classic mistake: overwriting metadata during optimization. Many compression tools (TinyPNG, ImageOptim, Squoosh) remove EXIF by default to reduce file size. Configure your tools to preserve at least geographic fields, or even all EXIF if the extra weight remains acceptable (often only a few KB).

Another trap: inconsistency between metadata and page content. If the image says "Lyon" but the page talks about Marseille, Google may ignore the EXIF signal or treat it as noise. Image metadata should reinforce the semantic signal of the page, not contradict it. Check the overall consistency of geographic markup: EXIF, Schema.org, hreflang tags if multilingual, and textual content.

Finally, do not overlook modern formats. If you serve WebP or AVIF, test that your metadata is well preserved. Some conversion pipelines forget to copy EXIF chunks from the source JPG to the WebP output. Use exiftool in the command line to force the copy: exiftool -TagsFromFile source.jpg target.webp.

How can I check that my site is configured correctly?

Three levels of control. First level: local extraction. Download some images from your site, run them through ExifTool (exiftool -a -G1 image.jpg), and check that the EXIF:GPSLatitude, EXIF:GPSLongitude, IPTC:City, and IPTC:Country fields are present and correct.

Second level: Google Search Console. In the Images section, check the indexing rate and look for errors or warnings related to metadata. If Google detects geographical inconsistencies, it may report them in coverage reports (even if not systematic).

Third level: real-world testing. Perform a Google Images search with a geographic filter ("photos Lyon") and check if your images appear. Use Google Lens to analyze one of your images: Lens sometimes shows the deduced location, giving you insight into what Google understands. If Lens detects nothing, it indicates a weak or absent signal.

• Audit the EXIF/IPTC metadata of your existing images using ExifTool or an equivalent tool.
• Define a production workflow that integrates textual geolocation (local language) + GPS coordinates.
• Configure your compression tools to preserve geographic EXIF fields.
• Check the consistency between image metadata and Schema.org/HTML markup on the page.
• Regularly test the preservation of EXIF during WebP/AVIF conversions and adjust scripts as necessary.
• Regularly monitor image indexing in Search Console and adjust in case of warnings.