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Google Using AI To Automatically Update Some Business Information



Google Using AI To Automatically Update Some Business Information

Google announced it will be using artificial intelligence (AI) and a machine learning (ML) model to automatically update business hours and real-world road information.

The goal of these initiatives is to provide users with more up-to-date information about neighborhood changes.

Harnessing The Power Of AI For More Accurate Information

Though research into AI began in the 1950s, it didn’t begin to make deep learning breakthroughs until relatively recently. This is largely because machine learning progressed quite significantly post-2010.

“From my experience, I saw that ML algorithms are no longer the bottlenecks. To be sure, they are far from perfect, and there’s a lot of work to be done, but that work is happening at breakneck speed,” Edo Liberty, the former head of Amazon’s AI lab and current CEO of Pinecone, a vector database for similarity search said in a February 22 interview with Search Engine Journal.

Corresponding with the rise of big data, these advances are allowing AI to progress with incredible speed.

Google Using AI To Update Business Hours

COVID-19 changed the way many businesses operate, including the hours retailers and restaurants are open. To address these changes and better search engine users, Google developed a machine learning model that automatically identifies if business hours are likely wrong.

Once incorrect hours are identified, Google instantly updates the company’s business profile with AI-generated predictions.


For example, a business may have a profile showing it’s closed on Mondays, but it hasn’t been updated in over a year.

If Google determines its busiest hours are typically Monday evenings, it will recognize the hours are likely out-of-date and update them automatically.

It also uses Street View images of the storefront to identify hours of operations signs, while enlisting the help of local guides and business owners to verify predictions.

Business owners are contacted using Google Duplex, an AI system that allows people to have natural conversations and accomplish real world tasks with computers over the phone.

Google predicts this technology will help it update the hours of more than 20 million businesses worldwide within the next six months.

ML Updates Real-World Road Conditions

Google also announced it is experimenting with other ways it can use images for AI and ML. Starting in the U.S., it is launching a third-party imagery pilot that will provide the most up-to-date speed limit information.

The goal of this technology is to improve driver safety and add details that can make driving more efficient. Google hopes to eventually add information about potholes, school zones and construction.

Emphasis On Privacy Remains High

This pilot is designed with privacy as a key component. Reference images will only come from public roads. Partners will also be required to blur identifying information, including faces and license plates.


Once Google receives an image, it again blurs the photo, which is then deleted after maps have been updated.

Source: Google

Featured Image: Screenshot from, April 2022.

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Google On How To Simplify Hreflang Implementation



Google On How To Simplify Hreflang Implementation

Google’s Search Advocate John Mueller says hreflang implementation doesn’t have to be as complicated as people think.

Hreflang is one of the more confusing aspects of technical SEO and among the most important for international businesses and publishers.

In reply to a thread on Reddit, Mueller outlines a simplified approach for publishers to follow.

Hreflang: The Problem

Hreflang is a link attribute that informs Google of the language used on a page. With that information, Google can show the page version corresponding to the language a person is searching in.

Without the hreflang attribute, Google may serve pages in a language the searcher doesn’t speak or pages specific to a country the searcher doesn’t reside.

In the r/TechSEO forum on Reddit, a user is seeking advice regarding the use of hreflang for websites in multiple countries.

They ask if they can get by with a partial implementation of hreflang. For example, they are setting up hreflang for versions of the website in the same language, such as Germany and Switzerland.


The alternative is linking all versions of all pages with hreflang, which is a considerable amount of work.

Mueller says that’s the best solution, but not exactly practical:

“In an idea [sic] world, you’d link all versions of all pages with hreflang. It would be the clean approach, however, sometimes it’s just a ton of work, and maintaining it if the sites are run individually is … good luck with that.”

Although linking every page with hreflang is the ideal solution, Mueller says it doesn’t have to be so complicated.

Hreflang: The Solution

First, Mueller suggests figuring out what needs fixing.

Identify whether a problem exists with searchers landing on the wrong site version.

If that isn’t happening, you may not need to implement hreflang.

Mueller states:

“In practice, you can simplify the problem. Where do you actually see issues with regards to people coming to the wrong country / language site? That’s where you should minimally implement hreflang (and, of course, a JS country/language recognizer / popupper to catch any direct visits). Probably a lot of that will be limited to same-language / different-country situations, so Switzerland / Germany in German may be the right place to start. Nothing breaks if you set up hreflang for 2 versions and have 4 unrelated versions.

If you already have these sites running, I’d check your analytics setup for traffic from Search, and compare the country where they come from vs the country that they end up on (pick one country, filter for the traffic from search, and compare the domains they end up on). If you don’t find a big mismatch there, most likely you don’t need to do a lot (or anything) for hreflang. There is no bonus for hreflang, it’s only about showing the most-fitting page in search for users in a specific country / language.”


Next, look at which pages searchers are landing on. One of the most likely mistakes Google can make is serving the wrong version of a website’s homepage.

Since brand names aren’t localized, Google doesn’t always know which version of a homepage to serve if that’s all a user types into the search box.

If you find searchers are landing on the wrong homepage, but there are no issues with other pages, you can get by with a partial implementation of hreflang.

Mueller states:

“When checking, focus on the most likely mistakes first: same-language / different-country sites is one, but there’s also homepage traffic. Often times a brand name is not localized, so when people search for it, it’s unclear to search engines what the expectation is. If you find a lot of mismatches on the homepage but not elsewhere in the site, you can also just do hreflang across the homepages (that’s often easier than all pages in a site). Or you could do a combination, of course, all homepages + all German-language pages. Hreflang is on a per-page basis, so the beauty (and curse) is that you can pick & choose.”

Lastly, Mueller reiterates that it’s possible to save a lot of time with hreflang by checking to see if there’s a genuine problem.

Google may serve the correct versions of pages all on its own, in which case you don’t gain anything by adding hreflang.

“In any case, before you rush off and work on this for a year, double-check that it’s an actual problem first, and if so, check where the problem is. Maybe there are super-simple solutions (maybe you just need a country/language popup and don’t even need the rest?), and you can spend your time more wisely elsewhere.”

Think of hreflang as a tool to utilize when needed. You can prioritize other tasks if there’s no need for it.

Source: Reddit


Featured Image: patpitchaya/Shutterstock

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