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How To Improve SEO Results With AI-Based Search Engine Modeling

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How To Improve SEO Results With AI-Based Search Engine Modeling

Is your search engine marketing strategy based on industry-wide best practices?

Confused because you’re not getting the results you want?

Not seeing results quickly enough?

You may need personalized SEO recommendations that just aren’t applicable to everyone.

AI-based search engine modeling can improve your SEO results with personalized solutions.

Without adding more work to your day, AI-based search engine modeling can:

  • Predict and test SEO algorithm changes before they hit SERPs.
  • Help get you to the top of the results for your target keywords faster.
  • Lead your organization to a better, personalized, and precise SEO strategy.

Don’t: Rely Only On Best Practices

Search engines are constantly evolving.

Best practices are constantly changing.

Ranking systems and algorithms continue to grow more intelligent.

These algorithm upgrades allow search engines to detect and remove pages with issues and poor user experience from search engine results pages (SERPs).

At the same time, they exchange those removed pages with new pages that match the true intent of the users’ searches.

What you learned yesterday could be old news by the time you update and implement your strategy.

Don’t: Rely Only On Past Data & Experience

“Any SEO tool will spit out 10s or 100s of ‘recommendations,’ most of those are going to be irrelevant to your site’s visibility in search,” John Mueller writes in a Reddit discussion about Core Web Vitals.

He believes that it takes experience to determine which recommendations to take action upon to produce the most valuable results.

Also, Google doesn’t go into detail about the specific ranking factors that shape SERPs; they just offer a basic guide on how their search engine algorithms work.

This is where large amounts of past experience in SEO come in.

Past experience with SEO can help you recognize trends and hope you hit the nail on the head.

But, this can take a lot of time.

The real question – how long will your search rankings suffer as you gain experience with your industry-specific keywords, chosen search engine, and geographic location?

How much time will you spend working on SEO tasks that ultimately won’t affect your visibility in search?

Instead of looking to the past and waiting until your team is up to speed, look to the future with AI-based search engine modeling.

Do: Leverage The Benefits Of AI-Based Search Engine Modeling

So, if you can’t rely on search engines to tell you which factors are most important for rankings, and the feedback loop on real-world results is too slow, what can you use to make impacts sooner?

Search engine modeling.

Search engine modeling creates a space to run experiments based on data-driven, experience-backed theories, so you don’t have to.

You save bandwidth and increase the ability to implement tested results.

Market Brew’s search engine modeling uses artificial intelligence to create customized models for your target search engine and keywords.

How Does Search Engine Modeling Work?

Search engine modeling works by reversing the process used by search engines.

It can create simulated SERPs for your target keywords based on the trends and algorithm of any given day.

Market Brew analyzes the SERPs against the content placed at the top of SERPs for a particular keyword search to determine which ranking factors shape the results.

Search engine models are trained by current SERPs – allowing them to learn the ranking factors that shape the results today.

The outcome?

The ability to focus on a precise SEO plan that will lead to faster, more measurable results in search rankings.

Know Exactly Which Ranking Factors Affect Your Target Keywords

First, use AI-based search engine modeling to find out the current ranking factors.

Using search engine modeling, you can determine what on-site and off-site ranking factors have helped your competitors rank at the top for your target keywords.

Screenshot of a search model within Market Brew revealing the ranking factors and scores for each website competitor, December 2021.

With this information, you can find out exactly how far behind you are from competitors and what it will take to outrank them.

By prioritizing which tasks will help improve your SERP position the fastest, Market Brew helps teams close the gap, work on what matters, and avoid what doesn’t.

Know Which Tasks To Prioritize

Once you know which ranking factors will have a direct impact on increasing your visibility in search engine results, you will know which tasks to prioritize.




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Google Cautions On Blocking GoogleOther Bot

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Google cautions about blocking and opting out of getting crawled by the GoogleOther crawler

Google’s Gary Illyes answered a question about the non-search features that the GoogleOther crawler supports, then added a caution about the consequences of blocking GoogleOther.

What Is GoogleOther?

GoogleOther is a generic crawler created by Google for the various purposes that fall outside of those of bots that specialize for Search, Ads, Video, Images, News, Desktop and Mobile. It can be used by internal teams at Google for research and development in relation to various products.

The official description of GoogleOther is:

“GoogleOther is the generic crawler that may be used by various product teams for fetching publicly accessible content from sites. For example, it may be used for one-off crawls for internal research and development.”

Something that may be surprising is that there are actually three kinds of GoogleOther crawlers.

Three Kinds Of GoogleOther Crawlers

  1. GoogleOther
    Generic crawler for public URLs
  2. GoogleOther-Image
    Optimized to crawl public image URLs
  3. GoogleOther-Video
    Optimized to crawl public video URLs

All three GoogleOther crawlers can be used for research and development purposes. That’s just one purpose that Google publicly acknowledges that all three versions of GoogleOther could be used for.

What Non-Search Features Does GoogleOther Support?

Google doesn’t say what specific non-search features GoogleOther supports, probably because it doesn’t really “support” a specific feature. It exists for research and development crawling which could be in support of a new product or an improvement in a current product, it’s a highly open and generic purpose.

This is the question asked that Gary narrated:

“What non-search features does GoogleOther crawling support?”

Gary Illyes answered:

“This is a very topical question, and I think it is a very good question. Besides what’s in the public I don’t have more to share.

GoogleOther is the generic crawler that may be used by various product teams for fetching publicly accessible content from sites. For example, it may be used for one-off crawls for internal research and development.

Historically Googlebot was used for this, but that kind of makes things murky and less transparent, so we launched GoogleOther so you have better controls over what your site is crawled for.

That said GoogleOther is not tied to a single product, so opting out of GoogleOther crawling might affect a wide range of things across the Google universe; alas, not Search, search is only Googlebot.”

It Might Affect A Wide Range Of Things

Gary is clear that blocking GoogleOther wouldn’t have an affect on Google Search because Googlebot is the crawler used for indexing content. So if blocking any of the three versions of GoogleOther is something a site owner wants to do, then it should be okay to do that without a negative effect on search rankings.

But Gary also cautioned about the outcome that blocking GoogleOther, saying that it would have an effect on other products and services across Google. He didn’t state which other products it could affect nor did he elaborate on the pros or cons of blocking GoogleOther.

Pros And Cons Of Blocking GoogleOther

Whether or not to block GoogleOther doesn’t necessarily have a straightforward answer. There are several considerations to whether doing that makes sense.

Pros

Inclusion in research for a future Google product that’s related to search (maps, shopping, images, a new feature in search) could be useful. It might be helpful to have a site included in that kind of research because it might be used for testing something good for a site and be one of the few sites chosen to test a feature that could increase earnings for a site.

Another consideration is that blocking GoogleOther to save on server resources is not necessarily a valid reason because GoogleOther doesn’t seem to crawl so often that it makes a noticeable impact.

If blocking Google from using site content for AI is a concern then blocking GoogleOther will have no impact on that at all. GoogleOther has nothing to do with crawling for Google Gemini apps or Vertex AI, including any future products that will be used for training associated language models. The bot for that specific use case is Google-Extended.

Cons

On the other hand it might not be helpful to allow GoogleOther if it’s being used to test something related to fighting spam and there’s something the site has to hide.

It’s possible that a site owner might not want to participate if GoogleOther comes crawling for market research or for training machine learning models (for internal purposes) that are unrelated to public-facing products like Gemini and Vertex.

Allowing GoogleOther to crawl a site for unknown purposes is like giving Google a blank check to use your site data in any way they see fit outside of training public-facing LLMs or purposes related to named bots like GoogleBot.

Takeaway

Should you block GoogleOther? It’s a coin toss. There are possible potential benefits but in general there isn’t enough information to make an informed decision.

Listen to the Google SEO Office Hours podcast at the 1:30 minute mark:

Featured Image by Shutterstock/Cast Of Thousands

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AI Search Boosts User Satisfaction

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AI chat robot on search engine bar. Artificial intelligence bot innovation technology answer question with smart solution. 3D vector created from graphic software.

A new study finds that despite concerns about AI in online services, users are more satisfied with search engines and social media platforms than before.

The American Customer Satisfaction Index (ACSI) conducted its annual survey of search and social media users, finding that satisfaction has either held steady or improved.

This comes at a time when major tech companies are heavily investing in AI to enhance their services.

Search Engine Satisfaction Holds Strong

Google, Bing, and other search engines have rapidly integrated AI features into their platforms over the past year. While critics have raised concerns about potential negative impacts, the ACSI study suggests users are responding positively.

Google maintains its position as the most satisfying search engine with an ACSI score of 81, up 1% from last year. Users particularly appreciate its AI-powered features.

Interestingly, Bing and Yahoo! have seen notable improvements in user satisfaction, notching 3% gains to reach scores of 77 and 76, respectively. These are their highest ACSI scores in over a decade, likely due to their AI enhancements launched in 2023.

The study hints at the potential of new AI-enabled search functionality to drive further improvements in the customer experience. Bing has seen its market share improve by small but notable margins, rising from 6.35% in the first quarter of 2023 to 7.87% in Q1 2024.

Customer Experience Improvements

The ACSI study shows improvements across nearly all benchmarks of the customer experience for search engines. Notable areas of improvement include:

  • Ease of navigation
  • Ease of using the site on different devices
  • Loading speed performance and reliability
  • Variety of services and information
  • Freshness of content

These improvements suggest that AI enhancements positively impact various aspects of the search experience.

Social Media Sees Modest Gains

For the third year in a row, user satisfaction with social media platforms is on the rise, increasing 1% to an ACSI score of 74.

TikTok has emerged as the new industry leader among major sites, edging past YouTube with a score of 78. This underscores the platform’s effective use of AI-driven content recommendations.

Meta’s Facebook and Instagram have also seen significant improvements in user satisfaction, showing 3-point gains. While Facebook remains near the bottom of the industry at 69, Instagram’s score of 76 puts it within striking distance of the leaders.

Challenges Remain

Despite improvements, the study highlights ongoing privacy and advertising challenges for search engines and social media platforms. Privacy ratings for search engines remain relatively low but steady at 79, while social media platforms score even lower at 73.

Advertising experiences emerge as a key differentiator between higher- and lower-satisfaction brands, particularly in social media. New ACSI benchmarks reveal user concerns about advertising content’s trustworthiness and personal relevance.

Why This Matters For SEO Professionals

This study provides an independent perspective on how users are responding to the AI push in online services. For SEO professionals, these findings suggest that:

  1. AI-enhanced search features resonate with users, potentially changing search behavior and expectations.
  2. The improving satisfaction with alternative search engines like Bing may lead to a more diverse search landscape.
  3. The continued importance of factors like content freshness and site performance in user satisfaction aligns with long-standing SEO best practices.

As AI becomes more integrated into our online experiences, SEO strategies may need to adapt to changing user preferences.


Featured Image: kate3155/Shutterstock

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Google To Upgrade All Retailers To New Merchant Center By September

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Google To Upgrade All Retailers To New Merchant Center By September

Google has announced plans to transition all retailers to its updated Merchant Center platform by September.

This move will affect e-commerce businesses globally and comes ahead of the holiday shopping season.

The Merchant Center is a tool for online retailers to manage how their products appear across Google’s shopping services.

Key Changes & Features

The new Merchant Center includes several significant updates.

Product Studio

An AI-powered tool for content creation. Google reports that 80% of current users view it as improving efficiency.

This feature allows retailers to generate tailored product assets, animate still images, and modify existing product images to match brand aesthetics.

It also simplifies tasks like background removal and image resolution enhancement.

Centralized Analytics

A new tab consolidating various business insights, including pricing data and competitive analysis tools.

Retailers can access pricing recommendations, competitive visibility reports, and retail-specific search trends, enabling them to make data-driven decisions and capitalize on popular product categories.

Redesigned Navigation

Google claims the new interface is more intuitive and cites increased setup success rates for new merchants.

The platform now offers simplified website verification processes and can pre-populate product information during setup.

Initial User Response

According to Google, early adopters have shown increased engagement with the platform.

The company reports a 25% increase in omnichannel merchants adding product offers in the new system. However, these figures have yet to be independently verified.

Jeff Harrell, Google’s Senior Director of Merchant Shopping, states in an announcement:

“We’ve seen a significant increase in retention and engagement among existing online merchants who have moved to the new Merchant Center.”

Potential Challenges and Support

While Google emphasizes the upgrade’s benefits, some retailers, particularly those comfortable with the current version, may face challenges adapting to the new system.

The upgrade’s mandatory nature could raise concerns among users who prefer the existing interface or have integrated workflows based on the current system.

To address these concerns, Google has stated that it will provide resources and support to help with the transition. This includes tutorial videos, detailed documentation, and access to customer support teams for troubleshooting.

Industry Context

This update comes as e-commerce platforms evolve, with major players like Amazon and Shopify enhancing their seller tools. Google’s move is part of broader efforts to maintain competitiveness in the e-commerce services sector.

The upgrade could impact consumers by improving product listings and providing more accurate information across Google’s shopping services.

For the e-commerce industry as a whole, it signals a continued push towards AI-driven tools and data-centric decision-making.

Transition Timeline

Google states that retailers will be automatically upgraded by September if they still need to transition.

The company advises users to familiarize themselves with the new features before the busy holiday shopping period.


Featured Image: BestForBest/Shutterstock

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