Trending February 2024 # The Next Wave Of Google Algorithm Changes # Suggested March 2024 # Top 4 Popular

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It sounds like Google’s algorithm is going to change again, and while I don’t believe in chasing the algorithm, I do find the impacts on our industry interesting, but even more so the impact it has on user behavior.  The Wall Street Journal’s coverage of changes to Google to get people to stay on site longer to compete against Facebook may actually be a bad strategy for Google and more importantly bad for people.  The article implies Google is slowly moving to an answer engine to compete against Siri, and becoming more semantic in nature.  While I think for the end user this may be a great idea, it may actually hurt Google financially and it will be interesting to see how this evolves.

A Primary Source of Revenue

Here’s an example scenario.  Say I searched for “things to do in Toronto”.  Google’s results may include:

A list of recommended hotels.

The top 5 attractions

The population

The geographic size

Other facts about the city.

The hotel list doesn’t really change from local results, but the top 5 attractions, what impact does this have on tourism?  Instead of getting a link to a page that may be able to cover a great variety of events, and attractions, we’re now stuck with Google’s Top 5 list.  Whether we realize it or not Google is slowly turning our lives into lists, and if you’re not on the list you’re not relevant.

This is why there was a boom in local search when this was introduced.  There will be a boom again as it becomes clearer what types of lists Google will focus on.  How about entertainment? Or restaurants? Or events?  How much of a coincidence that most of these things also have clear schema’s developed?

The Impact to Your World

We know changes to the algorithm also have real world impact as there are countless stories of complaints every time the algorithm changes. Users trust Google so implicitly they don’t question if Google still deserves that trust.  As Google gets better at recommending answers and things to do, will users actually get dumber?  Will users become more homogeneous?  Google already starts to suggest what you should search for as you type, and now they display the results.

Even if Google says they see 20% of searches as new and unique, what volume actually makes up the short head?  Further is the head growing?  Or are there specific categories of searches that are growing and easily classified? I assume we’ll know as we start to see these search results show up.

Why is it a Bad Thing for Google to Keep Users on Their Site?

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Maccabees Update: Google Confirms New Core Algorithm Changes

Today we received confirmation from a Google spokesperson that “several minor changes” were made to the core algorithm this month.

“We released several minor improvements during this timeframe, part of our regular and routine efforts to improve relevancy,” a Google spokesperson told Search Engine Journal.

The timeframe with the most volatility for some websites was between December 12 and 14.

Following published reports about the Maccabees Update, Danny Sullivan, Google’s public liaison for search, downplayed its significance on Twitter:

Reports calling this a single “update” or calling it “Fred” don’t reflect what we actually said: there were several minor changes that happened as they routinely do in any particular week.

— Danny Sullivan (@dannysullivan) December 20, 2023

Learn more: History of Google Algorithm Updates.

What is Update Maccabees (formerly known as Fred)?

Updates to the core algorithm do not receive a formal name. So they are informally named Fred. However, Barry Schwartz of SERoundtable named it Maccabees in recognition of Hanukkah and the search community followed on.

In a separate tweet, Sullivan was wary of giving this flux period a name because it wasn’t a single, major update:

There was no single update. I suppose some might find it useful to give a name to the general flux period, but I think it’s important to understand there were different changes happening — as happen in any week.

— Danny Sullivan (@dannysullivan) December 20, 2023

What Does a Core Update Mean?

Updates to the core algorithm can be a variety of things.

Here are some examples:

Algorithms that determine the relevance of a search query to a web page

Change in how links to a site are scored. This means, some links begin counting less or other links can count more. This will result in a re-ranking of certain kinds of sites. Sites that depend on a single kind of link can be vulnerable if that kind link is devalued.

Change in how page content is scored. For example, if a search query is informational in nature, then a commercial site may be deemed irrelevant.

What Is the Maccabees Update?

First reports of changes to Google’s search results began December 12. The impact is not widespread.

Anecdotal evidence shows that many affiliate type sites have felt it the most.  Normal e-commerce sites have not been affected on the same scale but some have reported as suffering drops in traffic (WebmasterWorld Google Update Discussion), but e-commerce sites appear to be in the minority.

It is tempting to view updates to the core algorithm as targeting a certain kind of site. However, as the Google spokesperson said, these changes are meant to improve relevancy. So that means it could be, as noted above, improvements to on-page or off-page relevance signals, and possibly both.

Here are the prevailing theories and counterarguments:

Maccabees Update is mobile-first related: This theory has been dismissed because some have reported that their sites are mobile friendly and others have reported they’ve seen no increase in Google’s mobile bot.

Desktop visibility affected more than mobile visibility: This is an interesting hypothesis but some have reported the opposite. I am inclined to rule this out.

What Kinds of Site are Affected by the Maccabees Update?

Given the timing, it may not be far fetched to speculate that this relevancy change might be shopping related, especially given how many affected publishers are in the shopping space.

I’ve been seeing quite a bit of concern in Facebook groups associated with aggressive linking techniques. This isn’t to say that this is a link related issue.

It could be that those kinds of sites share certain attributes related to their sites. It could be that they lack certain on-page or off-page signals of authority.

There are many affiliate sites that are still ranking fine. So it’s definitely not an affiliate related update. But it may be related to something that aggressive sites share in common.

Jim Boykin of Internet Marketing Ninjas told me that he checked and double checked the rankings of client sites and reported, “nothing changing in rankings or Google organic traffic for the past month.”

Casey Markee, of MediaWyse in San Diego offered this clue:

“I did have some sites contact me and they did have drops… Their content and overall user experience though had some holes.”

I polled some affiliate site publishers who had been affected and they shared that both mobile and desktop traffic has been affected. So there you are, a minor update to the core algorithm that feels major to certain sites on the Internet.

If you have been affected and feel it’s not merited, if the site truly does not merit, then history has shown that Google tends to dial back on changes when they find it’s been creating false positives.

Image Credits

All images via Shutterstock, modified by author

Decoding The Next Generation Of Ai

Robotics brings together a wide range of different machines including Pepper partnering with soft-bank; the Boston Dynamics humanoid robot Atlas, which can do backflips in movies and television and a plethora of humanoids and Bots that leave the human mind with awe and inspiration to achieve new tech heights. Much that the technology that powers robotics continues to achieve new pinnacle; people not familiar with the developments tend to hold polarized views, ranging from unrealistically high expectations of robots with human-level intelligence, or an underestimation of the potential of new research and technologies. Over the past years, questions have been asked about what is actually going on in deep reinforcement learning and robotics industry. How are AI-enabled robots different from traditional ones and their underlying potential to revolutionize various industries, what is the new excitement the robotics industry holds for the future. These questions point towards the challenging world of robotics and how difficult it can go to understand the current technological progress and industry landscape, to enable tech giants and newbies alike to make predictions for the future.  

The Uniqueness Behind the AI powered Robots

So what is about the robot evolution from the automation to autonomy? What started off as a quest to make routine work easy through automation has come a long way towards full robot autonomy? AI brings a game changer approach to robotics by enabling a move away from automation to true self-directed autonomy. When the robot needs to handle several tasks, or respond to humans or changes in the environment, it essentially needs certain levels of autonomy. The path from autonomy has been an uphill but a truly worthwhile change. According to a source, the evolution of robots can be explained by burrowing case studies from the autonomous car space. For an easy explanation of the process underlined below, robots are defined as the programmable machines capable of carrying out complex actions automatically. •  Level 0 stage is also called as the No automation stage where people operate machines, there is no automation without any robotic involvement. •  Level 1 stage is the driver assistance level, where a single function or task is automated, but the robot does not necessarily use information about the environment. Traditionally, robots are deployed in automotive or manufacturing industries programmed to repeatedly perform specific tasks with a high precision and speed. •  Level 2 stands for partial automation where a machine assists with certain functions, using sensory input from the environment to automate some operational decisions. Examples include identifying and handling different objects with a robotic vision sensor. In this stage, robots lack the ability to deal with surprises, new objects or changes. •  Level 3 is the Conditional autonomy where the machine controls the entire environment monitoring, but still requires a human’s intervention and attention for unpredictable events. •  Level 4 is the high autonomy stage where the machine is fully autonomous in certain situations or defined areas. •  Level 5 is the complete autonomy level powering the machine with full automation in all situations.  

The Current Stage of Automation

Today, a majority of robots deployed in factories are non-feedback controlled, or open-looped implying that their actions are independent from sensor feedback as that happens in level 1 stage as discussed above. Few robots in the business act and take commands based on sensor feedback as that happens in Level 2. A collaborative robot, or co-bot, is designed to be more versatile empowered to work with humans; however, the trade-off is less powerful and happens at lower speeds, especially when compared to industrial robots. Though a co-bot is relatively easier to program, it is not necessarily autonomous to handle. There is often a need of human workers to handhold a co-bot every whenever there is any change in the environment or the task. Pilot projects integrated with AI-enabled robots, have started to become a regular feature incorporating a Level 3 or 4 autonomy, like warehouse piece-picking. Traditional computer vision cannot handle a wide variety of objects like that in e-commerce because each robot needs to be programmed beforehand and each item needs to be registered. However reinforcement learning and deep learning has enabled robots to learn to handle different objects with minimum human assistance. In the times to come, there might be some goods that robots have never encountered before which would need a support system and a demonstration from human workers bringing the level 3 of automation. In the times to come, improvements will be seen into algorithms to get closer to full autonomy as the robots collect more data and improve through trial and error in Level 4. Taking a clue from the autonomous car industry, robotics startups are additionally taking different approaches to autonomy for their robots. Some aspects believe in a collaborative future between robots and humans, and focus on Level 3 mastery. While in a fully autonomous future, skipping Level 3 and focusing on Level 4, and eventually on Level 5 will be difficult to assess the actual level of autonomy.  

The Age of AI-Enabled Robots in Industries

Taking the brighter side, robots are being used in a lot more use cases and industries than ever before. AI-enabled robots are running warehouses, in a semi-controlled environment, picking up critical pieces that are fault-tolerant tasks. On the other hand, autonomous home or surgical robots will be a reality of the future, as there are uncertainties in the operating environment, where some tasks are not recoverable. With the change in time, the human eyes will see more AI-enabled robots being used across industries and scenarios as reliability and technology precision improves. The world has seen only about 3 million robots, most of which work on welding, assembly and handling tasks. There have been very few robot arms being used in varied industries like agriculture, industries or warehouses apart from electronics and automotive units, due to the limitation of computer vision.

Robotics brings together a wide range of different machines including Pepper partnering with soft-bank; the Boston Dynamics humanoid robot Atlas, which can do backflips in movies and television and a plethora of humanoids and Bots that leave the human mind with awe and inspiration to achieve new tech heights. Much that the technology that powers robotics continues to achieve new pinnacle; people not familiar with the developments tend to hold polarized views, ranging from unrealistically high expectations of robots with human-level intelligence, or an underestimation of the potential of new research and technologies. Over the past years, questions have been asked about what is actually going on in deep reinforcement learning and robotics industry. How are AI-enabled robots different from traditional ones and their underlying potential to revolutionize various industries, what is the new excitement the robotics industry holds for the future. These questions point towards the challenging world of robotics and how difficult it can go to understand the current technological progress and industry landscape, to enable tech giants and newbies alike to make predictions for the chúng tôi what is about the robot evolution from the automation to autonomy? What started off as a quest to make routine work easy through automation has come a long way towards full robot autonomy? AI brings a game changer approach to robotics by enabling a move away from automation to true self-directed autonomy. When the robot needs to handle several tasks, or respond to humans or changes in the environment, it essentially needs certain levels of autonomy. The path from autonomy has been an uphill but a truly worthwhile change. According to a source, the evolution of robots can be explained by burrowing case studies from the autonomous car space. For an easy explanation of the process underlined below, robots are defined as the programmable machines capable of carrying out complex actions automatically. • Level 0 stage is also called as the No automation stage where people operate machines, there is no automation without any robotic involvement. • Level 1 stage is the driver assistance level, where a single function or task is automated, but the robot does not necessarily use information about the environment. Traditionally, robots are deployed in automotive or manufacturing industries programmed to repeatedly perform specific tasks with a high precision and speed. • Level 2 stands for partial automation where a machine assists with certain functions, using sensory input from the environment to automate some operational decisions. Examples include identifying and handling different objects with a robotic vision sensor. In this stage, robots lack the ability to deal with surprises, new objects or changes. • Level 3 is the Conditional autonomy where the machine controls the entire environment monitoring, but still requires a human’s intervention and attention for unpredictable events. • Level 4 is the high autonomy stage where the machine is fully autonomous in certain situations or defined areas. • Level 5 is the complete autonomy level powering the machine with full automation in all situations.Today, a majority of robots deployed in factories are non-feedback controlled, or open-looped implying that their actions are independent from sensor feedback as that happens in level 1 stage as discussed above. Few robots in the business act and take commands based on sensor feedback as that happens in Level 2. A collaborative robot, or co-bot, is designed to be more versatile empowered to work with humans; however, the trade-off is less powerful and happens at lower speeds, especially when compared to industrial robots. Though a co-bot is relatively easier to program, it is not necessarily autonomous to handle. There is often a need of human workers to handhold a co-bot every whenever there is any change in the environment or the task. Pilot projects integrated with AI-enabled robots, have started to become a regular feature incorporating a Level 3 or 4 autonomy, like warehouse piece-picking. Traditional computer vision cannot handle a wide variety of objects like that in e-commerce because each robot needs to be programmed beforehand and each item needs to be registered. However reinforcement learning and deep learning has enabled robots to learn to handle different objects with minimum human assistance. In the times to come, there might be some goods that robots have never encountered before which would need a support system and a demonstration from human workers bringing the level 3 of automation. In the times to come, improvements will be seen into algorithms to get closer to full autonomy as the robots collect more data and improve through trial and error in Level 4. Taking a clue from the autonomous car industry, robotics startups are additionally taking different approaches to autonomy for their robots. Some aspects believe in a collaborative future between robots and humans, and focus on Level 3 mastery. While in a fully autonomous future, skipping Level 3 and focusing on Level 4, and eventually on Level 5 will be difficult to assess the actual level of autonomy.Taking the brighter side, robots are being used in a lot more use cases and industries than ever before. AI-enabled robots are running warehouses, in a semi-controlled environment, picking up critical pieces that are fault-tolerant tasks. On the other hand, autonomous home or surgical robots will be a reality of the future, as there are uncertainties in the operating environment, where some tasks are not recoverable. With the change in time, the human eyes will see more AI-enabled robots being used across industries and scenarios as reliability and technology precision improves. The world has seen only about 3 million robots, most of which work on welding, assembly and handling tasks. There have been very few robot arms being used in varied industries like agriculture, industries or warehouses apart from electronics and automotive units, due to the limitation of computer vision. Over the next 20 years, the world will witness an explosive growth and a changing industry landscape which will bought by the next-generation robots as reinforcement learning, cloud computing and deep learning unlock the robotic potential.

Google Predicts These 4 Pandemic Changes Are Permanent

Companies have changed the way they do business since the pandemic. In a new report, Google forecasts which of those changes are here to stay.

Citing search data to back up some of its predictions, Google says these pivots will become permanent:

Using real-time tracking insights to rapidly respond to consumers.

Holding virtual events.

Working from home.

Offering more convenient ways for consumers to buy online.

Google acknowledges all sectors had to rethink their approach to marketing during the pandemic. Business is likely to resume a degree of normalcy when the pandemic is over, but these consumer-friendly shifts won’t be forgotten.

Rapid Response to Changes in Consumer Habits

Consumer habits are evolving at a frantic pace throughout the pandemic, which is forcing businesses to get better at tracking real-time insights and responding to the data.

Habit Change: Searching Before Shopping

Consumers are increasingly turning to Google Search to find which businesses have items in stock before venturing out to a store.

Google points to data from the early months of the pandemic. Searches for “who has” and “in stock” were up over 8,000% year over year in the U.S.

Habit Change: Fewer Trips For Groceries

Consumers are limiting their trips out for food, as Google cites a growing search interest in queries like “can you freeze” in the U.K. and “home delivery” in France.

Habit Change: Saving More, Spending Less

As the pandemic continues to take a toll on personal income, many consumers are saving more and spending less on nonessential items.

Google cites data from a Kantar study showing 71% of people in G-7 countries say their personal income had or would be impacted by the pandemic.

The impact to personal income is highest in Italy (85%), the U.S. (75%), and Canada (75%).

A BCG report finds, of the people who expect to change their spending habits, 29% say they’ll save more and 27% say they’ll spend less on nonessential items.

Habit Change: Consumers Will Find Alternatives

Consumer behavior throughout the pandemic shows they’re keen to find alternatives when something they depend on gets taken away.

When schools were shut down, Google says searches for “online learning” went up 400% year over year.

When gyms were forced to close, searches for fitness apps jumped 200% year over year.

When the world became too isolating, people sought to cultivate connections online. Searches that included the phrase “with friends online” went up 300% year over year.

Searches for “watch party” (for example, “youtube watch party” or “private watch party”) grew 400% year over year.

Takeaway From Google

“To better respond to rapid shifts in consumer behavior, brands created real-time insights tracking, elevated insights within their organizations, and established new processes to quickly act on their discoveries. This new reality will ensure brands are positioned to lead with insights.”

Virtual Events Will Continue

The pandemic forced all in-person events to cancel, which lead to marketing teams pivoting toward virtual events.

Live events will eventually return, but Google predicts they’ll look different.

Now that consumers have experienced the convenience of attending events from their living room, live events will need to deliver an outstanding experience to draw them back in.

Working From Home Will Continue

Google predicts the changes businesses were forced to make to the traditional in-office work model are here to say.

Search and shopping data suggests the pivot to working from home started before the pandemic. People have been exhibiting a growing desire to spend more time doing what brings them joy and less time doing things like commuting.

For businesses, Google says this means continuing to find ways to meet people’s basic needs:

“The in-office work model has likely changed forever, shifting consumer habits and workplace cultures. For businesses, this means finding ways to meet people’s most basic needs and taking steps to foster a more resilient workforce.”

Online Shopping is Now The Norm

Ecommerce took off during the pandemic, with some people turning to online shopping for the first time in their lives out of necessity.

Googles notes there was an increase in shopping activity for items people wouldn’t ordinarily buy online.

“There was a meaningful increase in the number of people willing to buy groceries, clothing, and even cars online. In the first six months of 2023, for example, nearly 10% of cars were sold online, compared with just 1% of cars sold online during all of 2023.”

Brick-and-mortar businesses had to pivot toward offering options such as local delivery and curbside pickup.

These new and more convenient shopping habits likely won’t go away after the pandemic.

Source: Think with Google

Algorithm To Get The Combinations Of All Items In Array Javascript

In this problem statement, our task is to get the combinations of all items in an array with the help of Javascript functionalities. So for doing this task we can use a recursive approach that iteratively adds items to a running list of combinations.

Understanding the problem statement

The problem statement is to write a function in Javascript that will help to find out the combinations of all the elements in an array and create a separate array to show these combinations. For example, if we have an array [ 1, 2 ] so the combinations of this array will be [ [ 1, 2 ], [ 2 ] ].

Logic for the given problem

To create a function to get all the possible combinations of items in an array in Javascript can be done using a recursive algorithm which will iteratively add items to a list of combinations. So first we will define an array and initialize it as empty. Inside the created function we will define another function to recurse the running list of combinations.

Algorithm

Step 1 − Declare a function called getCombinations which is using a parameter of array.

Step 2 − Declare a result array inside the function which will hold our final list of combinations.

Step 3 − Define another function called recurse which will take two arguments cur and rem, here cur is the running list of items and rem is the array of items we have left to add in the combinations.

Step 4 − And after this if there are no items left in the rem array we will push current into the result array because we have reached the required result.

Step 5 − Otherwise we will iterate every item in the rem array and recursively call a recursive function with a new cur array that will include the current item.

Step 6 − Call recurse initially with an empty cur array and the full array we want to generate combinations for.

Step 7 − Return the final result array which contains all possible combinations of the input array.

Code for the algorithm function getCombinations(array) { const result = []; function recurse(cur, rem) { if (rem.length === 0) { result.push(cur); } else { for (let i = 0; i < rem.length; i++) { recurse([...cur, rem[i]], rem.slice(i + 1)); } } } recurse([], array); return result; } const array = [10, 20, 30, 40]; const combinations = getCombinations(array); console.log(combinations); Complexity

The time complexity for the above created function is O(2^n) because the algorithm generates all possible combinations of items in the array and there are 2^n possible combinations. And the space complexity for the code is also O(2^n) because the algorithm generates a list of 2^n combinations.

Conclusion

The above code provides a simple solution to generate all possible combinations of items in an array in Javascript. So it has an O(2^n) time and space complexity which can make it less efficient for large arrays. So it is important to note the size of the array when deciding whether to use this algorithm.

#Sejsummit Speaker Glenn Gabe On This Year’s Google Changes

Your SEJ Summit presentation is titled: What the Doctor Ordered: Your Yearly Google Algorithm Update Checkup (2024 Edition). In your opinion, what was the biggest update SEOs should be paying attention to this year?

Based on its frequency and level of impact, I believe Google’s quality updates (AKA Phantom) are incredibly important to pay attention to. And we’ve seen several quality updates in 2024.

As a quick reminder, the first quality update rolled out in May of 2024 and impacted many sites globally. Google finally confirmed that they did roll out an update and explained that it was a change to its core ranking algorithm with how it assessed “quality”. And with Google always trying to surface the highest quality and most relevant content for users, that’s an incredibly important statement.

Since May of 2024, we’ve seen six significant quality updates (and three in 2024 so far). The updates are global and industry-agnostic (I’ve seen many different types of sites impacted by Phantom). And websites seeing impact during a quality update can absolutely see the impact by subsequent updates (either reversing course, surging more, or declining further). That’s why I believe SEOs and business owners should be keenly aware of Phantom, and its history. Here are my posts about the November and June quality updates. Both were significant.

For example, here are two sites surging and dropping during the November 2024 update, and both saw impact during Phantom 2 as well (in May of 2024):

Let’s talk about Phantom. Part of what makes this update so elusive is that Google plays the ‘neither confirm nor deny’ game. What do SEOs most need to know about this update? Should we be worried?

You’re right; Google will typically not confirm changes to its core ranking algorithm. That said, they did confirm the first quality update, and then confirmed “core ranking algorithm changes” during certain subsequent updates.

But when major algorithm updates roll out, you can start to see a connection with previous updates. For example, sites impacted by a new update that also saw impact during previous quality updates. That’s when you can start to understand if the update was indeed Phantom.

Here is an excellent example of a site seeing impact across several quality updates. You can clearly see the connection between them:

But to make matters even tougher for SEOs, Google can absolutely retire Phantom at any point. They can also push it to real-time at some point. And if they do either, then we’ll have no idea that happened and may never see another immediate drop or spike like in the past (with Phantom anyway).

On that note, Panda is now part of Google’s core ranking algorithm. It’s not real-time yet, but continually rolls out slowly across the web. Therefore, we’ll never see another old-school Panda update (with significant movement all on one day). And I believe Google likes it that way. No drama, no media attention, no subsequent analysis, etc.

Moz is reporting an “unnamed update” in just the last week or two. (September 2024). What are your thoughts on their report?

Yes, there was another big update starting on August 31, 2024. But I don’t believe we saw just one update. I believe we saw three (two roll out and one being tested).

The first was spotted by Joy Hawkins and it was a local algorithm update. That rolled out about the same time as a core ranking algorithm update (which I believe was another quality update). Many of the sites impacted by the core ranking algo change (that rolled out after the local update) had been previously impacted by other quality updates. And then about a week later I saw sites that had previous link problems (and Penguin problems) spike. Others saw that too, like Marie Haynes.

So Google could have been testing Penguin 4 (or another link-based algorithm). And now that we know Penguin 4.0 rolled out, which Google announced on September 23, that third movement we saw very well could have been Penguin 4 being tested in the wild.

Needless to say, it’s always tricky when Google rolls out multiple algorithm updates at one time, or across a short period. And yes, Google can and will roll out multiple updates simultaneously. My favorite example was the algorithm sandwich in April of 2012. That’s when Google rolled out Panda, then Penguin 1.0, and then Panda again all within a ten-day period. It was crazy.

What strategies do you recommend for long-term Google algo update protection? I hear a lot of “just write good content, and you will always be safe!” That isn’t particularly actionable. Is there anything else brands can or should be doing?

Also, technical problems could cause quality problems as well. For example, canonicalization problems, chúng tôi issues, mobile problems, render problems, etc. can all impact SEO. If you are on top of the situation, then you can quickly rectify any issues that pop up. But if you’re not aware of them, then the problems will keep building until you get blindsided. And I’ve received many calls from business owners who have been blindsided by algorithm updates in the past.

So, auditing content that gets published, educating writers, editors, and others that are in control of publishing content, crawling and auditing a site over time, reviewing links on a regular basis to ensure something funny isn’t going on, and then nipping any problems in the bud to ensure they don’t become bigger and scarier problems. That’s how you can protect your site from getting dinged during future algorithm updates.

Looking forward, what is the #1 thing SEOs need to be thinking about as we move toward 2023?

With so many changes and new things going on in SEO, it’s really hard to pick the number one area to focus on. That said, I’ll quickly cover two areas that webmasters need to be aware of.

First, if Google keeps rolling out quality updates (Phantom), then webmasters should be keenly aware of those updates and the quality of their own sites. I covered this earlier, and it’s extremely important. We’ve seen quality updates roll out every few months, and the last was early September. So we will probably see another at the beginning of 2023 (just like last year). So keep your eye on Phantom. It’s certainly keeping its eye on you. 🙂

Next, and to state the obvious, mobile is booming. I have some clients with 80%+ mobile traffic. So staring at the beautiful desktop experience you are providing may not mean very much. I would make sure your mobile experience is as strong as possible. Google has a mobile-friendly algorithm, and it plans to incorporate mobile speed into the equation at some point. So I would start taking a hard look at how mobile users experience your website, how fast those pages load, if there are obstacles, etc.

Also, accelerated mobile pages (AMP) started rolling out to the core mobile SERPs on 9/20. I think AMP should be an area that business owners take a hard look at, since amplified pages load near-instantaneously for mobile users and Google is pushing AMP hard. I’m not saying every site should jump on the AMP bandwagon, but business owners should evaluate its performance, how it works for users, how it impacts conversion, revenue, etc.

And then there’s the mobile popup algorithm that’s rolling out in January of 2023. Many sites will be impacted by that, and some probably have no idea it’s coming. If a site is presenting popups or interstitials on the first page from the search results, then those pages could be demoted in the mobile search results. And popups and interstitials are used so heavily now by publishers that the algorithm will definitely impact many pages across the web.

Therefore, I highly recommend that sites evaluate their use of popups and interstitials, make the necessary changes well ahead of January 1, 2023, and then be ready for the algo to roll out. One thing is for sure, it should be interesting.

Don’t forget; you can still buy tickets and come learn more from speakers like Glenn  in NYC Nov. 2nd at the TimesCenter in Manhattan.

Image Credits

Screenshots taken by Glenn Gabe Sept 2024

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