SEO Archives SEO

May 16 2024

What’s The Ideal Blog Post Length For SEO? via @sejournal, @searchmastergen

Whether there’s an ideal blog post length for SEO has been the subject of debate for as long as search engines have been on the web.

If I may borrow a phrase from Google itself, the answer to that question is “it depends.”

The two main variables to consider when deciding how long your posts should be are:

Subject matter.
Searcher intent.

The ideal length of a blog post on how to take the perfect selfie is going to be different from the ideal length of a post on the invention of the digital camera.

Why? For starters, one subject demands more information than the other in order to provide a complete answer.

Say what you will about the intricacies of selfie-taking, there’s simply more to cover when talking about the invention of the technology that makes selfies possible.

Secondly, searcher intent is a major factor to consider in the length of a blog post. Do they want to read a short or long article?

It’s likely the person who wants to learn about the history of digital photography is looking to consume a more substantial article than the person looking for selfie tips.

Despite the fact that global attention spans are narrowing, long-form content still performs exceptionally well in search.

However, short content is more than capable of ranking alongside longer content in search results. One isn’t necessarily better than the other.

There are literally hundreds of factors that go into ranking search results.

Is article length one of them? If so, what is the ideal word count?

Let’s look at what the statistics say.

Statistics Don’t Lie

Stats offer a pretty good starting point, but we all know they can sometimes also be manipulated.

So, let’s get something clear from the get-go: regardless of length, there is always going to be good content and there is always going to be bad content.

Studies examining hundreds or thousands of pages of content, like the one mentioned above, are probably not examining which content is really good, which is really bad, which is mediocre, and so on.

It’s analyzing article length and how that may affect how good or bad that content ends up being based on simple practicality.

It’s probably true that shorter content is easier and faster for people to read; I’m not going to dispute that.

But does that one-word answer satisfy the question/query a user is looking for? Sure, some questions can be answered in as little as one word, but that’s not usually quality content.

That’s a one-word answer with no explanation or sourcing, and Google (usually) knows that’s not enough to distinguish a piece of content as high-quality, educational, and resourceful.

Of course, there are one-word answers that would be deemed useful and could score the featured snippet in Google, also called Position Zero.

Plus, good content comes in many forms; it’s compelling and often easier to digest because of sourcing, rich media, and sensible structure/formatting.

Google wants substance, evidence, and facts from authority entities on whatever the topic may be. Turns out, longer content typically has these elements baked into it.

That’s a big reason why long-form content ranks better in organic search than short content.

According to a HubSpot study from 2021, the ideal blog post length for SEO should be 2,100-2,400 words.

That’s a lot longer than the 200- or 500-word blog posts most writers or webmasters think is ideal.

Depending on the query, the search results on Page 1 may not be flooded with blog-style content, but the content that is going to be deemed resourceful by users — and Google — certainly may include well-constructed, thoughtful blogging content that satisfies a search query.

And that should be your goal as you begin planning content ideas and article structure for your website’s blog and other written on-site content.

What Does Google Say About Blog Post Length?

Google stands firm that word count is not a ranking factor.

There’s an entire episode of SEO Mythbusting dedicated to the topic of 0n-page content.

Google’s Martin Splitt confirms the number of words on a page is not taken into consideration when ranking search results.

What he means by that is Google does not total up the number of words on a page and use that number as an indication of quality.

A page with 1,000 words is not automatically seen as higher quality than a page with 500 words because it has twice as much content, for example.

That messaging is consistent whenever Googlers are asked about word count, which is a topic that comes up quite often.

Here’s Google’s John Mueller getting asked about it on Twitter. He states:

“Word count is not indicative of quality. Some pages have a lot of words that say nothing. Some pages have very few words that are very important & relevant to queries. You know your content best (hopefully) and can decide whether it needs the details.”

It’s important you don’t read that statement and think you can publish the bare minimum amount of content because Google doesn’t care how many words are on a page.

The number on its own means nothing to Google. However, Google’s algorithm is designed to satisfy user intent, and the intent of the search may call for a longer article over a shorter one.

What you should take away from Google’s position on blog post length is to focus on satisfying searchers. If a short post satisfies the query, then there’s no need to extend the length in hopes of pleasing Google.

Quality Over Quantity: Don’t Focus On Article Length

Too many people put too much emphasis on the average word length for articles and the misunderstood importance of having more than a certain number of words on each page to rank well.

Sure, it’s important to have some substance (and length) to the piece, but it’s not worth publishing a 2,500-word redundant review of a movie talking about the main character’s bad hair and foul language four different ways throughout the entirety of the content.

Surely the movie offered other elements and scenes that make the movie good or bad. Talk about them. Expand on real situations with reactions and in-depth explanations.

That’s what people are looking for when they search for information about a movie. “Was the movie good?”; “Why was it good or bad?”; and “Should I watch it?” are the real questions. The best movie reviews answer all three of those questions and don’t make it hard to figure out.

Give users what they want regardless of how many words it takes to say it. If it feels like you’re writing uninteresting copy for the sake of inflating the word count, know that your readers can feel it as well.

Moreover, Google is capable of recognizing content that contributes little to no added value to the web. That means longer posts can actually hold your site back in search if they don’t say anything useful.

Choose Your Target Audience: People, Personas, And Keywords

Like all good web content, you need to have a goal — a target.

You need to study your target audience. Who’s going to search for and consume your content?

You also need to consider that person’s level of intent as well; are they looking for basic discovery information, or are they trying to buy something right now in as few clicks as possible? Your content will reflect that person and their different stages of user intent.

Ideally, good content is mapped out before it is even created. It should connect the goals of your website/business and the content you are publishing with the goals of the users looking for it.

If you’ve done your audience research and still aren’t sure how long your posts should be, you can get a better idea by looking at the content they’re already consuming.

Search for keywords you want to target and examine the content that shows up on the first page. The length of those blog posts is a good source of insight into what it takes to answer those queries.

Content should satisfy a user’s search query. Thus, content should satisfy the user.

And, most importantly, there may very well be similar content on a website that satisfies various stages of user intent for one specific topic. That isn’t an accident.

Don’t Just Focus On Written Page Copy

Quality content goes beyond just written words. The best content connects thorough research and respectable writing with a user’s interest (their search query).

Even a great video should be accompanied by well-written text that explains the video, it’s concept and goals, and any other resources that may improve the content to better help the user.

That’s our ultimate goal as content strategists: offer the best information, in the most appropriate format, on the right platform.

For some topics, a blog post may not even be the best way to communicate the information to searchers. A detailed tutorial, for example, might be more suited for a video demonstration.

Content like an interview with an industry expert may be more preferable to consume in audio format than in plain text.

Sometimes the written word is the best way to communicate information. But other topics are more suited to visual, requiring photos or video. Sometimes, audio files will be the best type of rich media.

When you use visual or audio content, be sure to accompany it with written content that can connect the dots and make sense of everything on the page, as well as help users find your content.

That’s not only a good practice for readers, it’s necessary for Google as well. Word count is irrelevant, at least some written content is required to provide context to photos, videos, and audio shows.

Summary

Your content can take many forms, and it can be discovered and consumed in numerous ways.

It shouldn’t be your goal to write 2,500 words on a blog post because that seems like the “perfect length” to rank well in organic search.

If you’re worried about hitting an ideal blog post length for SEO, then you’re missing the point entirely.

Your goal should be to supply the best, most useful (and optimized) version of the content for your target audience that matches their intent.

Your audience will appreciate it – and your website analytics will reflect that.

More resources:

Featured image: fizkes/Shutterstock

FAQ

Does the length of a blog post affect its SEO performance?

The length of a blog post can affect its SEO performance, but it’s not the sole factor. Quality content that meets user intent is more important. Longer content tends to include more detailed information, which can help satisfy user queries better, leading to higher rankings. However, short content can also rank well if it effectively answers the searcher’s question. Focus on the substance and quality of your content rather than just the word count.

What factors should be considered when determining the length of a blog post?

When determining the length of a blog post, consider the subject matter and searcher intent. Some topics naturally require more detail than others. For instance, a post about the history of digital cameras may need more words than a post about taking the perfect selfie. Additionally, consider what the searcher is looking to achieve; are they seeking a quick answer or an in-depth exploration?

How can I create content that ranks well in search results?

To create content that ranks well, focus on providing value and meeting user intent. Conduct thorough audience research to understand what your target readers are looking for. Use appropriate keywords and ensure that your content is well-structured, including sourcing, rich media, and logical formatting. Combine written content with other formats like videos, audio, or images if they help to better explain your topic. Quality and relevance should be prioritized over simply aiming for a specific word count.

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May 16 2024

SEM Vs. SEO: What’s The Difference? via @sejournal, @searchmastergen

CSS. HTTP. URL. HTML.

It’s possible the only field that uses more acronyms and initializations than web marketing is the military.

The military uses them to save time.

Sometimes, it seems like our industry only uses them to confuse newcomers.

And it’s not uncommon for even experienced professionals to mix them up.

Some of the most common mistakes happen when it comes to the similar and related, but distinctly different concepts of search engine optimization (SEO) and search engine marketing (SEM).

Once upon a time, in the halcyon days of the early internet (that is, circa 2001), SEO referred to a part of SEM.

But, as the language and nuance of web marketing shifted, search engine marketing came to refer to a specific type of digital marketing. So, what’s the difference?

Sometimes also referred to as organic (SEO) and inorganic (SEM) search, both are focused on using Google (and to a lesser extent other search engines) to drive traffic to a specific website.

From a high-level view (and don’t worry, we’ll dive into the details a bit later), SEO is the process of improving your website to generate traffic, while SEM is using paid methods to show up in searches.

Don’t feel bad if you’ve mixed these terms up. It happens all the time.

To help you avoid any embarrassing mishaps when speaking with other digital marketers, we’ve compiled this handy guide to give you an overview of these concepts.

Confused? Don’t be, all will be made clear in the end. Now let’s get started.

PPC, Another Variable In The Mix

As we get started, just to make everything even more confusing, let’s add one more initialization into the mix: PPC or pay-per-click.

Okay, that one isn’t really fair because PPC is just another term for SEM – or at least, a part of it.

PPC is most likely a term that evolved through the Wild West days of early search engine strategies when different people used different terms to refer to the same thing.

Eventually, pay-per-click and search engine marketing came to mean the same thing: paid digital marketing advertisements on search platforms.

Pay-per-click, regardless if it’s called PPC, CPC (that is cost-per-click), paid search, or search ads are referring to paid search marketing, typically through search engines like Google and Bing.

Other terms and tactics used in digital marketing initiatives – especially those tied to search marketing tactics (both paid and organic) – may not be so simple and clearly defined, though.

What’s The Difference Between SEO & SEM/PPC?

We know SEO is search engine optimization.

Marketers aren’t optimizing search engines, however. We’re optimizing content and websites for search engines (and humans, too), so they can better understand, access, and direct searchers to our website.

Again, initialism doesn’t always make sense. So, naturally, this is a bit illogical.

Just like other things in life that don’t always add up, there are some acronyms that will never make sense either.

Like Humvee, which doesn’t stand for any words that start with U or E in them. (It actually stands for High Mobility Multipurpose Wheeled Vehicle, and was spawned from the original acronym, HMMWV.)

We’ve also determined that PPC marketing is (at least now) the same as or a very large part of SEM. Here’s where they overlap:

Both are paid initiatives.
Both need a budget.
Both make search engines like Google and other advertising platforms a lot of money.

But, while Wikipedia defines SEM as “a form of internet marketing that involves the promotion of websites by increasing their visibility in search engine results pages (SERPs) primarily through paid advertising,” it’s not so quick to call them the same exact thing.

In fact, pay-per-click marketing has its own Wikipedia page separate from search engine marketing (despite there being plenty of discrepancies and confusion throughout the page).

The bottom line is this:

SEO is not a component of SEM.

And, while PPC is typically the largest and most demanding component of SEM, both PPC and SEM are paid initiatives that offer real-time data, ROI, and protected data that can only be accessed by advertisers on certain platforms.

Why It Matters

Consistency is the main reason it’s important to clarify these terms.

Too many novice marketers, or marketers who aren’t specialists in maximizing value through search, have adopted these industry definitions and crossed them, combined them, confused them, or used them in a way that only further diluted their true meaning.

And even well-seasoned marketers who simply didn’t agree with or possibly even completely understand the terms themselves help contribute to the turning tide, as well.

Conferences have set up entire segments of their educational offering around the SEM naming convention when referring to strictly paid marketing efforts, but those efforts aren’t strictly done through search engines.

SEM, at least from this perspective, includes PPC ads on search engines but also on third-party platforms like Amazon and YouTube, as well as industry-focused platforms like Houzz, Thumbtack, or Yelp. It also includes display ads and remarketing efforts.

And, as the opportunity to advertise on social media continues to grow, it is usually used to refer to paid advertising on those networks, too.

Here at Search Engine Journal, we’re doing our part. Keeping the definitions and their usage consistent is going to be the best way to keep the information organized in a way that makes sense for marketers.

It also helps us, as marketers, convey our thoughts and ideas to clients and stakeholders, peers, or a friend who is curious about just what exactly it is we do for a living.

But, you should never assume someone else knows what you’re referring to when you use these terms.

Be concise and explain exactly what you’re talking about and make sure everyone agrees on term definitions.

Before we move on, let’s recap:

SEO is the organic effort that goes into marketing through search engines.
SEM and PPC are paid initiatives through search and other platforms.

Now that we have that out of the way, let’s move on.

Should I Use SEO Or SEM?

Now that you hopefully have a grasp on the differences between SEO and SEM, you’re undoubtedly asking yourself a question: Which one should I be using?

Ideally, both.

But if you don’t have the bandwidth and can only choose one, here are some things to consider:

What Are Your Goals?

If you want to drive traffic quickly, whether to promote a sale, try out a new offer or just give your website more exposure, SEM is the choice for you.

SEO, on the other hand, is a marathon, not a sprint. It takes more time to show results but is good for long-term growth and compounding value.

What Is Your Budget?

Obviously, SEM campaigns are going to cost you money. After all, there’s a reason it’s called pay-per-click.

If your budgets are tight or you have low product margins, it may not make sense to run SEM.

SEO, on the other hand, is more of a time investment than a financial one. And, you can probably enlist people already on your payroll like writers, IT personnel, and marketers to help.

How Is Your Site Currently Performing?

If your website already ranks highly for your keywords, your SEO needs will be primarily driven by changes to the Google algorithm and competition.

In this situation, SEM is a great augmentation. Conversely, if you’re not getting a lot of organic traffic, you probably need to get your SEO in order before you start spending money on paid ads.

How Much Data Do You Have Or Need About Visitors?

SEM lets you capture a lot more visitor data than organic search.

You can run your PPC campaigns through dashboards like Google Analytics, where you can see clicks, impressions, CTR, sessions, conversions, etc.

You can then use this data to track trends and attract new customers.

How Is Your Online Reputation?

SEO is a great way to control the narrative around your brand.

Using the same techniques you use to climb to the top of search rankings, you can control the way your organization is seen online.

In one famous (albeit unsuccessful) example, UC-Davis paid a consulting firm $175,000 to scrub the internet of negative postings.

Of course, if you can swing it, you should combine SEO and SEM as complementary search strategies.

This way, you can use the data you gather from your PPC campaigns to refine your SEO campaigns. This will give you a better idea of exactly what your audience is looking for when they click your links, so you can customize your content to it.

Combining both practices also lets you create remarketing campaigns.

If your SEO work is driving visitors, but you’re not seeing the conversions you want, you can use SEM to actively reach out to those targets and bring them back to your website.

Pairing SEO and SEM can also allow you to completely dominate search engine results pages (SERPs).

If you have the top ranking on the first page of results, plus paid listings on the same page, you’ve just claimed a lot of real estate.

The downside of this, however, is that your paid listings may cannibalize your organic traffic, which costs you unnecessary money.

Conclusion

Hopefully, by this point, we’ve successfully impressed on you the difference between SEO and SEM. But just in case it wasn’t clear, here it is once more for the people in the back:

SEO is using non-paid tactics to drive traffic to your website organically. It’s a slower process (usually three to six months) but can pay long-term dividends.

SEM, including PPC, is the use of paid search platforms to drive targeted traffic to your website. It requires a budget but can drive results very quickly.

Too many people either see these as the same thing or as completely separate initiatives and miss out on the benefits of using them together.

To get the best results, both should be a part of your digital marketing strategy.

They each have different strengths and weaknesses, but when properly united, can give you a real competitive advantage.

More Resources:

Featured Image: Krakenimages.com/Shutterstock

FAQ

When should a business prioritize SEM over SEO?

Businesses should prioritize SEM when they need quick results, such as promoting a sale or testing a new offer. SEM is also ideal if the business has a product with a limited-time offer or requires rapid visibility for critical events. Essentially, if the objective is immediate traffic and short-term goals, SEM, including PPC campaigns, should be considered the primary strategy, provided there is an appropriate budget in place.

How do SEO and SEM complement each other?

SEO and SEM complement each other by addressing both short-term and long-term marketing goals. SEO helps build a foundation for sustained organic traffic over time, while SEM provides immediate visibility and traffic through paid ads. Combine data from SEM campaigns to refine your SEO efforts, ensuring that content aligns with what your audience seeks. When used together, these strategies can occupy more search engine real estate, increasing both paid and organic reach.

What factors should influence the choice between SEO and SEM?

Your choice between SEO and SEM should consider several factors:

Goals: If you aim for quick visibility, opt for SEM. For long-term growth, focus on SEO.
Budget: SEM involves ongoing costs for ad placements, while SEO requires time investment, with potential internal resources.
Current website performance: If your site already ranks well organically, SEM can augment your traffic further. Conversely, if organic traffic is low, prioritize SEO.
Data needs: SEM provides detailed insights through platforms like Google Analytics, which can be advantageous for in-depth analysis and strategy adjustments.

Ultimately, assess these factors to determine the best approach for your marketing strategy.

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May 16 2024

Google AI Overviews = Theft? Court Ruling Sets Precedent via @sejournal, @MattGSouthern

Google’s bold new vision for the future of online search, powered by AI technology, is fuelling an industrywide backlash over fears it could damage the internet’s open ecosystem.

At the center of the controversy are Google’s newly launched “AI Overviews,” which are generated summaries that aim to directly answer search queries by pulling in information from across the web.

AI overviews appear prominently at the top of results pages, potentially limiting users’ need to click through to publishers’ websites.

The move sparked legal action in France, where publishers filed cases accusing Google of violating intellectual property rights by ingesting their content to train AI models without permission.

A group of French publishers won an early court battle in April 2024. A judge ordered Google to negotiate fair compensation for repurposing snippets of their content.

Publishers in the US are raising similar objections as Google’s new AI search overviews threaten to siphon traffic away from sources. They argue that Google unfairly profits from others’ content.

The debate highlights the need for updated frameworks governing the use of online data in the age of AI.

Concerns From Publishers

According to industry watchers, the implications of AI overviews could impact millions of independent creators who depend on Google Search referral traffic.

Frank Pine, executive editor at MediaNews Group, tells The Washington Post:

“If journalists did that to each other, we’d call that plagiarism.”

Pine’s company, which publishes the Denver Post and Boston Herald, is among those suing OpenAI for allegedly scraping copyrighted articles to train their language models.

Google’s revenue model has long been predicated on driving traffic to other websites and monetizing that flow through paid advertising channels.

AI overviews threaten to shift that revenue model.

Kimber Matherne, who runs a food blog, is quoted in the post article stating:

“[Google’s] goal is to make it as easy as possible for people to find the information they want. But if you cut out the people who are the lifeblood of creating that information, then that’s a disservice to the world.”

According to the Post’s report, Raptive, an ad services firm, estimates the changes could result in $2 billion in lost revenue for online creators.

They also believe some websites could lose two-thirds of their search traffic.

Raptive CEO Michael Sanchez tells The Post:

“What was already not a level playing field could tip its way to where the open internet starts to become in danger of surviving.”

Concerns From Industry Professionals

Google’s AI overviews are understandably raising concerns among industry professionals, as expressed through numerous tweets criticizing the move.

Matt Gibbs questioned how Google developed the knowledge base for its AI, bluntly stating, “They ripped it off publishers who did the actual work to create the knowledge. Google are a bunch of thieves.”

From the top of Google’s “Generative AI in Search” article today.

How did they develop that knowledge base?

They ripped it off publishers who did the actual work to create the knowledge.

Google are a bunch of thieves. pic.twitter.com/SIkPqtWZwa

— Matt Gibbs (@ematt) May 14, 2024

In her tweet, Kristine Schachinger echoed similar sentiments, referring to Google’s AI answers as “a complete digital theft engine which will prevent sites getting clicks at all.”

.@sundarpichai and @Google launch AI answers at #GoogleIO2024 otherwise known as a complete digital theft engine which will prevent sites getting clicks at all.

We need government to step in now and press to bring the sunshine.

This is ONE AI ANSWER.
Click into it. pic.twitter.com/5NNtKAURxC

— Kristine (@schachin on Threads) 🇺🇦 (@schachin) May 14, 2024

Gareth Boyd retweeted a quote from the Washington Post article highlighting the struggles of blogger Jake Boly, whose site recently saw a 96% drop in Google traffic.

Boyd said, “The precedent being set by OpenAI and Google is scary…” and that “more people should be equally angry” at both companies for the “open theft of content.”

The precedent being set by OpenAI and Google is scary… more people should be equally angry with OpenAI as well as Google for the open theft of content.

To be clear, I HATE regulation, but by the time AI is quite rightly regulated, it will be too late. https://t.co/KsbNUKopeV

— Gareth Boyd (@garethaboyd) May 15, 2024

In his tweet, Avram Piltch directly accused Google of theft, stating, “the data used to train their AI came from the very publishers that allowed Google to crawl them and are now going to be harmed. This is theft, plain and simple. And it’s a threat to the future of the web.”

You can say that Google doesn’t “owe” publishers anything, but the data used to train their AI came from the very publishers that allowed Google to crawl them and are now going to be harmed. This is theft, plain and simple. And it’s a threat to the future of the web. https://t.co/buDZgRaSuL

— Avram Piltch (@geekinchief) May 15, 2024

Lily Ray made a similar claim about Google: “Using all the content they took from the sites that made Google. With little to no attribution or traffic.”

Using all the content they took from the sites that made Google. With little to no attribution or traffic. https://t.co/0sNwk2ASmT

— Lily Ray 😏 (@lilyraynyc) May 14, 2024

Legal Gray Area

The controversy taps into broader debates around intellectual property and fair use, as AI systems are trained on unprecedented scales of data scraped across the internet.

Google argues its models only ingest publicly available web data and that publishers previously benefited from search traffic.

Publishers implicitly consent to their content being indexed by search engines unless they opt out.

However, laws weren’t conceived with training AI models in mind.

What’s The Path Forward?

This debate highlights the need for new rules around how AI uses online data.

The way forward is unclear, but the stakes are high.

Some suggest revenue sharing or licensing fees when publisher content is used to train AI models. Others propose an opt-in system that gives website owners more control over how their content is used for AI training.

The French rulings suggest that the courts may step in without explicit guidelines and good-faith negotiations.

The web has always relied on a balance between search engines and content creators. If that balance is disrupted without new safeguards, it could undermine the exchange of information that makes the internet so valuable.

Featured Image: Veroniksha/Shutterstock

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May 16 2024

As Chatbots And AI Search Engines Converge: Key Strategies For SEO

A lot is happening in the world of search right now, and for many, keeping pace with these changes can be overwhelming.

The rise of chatbots and AI assistants – like ChatGPT and its new model GPT-4o, along with Google’s rollout of AI Overviews and Search Generative Experience (SGE) – is blurring the lines between chatbots and search engines.

New AI-first entrants, such as Perplexity and You.com, also fragment the search space.

While this causes some confusion and necessitates that marketers pivot and optimize for multiple types of “engines,” it also presents a whole new array of opportunities for SEO pros to optimize for both traditional and AI-driven search engines in a new multisearch universe.

This evolution raises a broader question – perhaps for another day – about redefining what we call SEO to encompass terms like Artificial Intelligence Optimization (AIO) and Generative Engine Optimization (GEO).

Currently, every naming convention seems subject to change, which is something to consider as I write this article.

Either way, this evolution opens up tremendous opportunities for disruption in the overall search landscape.

What Is A Chatbot Or AI Assistant?

Screenshot from Wikipedia, May 2024

At the most basic level, chatbots use natural language processing (NLP) and large language models (LLMs) that are trained to extract data from online information, sources, and specific datasets. They then classify and fine-tune text and visual outputs based on a user’s prompt or question.

Chatbots are often used within specific applications or platforms, such as customer service websites, messaging apps, or ecommerce sites. They are designed to address specific queries or tasks within these defined contexts.

Right now, we see many crossovers between LLM-based chatbots and search engines. Rapid developments in these areas can cause confusion.

In this article, we’ll focus on the development of AI models in chatbots and their relation to search, with an inferred reference between chatbots and AI assistants.

The Evolution Of Chatbots And AI Models

Since ChatGPT emerged in November 2022, we’ve seen a significant boom in chatbots and AI assistants. Now, generative AI allows users to interact directly with AI and engage in human-like conversations to ask questions and complete various tasks.

For example, these AI tools can assist with SEO tasks, create content, compose emails, write essays, and even handle coding and programming tasks.

As they evolve, chatbots become multimodal (MMLLMs), improving capabilities beyond text to include images, audio, and more.

Image from 2024 AI Index Report from Stanford University, May 2024

For those interested in digging deeper into these models, the 2024 AI Index Report from Stanford University is a great resource for SEJ readers.

While many chatbots and AI models serve similar purposes, they also have distinct applications and use cases, such as content creation, image generation, and voice recognition.

Here are a few examples with some interesting differentiators and points:

ChatGPT: Conversational AI for research, ideation, text, image content, and more.
Google Gemini and Gemma: Uses Google’s LLM to connect and find sources within Google.
Microsoft Bing: Uses ChatGPT for conversational web search in Bing.
Anthropic Claude: Various AI models for content generation, images, and coding.
Stability AI: Suite of models and AI assistants for text, image, audio, and coding.
Meta Llama3: Utilizes Facebook’s social graph, its own Llama 3 model, and real-time data from Google.
Microsoft’s Copilot: AI assistant for business creativity and productivity apps.
Amazon LLM and Codewhisperer: Enhances customer and employer experiences.
Perplexity AI: Provides quick answers, sources of information, and citations.

Perplexity AI (which I will touch on later in this article) acts more like a search engine than many other chatbots and AI assistants.

Beyond their primary use cases, many companies are making their models available to a wider audience and broader ecosystems, allowing users to customize their own AI assistants.

For example, Amazon’s Bedrock enables AWS customers to use Anthropic and other LLMs, including Amazon’s own model, to create custom AI agents. Companies like Lonely Planet, Coda, and United Airlines are already using it.

On May 13, OpenAI launched its new flagship model, GPT-4. This model is a combination of AI technologies, bringing together what OpenAI calls “text, vision, and audio.” It also opens up access to its application programming interface (API), allowing developers to build their own applications.

All of this convergence has a lot of people wondering.

What’s The Difference Between Chatbots And Search Engines?

The first thing to note is that both chatbots and search engines are designed to provide information.

Search engines and some chatbot models share many similarities, which means their definitions can blur, and the relationships between them converge and collide.

However, at the moment (but it is changing), there is still a distinct difference between the two:

Search Engines

Search engines are better for exploring a wide range of topics.
They provide diverse perspectives from multiple sources.

Chatbots

Chatbots are better for quick answers, task completion, and personalized interactions.
They enhance the efficiency of the average searcher, making them much more effective at finding information.

Image from author, May 2024

As more overlays and overlaps occur, the definitions of what constitutes a chatbot, an AI assistant, and a search engine may need to be redefined.

How Chatbots And Search Engines Work Together

Conversational search is a key area where search engines increasingly integrate chatbot features to provide a more interactive search experience.

You can ask questions in natural language, and the search engine may respond with direct answers or engage in a dialogue to refine your query.

Chatbots and AI assistants often utilize search engine technology to access information from the web, enhancing their ability to provide accurate and comprehensive answers.

This integration allows chatbots to go beyond their programmed knowledge base and tap into a broader range of information.

Here are a few examples:

Google: Integrates its own chatbot features into its search engine through SGE, providing direct answers and engaging in conversational search for some queries.
Bing: Incorporates a chatbot called “Bing Chat” that uses ChatGPT, conversational AI, and search technology to answer questions and provide information.
YouChat: A search engine that provides conversational responses to queries and allows for follow-up questions.
Meta: Utilizes its social graph and Google’s real-time data in its chatbot/AI assistant.
Perplexity AI: A chatbot that functions like a search engine, focusing on informational sources, sites, and citations.

These examples illustrate how the lines between chatbots and search engines are blurring. Thousands more instances show this convergence, highlighting the evolving landscape of digital search and AI.

How “Traditional” Search Engines Are Evolving As AI-First Entrants Arrive

The rise of generative AI and chatbots has caused significant upheaval in the traditional search space.

Traditional search engines are evolving into “answer engines.” This transformation is driven by the need to provide users with direct, conversational responses rather than just a list of links.

The line between chatbot engines and AI-led search engines is becoming increasingly blurred.

While AI in search is not a new concept, the introduction of generative AI and chatbots has necessitated a seismic shift in how search engines operate. For the first time, users can interact with AI in a conversational way, prompting giants like Google and Microsoft to adapt.

On May 14 at Google IO, Google announced the roll-out of AI Overviews as it integrates AI features into its search engine. It is also making upgrades to SGE.

The ultimate goal is to enhance its ability to provide direct answers and engage in conversational search. This evolution signifies Google’s commitment to maintaining its leadership in the search space by leveraging AI to meet user expectations.

In a recent interview on Wired Magazine titled It’s the End of Google Search As We Know It, Google Head of Search, Liz Reid, was clear that:

“AI Overviews like this won’t show up for every search result, even if the feature is now becoming more prevalent.”

As my co-founder, Jim Yu, states in the same article:

“The paradigm of search for the last 20 years has been that the search engine pulls a lot of information and gives you the links. Now the search engine does all the searches for you and summarizes the results and gives you a formative opinion.”

Beyond Google, we are seeing a rise in new, AI-driven search engines like Perplexity, You.com, and Brave, which act more like traditional search engines by providing informational sources, sites, and citations.

These platforms leverage generative AI to deliver comprehensive answers and facilitate follow-up questions, challenging the dominance of established players.

Meta is also entering the fray by utilizing its social graph and real-time data from Google in its AI assistant, further contributing to the convergence of search and AI technologies.

At the same time, according to Digiday, TikTok is starting to reward what it calls “search value.”

Going forward, it’s important to remember that people have diverse needs, and we turn to different platforms for specific purposes.

Just as we go to Amazon for products, Yelp for restaurant suggestions, and YouTube for videos, the rise of AI will only amplify this trend. Each search engine will find its niche, leveraging its strengths to cater to particular user requirements.

ChatGPT is an intriguing case that stands out not for its research capabilities but for its prowess in content creation. While it excels in crafting high-quality content, its research functionalities fall short.

Effective research relies on real-time data, which platforms like ChatGPT currently lack. As we move forward, we expect to see search engines specialize even further, each excelling in specific areas based on its unique strengths and features.

What Does It All Mean For Marketers?

This fast-moving landscape and the convergence of search and AI presents both challenges and opportunities for marketers.

Optimizing for one engine is no longer sufficient; it’s essential to target multiple platforms – each with unique users, demographics, and intents.

Here’s how marketers can adapt and thrive in this dynamic environment.

Optimizing For Different Platforms

Google

Strength: Dominates the traditional search space with a vast user base and comprehensive data sources.
Tip: Focus on core technical SEO, including schema markup and mobile optimization. Google’s Search Generative Experience means direct answers are becoming more prevalent, so structured data and high-quality content are vital.

Perplexity AI

Strength: Provides detailed citations and emphasizes source material, driving referral traffic back to original sites.
Tip: Ensure your content is authoritative and well-cited. Being a reliable source will increase the likelihood of your site being referenced, which can drive traffic and enhance brand trust.

ChatGPT

Strength: Excels in conversational AI, making it suitable for quick answers and personalized interactions.
Tip: Create engaging, concise content that answers common questions directly. Utilize conversational language in your SEO strategy to match the style of ChatGPT interactions.

Key Strategies For Marketers

From optimizing technical SEO to harnessing the power of semantic understanding and creativity, these strategies provide a roadmap for success in the era of AI-driven search.

Core Technical SEO

Basics like site speed, mobile-friendliness, and proper schema markup remain crucial. Ensuring your site is technically sound helps all search engines index and rank your content effectively.

Semantic Understanding

Search engines and conversational AI are increasingly focused on semantic search. Optimize for natural language queries and long-tail keywords to match user intent more accurately.

Content And Creativity

High-quality, creative content is more important than ever. Unique, valuable content that engages users will stand out in both traditional and AI-driven search results.

Expanded Role Of SEO

SEO now encompasses content creation, branding, public relations, and AIO. Marketers who can adapt to these roles will be more successful in the evolving search landscape.

Be The Source That Gets Cited

Ensure your content is authoritative and well-researched. Being a primary source will increase the likelihood of citations that drive traffic and enhance credibility.

Get Predictive

Anticipate follow-up questions and provide comprehensive answers. This will not only improve user experience but also increase the chances of your content being highlighted in AI-driven search results.

Brand Authority

Focus on areas where your brand excels. AI search engines prioritize authoritative sources, so build and maintain your reputation in key areas to stay competitive.

The Best Content That Provides The Best Experience Wins

Ultimately, the quality of your content will determine your success. Invest in creating the best possible user experience, from engaging visuals to informative text.

Key Takeaways

Today, search encompasses a dual purpose: It can serve as a standalone assistant-based application or integrate into search engines for AI-led conversational experiences.

This fusion presents marketers with a unique opportunity to elevate their brands by creating accurate and authoritative content that positions them as trusted sources in their respective fields.

Ranking on the first page and being recognized as the go-to source cited by AI engines is no less important than 10 or 20 years ago but is exponentially more difficult.

The good news is that whether it’s Google’s AI engine or newcomers like Perplexity, brands that establish themselves as authorities in their niche stand to benefit immensely.

Marketers need to embrace creativity and collaboration across omnichannel teams. Ensure that your website is visible and accessible to all types of engines, whether traditional or AI-driven.

I’d like to leave you with a few questions to consider as you find your way forward in this complex environment. Pardon the pun, but no one has all the right answers yet.

Are chatbots morphing into search engines?
How do social platforms differentiate as younger generations look to them as search engines?
How would you define a search engine?
Who will win the race for user loyalty – traditional search engines infused with AI or new entrants built on generative AI from the beginning?
How would you redefine your role as an SEO – are you AI first?

While you consider that, stay proactive and adaptable and position yourself and your company to leverage the diversity and complexity of the search ecosystem to your advantage. In a world of ChatGPT, chatbots, and AI in search, you’re not optimizing for one channel, such as Google or Bing.

Successful optimization in this multifaceted landscape calls for a holistic approach. It’s not about keyword rankings or click-through rates; it’s about unraveling the intricacies of each platform and adjusting your strategies accordingly.

This means optimizing your content for conversational search, tapping into the capabilities of AI to tailor user experiences, and seamlessly integrating across different channels and devices.

Leverage the strengths of each platform to amplify your message by use case and engage with your audience on a deeper level, and you’ll ultimately drive more meaningful results for your business.

More resources:

Featured Image: Memory Stockphoto/Shutterstock

Ecommerce MGMT 0 Comments

May 16 2024

Building Brand Authenticity Through Community via @sejournal, @navahf

One of a brand’s greatest gifts is its ability to communicate with its prospects and customers through social communities.

These goldmines of customer sentiment and potential product or service positioning can provide every brand with a wealth of information.

However, cultivating those communities and building the authenticity to engage with your customers takes time and effort.

This post will not tell you, “Here’s exactly how to do it,” because every brand will have a different voice that it needs to leverage as well as different needs for its community.

However, we will explore a framework you can leverage for your brand so that your conversations with customers and prospects are meaningful.

Here are the main areas we will discuss in this article:

Value and tone – how to determine which ones are right for you.
Translating your message across channels and carrying your customers with you.
Owning whether engagement should be paid or organic.

A final note before we dive in: this is not going to be a criticism or praise of any one particular channel. We intend to keep this as agnostic as possible, acknowledging that some brands will be more aligned with some channels than others.

This can be related to creative bandwidth, i.e., how much time you have to post and engage with a channel. It could also be related to whether you have the means to create video. There are a number of different criteria.

Just know that whatever you decide to engage with, you do need to be consistent.

Value & Tone

A brand’s values come down to who it is at its core. Some brands lean toward transparency and sharing all of the ins and outs of how they function. This can include what it’s doing with its team and what the product/service roadmap looks like.

Others will focus far more on doing well by doing good, highlighting customer engagement in the community versus just what they are working on themselves.

There is no right or wrong answer to this. You need to make sure that you know what your brand’s beating heart is and how the message you’re sending ties back to that.

Coming up with your values is not something you should undertake lightly. Additionally, your team needs to agree on and comply with them.

If giving in the community is a core value, your team members shouldn’t be caught posting things that make light of others’ suffering.

Conversely, if part of your values relate to certain tech advancements, calling out those tech advancements in a negative light could be counterproductive.

This doesn’t mean that you can’t change your opinion and have reasons why your opinion shifts, but consistent communication is needed to reinforce the new value position.

Image from Semrush, April 2024

One example is Semrush. Semrush used to have a different brand aesthetic, and there were questions about how to pronounce its brand name.

The company settled the debate once and for all with a very clear-cut statement. In doing so, it actually ruffled a few feathers because the community didn’t like being told they were wrong.

On the other hand, Semrush ensured that its branding would be consistent moving forward. This was particularly useful as it prepared for its IPO.

Screenshot from Twitter, April 2024

Burger King ran an ill-fated X (Twitter) campaign saying women belong in the kitchen.

Now, most of us would know it’s common sense that this could only have ended badly. However, the campaign intended to highlight the shortage of female chefs leading kitchen brigades and earning top dollar compared to their male counterparts.

The brand redeemed itself somewhat instead of representing a true failure because it acknowledged the mistake and then provided detailed information about what it had been trying to do.

So, while Burger King did fall down publicly as a brand, it paved the way for more attention to be shown to the cause.

Thank you to Purna Virji for highlighting this one and lots of other great examples in her book, “High Impact Marketing.” You can read chapter one of her book here.

Both of these cases provide a useful framework to consider how you want your values and tone to come across to your customers:

Are you comfortable poking fun at your customers and yourselves, or do you feel the need to be serious?
How quickly can you respond to customer sentiment shifts, and how much can you let that influence your risk tolerance and risk aversion?
How much should you be tied to public events versus how often should you create events based on industry, product, or service innovations?

The answers to all of these questions will help you build a framework that you can then take to each channel.

You are prepared to build a community, but these communities will need moderation, so you should only engage in a channel that you are prepared for.

Staff will go through each major channel in a moment, but it is important to know that no matter how many you choose, successes tend to go unnoticed. Failures tend to be remembered indefinitely, and the greatest failure is not owning your brand.

So, even if you aren’t prepared to engage with a channel, you should still at least claim your profile.

Translating Messages Across Channels

When people talk about social media, they are typically referring to Facebook, Instagram, Reddit, TikTok, LinkedIn, X (Twitter), Snapchat, Pinterest, and Quora.

However, how you actually engage with each of these channels or any additional ones that pop up, including login-based communities like Discord, Slack, and Tumblr, will all depend on how well-equipped your team is to engage with the pace of each channel.

We’re going to break down each channel based on its pace, general tone, and creative flexibility.

When engaging with these communities, it’s important to note that you should claim your profile across all channels but only be active where you intend to be consistent and know your customers and prospects are or could be enticed to engage.

Facebook

Tone: Generally casual and personal, but can vary depending on the content shared.
Pace: Moderate pace, with a mix of real-time updates and more evergreen content. Brands typically post 1-2 times per day to maintain visibility in the algorithm.
Creative Flexibility: Offers various content formats like text posts, images, videos, live streams, and Stories. Moderation includes adherence to community standards, which restricts certain types of content.
Community Management Tools: Provides features like Groups, Pages, and messaging for community management. Also offers insights and analytics for Page owners.

Instagram

Tone: Visual and aesthetic-focused, often aspirational or inspirational.
Pace: Fast-paced, with a focus on real-time updates and Stories. Brands typically post at least once per day to maintain visibility.
Creative Flexibility: This category primarily includes visual content (photos and videos), with features like filters, stickers, and editing tools for creative expression. Moderation includes content guidelines and community standards enforcement.
Community Management Tools: Offers business profiles, analytics, and messaging for community management. Also, features like hashtags and tagging help in content discovery.

Tone: While mostly professional and formal, geared towards career development and networking, there is an appetite for B2B humor/memes.
Pace: The pace is generally slower, with more thoughtful and curated content. Brands typically post 2-5 times per week to maintain visibility. However, individuals post daily to maintain their presence in the feed.
Creative Flexibility: Primarily text-based posts, articles, and professional updates, with multimedia options. Moderation includes professional standards and restrictions on promotional content.
Community Management Tools: Provides tools for personal and business profiles, including messaging, groups, and analytics. Also offers job postings and networking features.

TikTok:

Tone: Fun, entertaining, and often light-hearted or humorous.
Pace: Very fast-paced, with short-form videos designed for quick consumption. Brands typically post multiple times per day to maintain visibility.
Creative Flexibility: This is highly flexible, with a focus on short videos augmented with effects, filters, and music. Moderation includes enforcing community guidelines and restricting certain content types.
Community Management Tools: Offers features like Duets, reactions, comments, and hashtags for engagement. Also provides analytics for creators.

X (Twitter)

Tone: Conversational, often informal, and concise due to character limit.
Pace: Fast-paced, with real-time updates and trending topics. Brands typically post multiple times per day to maintain visibility.
Creative Flexibility: Limited by character count but supports text, images, videos, and GIFs. Moderation includes adherence to Twitter rules and restrictions on sensitive content.
Community Management Tools: Features like retweets, replies, hashtags, and lists facilitate engagement and community building. Analytics and Twitter chats are also useful for community management.

Tone: Diverse, depending on the subreddit, but generally informal and community-driven.
Pace: This can vary, but it is often a mix of real-time discussions and slower-paced threads. Brands typically engage regularly but avoid spamming to maintain credibility.
Creative Flexibility: Supports various content types including text, images, links, and videos. Moderation includes subreddit-specific rules, enforced by moderators.
Community Management Tools: Moderation tools like banning, removing posts, and community guidelines enforcement. Subreddit creation and management, along with voting and commenting systems, are essential for community engagement.

Quora

Tone: Informative and knowledge-focused, with an emphasis on sharing expertise.
Pace: Generally slower-paced, with longer-form questions and answers. Brands typically engage by answering relevant questions and participating in discussions.
Creative Flexibility: Primarily text-based, with options for including images and links. Image size: Varies based on Quora’s formatting. Moderation includes adherence to Quora’s policies and guidelines.
Community Management Tools: Moderation tools for questions, answers, and comments. Features like following topics, upvoting, and following users facilitate community interaction.

Discord

Tone: Varied depending on the server, but often casual and conversational.
Pace: Can range from slow-paced discussions to real-time chats and events. Brands typically maintain active presence but avoid overwhelming channels.
Creative Flexibility: Supports text, voice, and video communication, along with customizable server settings and bots for additional functionality. Moderation includes server-specific rules enforced by administrators.
Community Management Tools: Extensive moderation tools for roles, channels, permissions, and content moderation. Features like voice channels, emojis, and reaction roles enhance community engagement.

Slack

Tone: Professional and work-focused, though it can be casual within specific channels or teams.
Pace: Typically moderate-paced, with real-time communication within teams. Brands typically engage regularly but avoid excessive messaging to maintain productivity.
Creative Flexibility: Primarily text-based, with options for file sharing, integrations, and custom emoji. Moderation includes adherence to team guidelines and restrictions on off-topic discussions.
Community Management Tools: Offers channel management, user roles, message deletion, and integrations with various apps and services for productivity and collaboration.

With each channel’s baseline explored, we can now talk about translating messages across each.

As a general rule of thumb, text-based creative will translate fairly well across each, provided that you count for the character and or word count. Where it gets a little bit tougher is when you begin layering in visual content.

This is tough on two counts.

First, there’s pressure to create visual content because visual content tends to do better on social channels. However, there’s also a difference in tone and formatting between the visual channels. For example, you can’t always just recut a video you made for LinkedIn to be a TikTok video.

While length is a factor, so are tone and subject matter expertise. While the ideas might be the same, you may need to repackage them for each channel.

Additionally, from a community standpoint, there are different algorithmic rules that go into each platform. So, if you have a community that’s a little bit looser on language/sensitive topics, you may struggle to translate that community to channels with stricter guidelines.

An excellent example of this is that Facebook Groups tend to have stringent community rules based on bots identifying and removing posts.

Conversely, on platforms like Slack or Discord (i.e., private servers with a login), what’s allowed is up to the server controller’s discretion. So, if you know that your community will need that flexibility, you may decide to go for the password-gated community versus a more open group, such as LinkedIn or Facebook.

Different communities have different algorithms for how content reaches users, so if you care that the content reaches your people specifically, you may need to tell them to check the group regularly.

You may also need to tell them to identify that your Group or your Page is of special interest to them so that they receive all updates from you as opposed to only getting it filtered through their feed. For example, when someone posts on LinkedIn, they can tell the system whether they want to see more or less from a particular person or group. This is true on Facebook as well.

If people consistently say that they don’t want to hear from your Group, even if you have engaged members, you may struggle to have your content reach them organically without them coming to your community page.

Paid Versus Organic

When it comes to being real with your audience, you’ve got to think about how you talk to them – whether you’re paying for it or not. The key to being genuine lies in how you interact with the folks who support your brand.

No matter how you promote yourself, it’s no accident that paid ads and sponsored content often let people leave comments and reactions. If you see lots of people engaging with a paid post, that’s a sign you should also share some regular stuff. And if you respond to comments, you can reach even more people than you paid for – but there’s a catch.

Paying to show up where people haven’t asked for you can sometimes annoy them instead of making them like you more.

For instance, imagine a brand keeps running ads on YouTube about something new, but it doesn’t limit how often you see them. Then, the brand brings up the same thing in its online groups. Instead of getting a positive response, it might end up getting yelled at for being annoying because people are already tired of hearing about it.

The trick is listening to what your customers say while explaining how things work. For example, if you want to prevent your current customers from seeing your ads, you have to meet certain audience size requirements (1,000 for search-first platforms and 100 for social-first platforms).

If you can’t, it’s important to let them know it’s not intentional – it’s just how the system works.

Now, about being genuine: Some say paid ads aren’t as real as regular posts. But the truth is that many social platforms make a lot of money from boosting regular posts, so there’s no shame in doing the same to reach more people.

The key is to know which posts are worth boosting and why. If a post looks okay on its own but doesn’t quite fit your brand’s style for ads, maybe hold off.

And if a post is already doing great without any help, putting a “sponsored” tag on it might make people trust it less. So, thinking about how your audience feels about ads is essential.

Finding the right balance between paid and regular content means keeping it real with your audience and respecting their preferences. It’s all about building trust and making sure your brand stays true to itself.

Final Takeaways

Building authenticity is all about consistency and being useful to your people in the way that they want to be helped using a channel. Just because your competitors are is meaningless.

If your customers aren’t there and if you’re not able to engage with them in a way that lets you help them, the best way to confirm whether to be on a channel or not and whether to foster a community there or not is all down to how much can you be you while engaging with your customers?

More resources:

Featured Image: FabrikaSimf/Shutterstock

Ecommerce MGMT 0 Comments

May 15 2024

New Google AI Overviews Documentation & SEO via @sejournal, @martinibuster

Google published new documentation about their new AI Overviews search feature which summarizes an answer to a search query and links to webpages where more information can be found. The new documentation offers important information about how the new feature works and what publishers and SEOs should consider.

What Triggers AI Overviews

AI Overviews shows when the user intent is to quickly understand information, especially when that information need is tied to a task.

“AI Overviews appear in Google Search results when our systems determine …when you want to quickly understand information from a range of sources, including information from across the web and Google’s Knowledge Graph.”

In another part of the documentation it ties the trigger to task-based information needs:

“…and use the information they find to advance their tasks.” “

What Kinds Of Sites Does AI Overviews Link To?

An important fact to consider is that just because AI Overviews is triggered by a user’s need to quickly understand something doesn’t mean that only queries with an informational need will trigger the new search feature. Google’s documentation makes it clear that the kinds of websites that will benefit from AI Overviews links includes “creators” (which implies video creators), ecommerce stores and other businesses. This means that far more than informational websites that will benefit from AI overviews.

The new documentation lists the kinds of sites that can receive a link from the AI overviews:

“This allows people to dig deeper and discover a diverse range of content from publishers, creators, retailers, businesses, and more, and use the information they find to advance their tasks.”

Where AI Overviews Sources Information

AI Overviews shows information from the web and the knowledge graph. Large Language Models currently need to be entirely retrained from the ground up when adding significant amounts of new data. That means that the websites chosen to be displayed in Overviews feature are selected from Google’s standard search index which in turn means that Google may be using Retrieval-augmented generation (RAG).

RAG is a system that sits between a large language model and a database of information that’s external to the LLM. This external database can be a specific knowledge like the entire content of an organization’s HR policies to a search index. It’s a supplemental source of information that can be used to double-check the information provided by an LLM or to show where to read more about the question being answered.

The section quoted at the beginning of the article notes that AI Overviews cites sources from the web and the Knowledge Graph:

“AI Overviews appear in Google Search results when our systems determine …when you want to quickly understand information from a range of sources, including information from across the web and Google’s Knowledge Graph.”

What Automatic Inclusion Means For SEO

Inclusion in AI Overviews is automatic and there’s nothing specific to AI Overviews that publishers or SEOs need to do. Google’s documentation says that following their guidelines for ranking in the regular search is all you have to do for ranking in AI Overviews. Google’s “systems” determine what sites are picked to show up for the topics surfaced in AI Overviews.

All the statements seem to confirm that the new Overviews feature sources data from the regular Search Index. It’s possible that Google filters the search index specially for AI Overviews but offhand I can’t think of any reason Google would do that.

All the statements that indicate automatic inclusions point to the likely possibility that Google uses the regular search index:

“No action is needed for publishers to benefit from AI Overviews.”

“AI Overviews show links to resources that support the information in the snapshot, and explore the topic further.”

“…diverse range of content from publishers, creators, retailers, businesses, and more…”

“To rank in AI Overviews, publishers only need to follow the Google Search Essentials guide.

“Google’s systems automatically determine which links appear. There is nothing special for creators to do to be considered other than to follow our regular guidance for appearing in search, as covered in Google Search Essentials.”

Think In Terms Of Topics

Obviously, keywords and synonyms in queries and documents play a role. But in my opinion they play and oversized role in SEO. There are many ways that a search engine can annotate a document in order to match a webpage to a topic, like what Googler Martin Splitt referred to as a centerpiece annotation. A centerpiece annotation is used by Google to label a webpage with what that webpage is about.

Semantic Annotation

This kind of annotation links webpage content to concepts which in turn gives structure to a unstructured document. Every webpage is unstructured data so search engines have to make sense of that. Semantic Annotation is one way to do that.

Google has been matching webpages to concepts since at least 2015. A Google webpage about their cloud products talks about how they integrated neural matching into their Search Engine for the purpose of annotating webpage content with their inherent topics.

This is what Google says about how it matches webpages to concepts:

“Google Search started incorporating semantic search in 2015, with the introduction of noteworthy AI search innovations like deep learning ranking system RankBrain. This innovation was quickly followed with neural matching to improve the accuracy of document retrieval in Search. Neural matching allows a retrieval engine to learn the relationships between a query’s intentions and highly relevant documents, allowing Search to recognize the context of a query instead of the simple similarity search.

Neural matching helps us understand fuzzier representations of concepts in queries and pages, and match them to one another. It looks at an entire query or page rather than just keywords, developing a better understanding of the underlying concepts represented in them.”

Google’s been doing this, matching webpages to concepts, for almost ten years. Google’s documentation about AI Overviews also mentions that showing links to webpages based on topics is a part of determining what sites are ranked in AI Overviews.

Here’s how Google explains it:

“AI Overviews show links to resources that support the information in the snapshot, and explore the topic further.

…AI Overviews offer a preview of a topic or query based on a variety of sources, including web sources.”

Google’s focus on topics has been a thing for a long time and it’s well past time SEOs lessened their grip on keyword targeting and start to also give Topic Targeting a chance to enrich their ability to surface content in Google Search, including in AI Overviews.

Google says that the same optimizations described in their Search Essentials documentation for ranking in Google Search are the same optimizations to apply to rank in Google Overview.

This is exactly what the new documentation says:

“There is nothing special for creators to do to be considered other than to follow our regular guidance for appearing in search, as covered in Google Search Essentials.”

Read Google’s New SEO Related Documentation On AI Overviews

AI Overviews and your website

Featured Image by Shutterstock/Piotr Swat

Ecommerce MGMT 0 Comments

May 15 2024

Competing Against Brands & Nouns Of The Same Name via @sejournal, @TaylorDanRW

Establishing and building a brand has always been both a challenge and an investment, even before the days of the internet.

One thing the internet has done, however, is make the world a lot smaller, and the frequency of brand (or noun) conflicts has greatly increased.

In the past year, I’ve been emailed and asked questions about these conflicts at conferences more than I have in my entire SEO career.

When you share your brand name with another brand, town, or city, Google has to decide and determine the dominant user interpretation of the query – or at least, if there are multiple common interpretations, the most common interpretations.

Noun and brand conflicts typically happen when:

A rebrand’s research focuses on other business names and doesn’t take into consideration general user search.
When a brand chooses a word in one language, but it has a use in another.
A name is chosen that is also a noun (e.g. the name of a town or city).

Some examples include Finlandia, which is both a brand of cheese and vodka; Graco, which is both a brand of commercial products and a brand of baby products; and Kong, which is both the name of a pet toy manufacturer and a tech company.

User Interpretations

From conversations I’ve had with marketers and SEO pros working for various brands with this issue, the underlying theme (and potential cause) comes down to how Google handles interpretation of what users are looking for.

When a user enters a query, Google processes the query to identify known entities that are contained.

It does this to improve the relevance of search results being returned (as outlined in its 2015 Patent #9,009,192). From this, Google also works to return related, relevant results and search engine results page (SERP) elements.

For example, when you search for a specific film or TV series, Google may return a SERP feature containing relevant actors or news (if deemed relevant) about the media.

This then leads to interpretation.

When Google receives a query, the search results need to often cater for multiple common interpretations and intents. This is no different when someone searches for a recognized branded entity like Nike.

When I search for Nike, I get a search results page that is a combination of branded web assets such as the Nike website and social media profiles, the Map Pack showing local stores, PLAs, the Nike Knowledge Panel, and third-party online retailers.

This variation is to cater for the multiple interpretations and intents that a user just searching for “Nike” may have.

Brand Entity Disambiguation

Now, if we look at brands that share a name such as Kong, when Google checks for entities and references against the Knowledge Graph (and knowledge base sources), it gets two closer matches: Kong Company and Kong, Inc.

The search results page is also littered with product listing ads (PLAs) and ecommerce results for pet toys, but the second blue link organic result is Kong, Inc.

Also on page one, we can find references to a restaurant with the same name (UK-based search), and in the image carousel, Google is introducing the (King) Kong film franchise.

It is clear that Google sees the dominant interpretation of this query to be the pet toy company, but has diversified the SERP further to cater for secondary and tertiary meanings.

In 2015, Google was granted a patent that included features of how Google might determine differences in entities of the same name.

This includes the possible use of annotations within the Knowledge Base – such as the addition of a word or descriptor – to help disambiguate entities with the same name. For example, the entries for Dan Taylor could be:

Dan Taylor (marketer).
Dan Taylor (journalist).
Dan Taylor (olympian).

How it determines what is the “dominant” interpretation of the query, and then how to order search results and the types of results, from experience, comes down to:

Which results users are clicking on when they perform the query (SERP interaction).
How established the entity is within the user’s market/region.
How closely the entity is related to previous queries the user has searched (personalization).

I’ve also observed that there is a correlation between extended brand searches and how they affect exact match branded search.

It’s also worth highlighting that this can be dynamic. Should a brand start receiving a high volume of mentions from multiple news publishers, Google will take this into account and amend the search results to better meet users’ needs and potential query interpretations at that moment in time.

SEO For Brand Disambiguation

Building a brand is not a task solely on the shoulders of SEO professionals. It requires buy-in from the wider business and ensuring the brand and brand messaging are both defined and aligned.

SEO can, however, influence this effort through the full spectrum of SEO: technical, content, and digital PR.

Google understands entities on the concept of relatedness, and this is determined by the co-occurrence of entities and then how Google classifies and discriminates between those entities.

We can influence this through technical SEO through granular Schema markup and by making sure the brand name is consistent across all web properties and references.

This ties into how we then write about the brand in our content and the co-occurrence of the brand name with other entity types.

To reinforce this and build brand awareness, this should be coupled with digital PR efforts with the objective of brand placement and corroborating topical relevance.

A Note On Search Generative Experience

As it looks likely that Search Generative Experience is going to be the future of search, or at least components of it, it’s worth noting that in tests we’ve done, Google can, at times, have issues when generative AI snapshots for brands, when there are multiple brands with the same name.

To check your brand’s exposure, I recommend asking Google and generating an SGE snapshot for your brand + reviews.

If Google isn’t 100% sure which brand you mean, it will start to include reviews and comments on companies of the same (or very similar) name.

It does disclose that they are different companies in the snapshot, but if your user is skim-reading and only looking at the summaries, this could be an accidental negative brand touchpoint.

More resources:

Featured Image: VectorMine/Shutterstock

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May 14 2024

Google Rolls Out New ‘Web’ Filter For Search Results via @sejournal, @MattGSouthern

Google is introducing a filter that allows you to view only text-based webpages in search results.

The “Web” filter, rolling out globally over the next two days, addresses demand from searchers who prefer a stripped-down, simplified view of search results.

Danny Sullivan, Google’s Search Liaison, states in an announcement:

“We’ve added this after hearing from some that there are times when they’d prefer to just see links to web pages in their search results, such as if they’re looking for longer-form text documents, using a device with limited internet access, or those who just prefer text-based results shown separately from search features.”

We’ve added this after hearing from some that there are times when they’d prefer to just see links to web pages in their search results, such as if they’re looking for longer-form text documents, using a device with limited internet access, or those who just prefer text-based…

— Google SearchLiaison (@searchliaison) May 14, 2024

The new functionality is a throwback to when search results were more straightforward. Now, they often combine rich media like images, videos, and shopping ads alongside the traditional list of web links.

How It Works

On mobile devices, the “Web” filter will be displayed alongside other filter options like “Images” and “News.”

Screenshot from: twitter.com/GoogleSearchLiaison, May 2024.

If Google’s systems don’t automatically surface it based on the search query, desktop users may need to select “More” to access it.

Screenshot from: twitter.com/GoogleSearchLiaison, May 2024.

More About Google Search Filters

Google’s search filters allow you to narrow results by type. The options displayed are dynamically generated based on your search query and what Google’s systems determine could be most relevant.

The “All Filters” option provides access to filters that are not shown automatically.

Alongside filters, Google also displays “Topics” – suggested related terms that can further refine or expand a user’s original query into new areas of exploration.

For more about Google’s search filters, see its official help page.

Featured Image: egaranugrah/Shutterstock

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May 14 2024

SGE Is Here. Google Rolls Out AI-Powered Overviews To US Search Results via @sejournal, @MattGSouthern

At its annual I/O developer conference, Google unveiled plans to incorporate generative AI directly into Google Search.

Additionally, Google announced an expansion to Search Generative Experience (SGE), designed to reinvent how people discover and consume information.

Upcoming upgrades include:

Adjustable overviews to simplify language or provide more detail
Multi-step reasoning to handle complex queries with nuances
Built-in planning capabilities for tasks like meal prep and vacations
AI-organized search result pages to explore ideas and inspiration
Visual search querying through uploaded videos and images

Liz Reid, Head of Google Search, states in an announcement:

“Now, with generative AI, Search can do more than you ever imagined. So you can ask whatever’s on your mind or whatever you need to get done — from researching to planning to brainstorming — and Google will take care of the legwork.”

What’s New In Google Search & SGE

New Gemini Model

A customized Gemini language model is central to Google’s AI-powered Search revamp.

Google’s announcement states:

“This is all made possible by a new Gemini model customized for Google Search. It brings together Gemini’s advanced capabilities — including multi-step reasoning, planning and multimodality — with our best-in-class Search systems.”

AI overviews generate quick answers to their queries, piecing together information from multiple sources.

Google reports that people have already used AI Overviews billions of times through Search Labs.

AI Overviews In US Search Results

Google is bringing AI overviews from Search Labs into its general search results pages.

That means hundreds of millions of US searchers will gain access to AI overviews this week and over 1 billion by year’s end.

Image Credit: blog.google/products/search/generative-ai-google-search-may-2024/, May 2024.

Searchers will soon be able to adjust the language and level of detail in AI overviews to suit their needs and understanding of the topic.

Image Credit: blog.google/products/search/generative-ai-google-search-may-2024/, May 2024.

Complex Questions & Planning Capabilities

SGE’s multi-step reasoning capabilities will allow you to ask complex questions and receive detailed answers.

For example, you could ask, “Find the best yoga or pilates studios in Boston and show details on their intro offers and walking time from Beacon Hill,” and receive a comprehensive response.

Image Credit: blog.google/products/search/generative-ai-google-search-may-2024/, May 2024.

In addition to answering complex queries, SGE will offer planning assistance for various aspects of life, such as meal planning and vacations.

You can request a customized meal plan by searching for something like “create a 3-day meal plan for a group that’s easy to prepare.” You will receive a tailored plan with recipes from across the web.

AI-Organized Results & Visual Search

Google is introducing AI-organized results pages that categorize helpful results under unique, AI-generated headlines, presenting diverse perspectives and content types.

This feature will initially be available for dining and recipes, with plans to expand to movies, music, books, hotels, shopping, and more.

SGE will also enable users to ask questions using video content. This visual search capability can save you time describing issues or typing queries, as you can record a video instead.

Image Credit: blog.google/products/search/generative-ai-google-search-may-2024/, May 2024.

What Does This Mean For Businesses?

While Google touts SGE as a way to enhance search quality, the prominence of AI-generated content could impact businesses and publishers who rely on Google Search traffic.

AI overviews occupy extensive screen real estate and could bury traditional “blue link” web results, significantly limiting clickthrough rates.

Data from ZipTie and Search Engine Journal contributor Bart Goralewicz indicate that SGE displays cover over 80% of search queries across most verticals.

Additionally, under SGE’s unique ranking system, only 47% of the top 10 traditional web results appear as sources powering AI overview generation.

Bart Goralewicz, Founder of Onely, states:

“SGE operates on a completely different level compared to traditional search. If you aim to be featured in Google SGE, you’ll need to develop a distinct strategy tailored to this new environment. It’s a whole new game.”

Tomasz Rudzki of ZipTie cautions:

“Google SGE is the most controversial and anxiety-provoking change in search,” commented. With so much changing week by week, businesses relying on organic search must carefully monitor SGE’s evolution.”

How To Optimize Your Site for SGE

As AI search accelerates, SEO professionals and content creators face new challenges in optimizing for discoverability.

Consider implementing these tactics for a potential increase in visibility in search results.

Structure content explicitly as questions and direct answers.
With AI overviews answering queries directly, optimizing content in a question-and-answer format may increase the likelihood of having it surfaced by Google’s AI models.

Create topic overview pages spanning initial research to final decisions.
Google’s AI search can handle complex, multi-step queries. Creating comprehensive overview content that covers the entire journey—from initial research to final purchasing decisions—could position those pages as prime sources for Google’s AI.

Pursue featured status on high-authority Q&A and information sites.
Studies found sites like Quora and Reddit are frequently cited in Google’s AI overviews. Having authoritative, industry-expert-level content featured prominently on these high-profile Q&A platforms could increase visibility within AI search results.

Maximize technical SEO for improved crawling of on-page content.
Like traditional search-leveraged web crawlers, Google’s AI models still rely on crawling a site’s content. Ensuring optimal technical SEO for crawlers to access and adequately render all on-page content is crucial for it to surface in AI overviews.

Tracking search volume for queries exhibiting AI overviews.
Identifying queries that currently trigger AI overviews can reveal content gaps and optimization opportunities. Tracking search volume for these queries enables prioritizing efforts around high-value terms and topics Google already enhances with AI results.

Looking Ahead

As Google moves forward with its AI-centric search vision, disruptions could reshape digital economies and information ecosystems.

Companies must acclimate their strategies for an AI-powered search landscape.

We will be following these developments closely at Search Engine Journal with an aim to provide strategies to help make your content discoverable in SGE.

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May 14 2024

David Vs. Goliath: Does Google Give Big Sites An Unfair SEO Advantage? via @sejournal, @Kevin_Indig

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The voices criticizing Google for killing small sites are shouting louder.

Cases like HouseFresh or Retro Dodo garnered a lot of attention and made compelling cases. Hardcore updates and the growing rift between SEOs, publishers, and Google add kerosene to the fire.

The most volatile market in the world is not Brazil, Russia, or China. It’s Google search. No platform has as many changes of requirements. Over the last 3 years, Google launched 8 Core, 19 major and 75-150 minor updates. The company mentions thousands of improvements every year.

The common argumentation is that Google is breaking apart under the weight of the web’s commercialization. Or Google is cutting off middlemen like affiliates and publishers and sending traffic directly to software vendors and ecommerce brands.

But does the data support those claims?

As the saying goes, “In God we trust, all others must bring data.”

An illustration of two warriors in combat.

Image Credit: Lyna ™

Does Google Give Big Sites An Unfair SEO Advantage?

I thoroughly analyzed sites that lost and gained the most SEO traffic over the last 12 months to answer the question of whether big sites get an unfair SEO advantage.

TL;DR: Google does indeed seem to grow large sites faster, but likely due to secondary factors instead of the amount of traffic they get.

Method

I pulled the top 1,000 sites that gained and lost the most visibility over the last 12 months, each from Sistrix. I picked relative change over absolute to normalize for size of the site. For the list of winner sites, I set a minimum SEO visibility of one to filter out spam and noise.
Then, I cross-referenced the sites with backlinks and traffic data from Ahrefs to run correlations against factors like site traffic or backlinks.

Results

Sites in higher visibility percentiles have a strong relationship with SEO visibility growth over the last 12 months.

Sites that lost visibility have no relationship between the size of their loss and SEO visibility. We can, therefore, say bigger sites are more likely to be successful in SEO.

Bar chart showing SEO Advantage and Average Change percentiles over the last 12 months.

Sites in higher percentiles (= more SEO visibility) see stronger growth (Image Credit: Kevin Indig)

However, let’s not forget one thing: Newcomer sites can still get big. It’s harder than it was five or ten years ago, but it’s possible.

There are two reasons why big sites tend to gain more organic traffic.

One reason is how Google weighs ranking signals. Bigger sites tend to have more authority, which allows them to rank for more terms and grow their visibility if they’re able to avoid scale issues, keep content quality high, and continue to satisfy users by solving their problems.

Authority, based on our understanding, is the result of backlinks, content quality, and brand strength.

Google seems to be aware and taking action.

The correlation between SEO visibility and the number of linking domains is strong but was higher in May 2023 (.81) than in May 2024 (0.62). Sites that lost organic traffic showed lower correlations (0.39 in May 2023 and 0.41 in May 2024).

Even though sites that gained organic visibility have more backlinks, the signal seems to have come down significantly over the last 12 months. Backlink volume is still important, but its impact is shrinking. Mind you, volume and quality are two different pairs of sneakers.

The second reason big sites are gaining more organic traffic is Google’s Hidden Gem update, which gives preferential treatment to online communities. The impact is quite visible in the data.

High at the top of the winner list, you find online communities like:

Reddit.
Quora.
Steam Community.
Stack Exchange.
Ask Ubuntu.

Anecdotally, I noticed strong growth in popular SaaS vendor communities like HubSpot, Shopify, and Zapier. Surely, there are online communities that don’t have the same visibility as the big ones, but still grew significantly over the last 12 months.

The list of losers concentrates on publishers and ecommerce. A surprising number of big publishers lost organic traffic from classic blue links, equal to smaller publishers.

Examples of big publishers:

nypost.com (-62.3%).
bbc.com (-58.6%).
nytimes.com (-40.3%).
cnn.com (-40.1%).
theguardian.co.uk (-32.8%).

Examples of small publishers:

makeuseof.com (-79%).
everydayhealth.com (-70.6%).
thespruce.com (-58.5%).
goodhousekeeping.com (-46.5%).
verywellfamily.com (-38.4%).

Keep in mind that publishers rely a lot more on traffic from Top Stories, Google News, and Google Discover, which are not reflected in the data.

Popular Parasite SEO targets like chron.com or timesofindia.com lost significant SEO traffic, as did sites that are not on the list, like medium.com or linkedin.com/pulse. How much effort Google puts into cleaning the search engine results pages (SERPs) is unclear.

Two-thirds of sites on the list of winners were either SaaS companies, ecommerce companies, education companies, or online communities, with gains between 63% and 83%.

Over 50% of sites on the loser list were publishers or ecommerce sites, with losses between -45% and -53% SEO visibility.

It’s a lot harder to succeed in ecommerce and publisher SEO as almost twice as many ecommerce and five times as many publishers lost SEO visibility than gained.

Bar chart illustrating the number of big sites by vertical that gained or lost SEO visibility.

Image Credit: Kevin Indig

The top 5 loser sites with the highest SEO visibility in May 2023 are:

target.com (-35.5%).
wiktionary.org (-61.5%).
etsy.com (-43.6%).
nytimes.com (-40.3%).
thesaurus.com (-59.7%).

I found no discernible pattern for country code top-level domains (ccTLDs): 75% of sites on the winner list had .com ccTLDs. Only 65 were .edu, 39 were .gov, and 94 were .org.

Limitations

Of course, the biggest limitation of the analysis is that sites could have gained or lost traffic due to SEO campaigns, technical issues, or domain migrations.
The second limitation is the small sample set of 2,000 sites. Even though the analysis looks at the peak of the iceberg, the web might hold millions of sites.

Open Questions

There is a lot of room for interpretation when we talk about the word “big” in big sites. Are we talking about a certain amount of traffic, being owned by a big company, or making a lot of money when calling a big site big?

I focused on organic traffic in this analysis, but it would be interesting to see how some of the biggest companies fare in SEO. One reference point could be Glen Allsopp’s analysis of the big publishing houses dominating the SERPs.

Another question is when Google rewards big sites. During algorithm updates? Continuously over time? An answer would help us understand better how Google works.

I’ll leave you with this: In my interpretation of the data, what made big sites successful is often what keeps their growth going. When a site figures out the right quality for content or a good user experience, it’s more likely to grow continuously than sites that have plateaued or declined in traffic.

Personally, I doubt that people at Google deliberately decide to “go after a niche” or “kill small sites,” but rather that algorithmic decisions lead to those outcomes.

That is not to say Google doesn’t carry a certain responsibility.

Featured Image: Paulo Bobita/Search Engine Journal

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