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Why Prediction Of 25% Search Volume Drop Due to Chatbots Fails Scrutiny

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Why Prediction Of 25% Search Volume Drop Due to Chatbots Fails Scrutiny

Gartner’s predictions that AI Chatbots are the future and will account for a 25% drop in search market share got a lot of attention. What didn’t get attention is the fact that the claim fails to account for seven facts that call into question the accuracy of the prediction and demonstrates that it simply does not hold up to scrutiny.

1. AI Search Engines Don’t Actually Exist

The problem with AI technology is that it’s currently impossible to use AI infrastructure to create a constantly updated search index of web content in addition to billions of pages of news and social media that is constantly generated in real-time. Attempts to create a real-time AI search index fail because the nature of the technology requires retraining the entire language model to update it with new information. That’s why language models like GPT-4 don’t have access to current information.

So-called AI search engines aren’t really AI search engines. In practice, they’re chatbots that are inserted between the searcher and a traditional search engine.  When a user asks a question, a traditional search engine finds the answers and the AI chatbot chooses the best answer and summarizes them in a natural language response.

So, when you use a chatbot AI search engine what’s essentially happening is that you’re asking a chatbot to Google/Bing it for you. This is true for Bing Copilot, Google SGE and Perplexity. It’s an interesting way to search but it’s not an actual AI-based search engine, there’s still a traditional search engine behind the chatbot.

The time to panic is when the transformer technology goes through a significant change so that it can handle a real-time updated search index (or another technology replaces it). But that time is not here yet, which makes the prediction of a 25% drop in search demand by 2026 appear a bit premature.

2. Generative AI Is Not Ready For Widescale Use

The recent fiasco with Gemini’s image search underscores the fact that generative AI as a technology is still in its infancy. Microsoft Copilot completely went off the rails in March 2024 by assuming a godlike persona, calling itself “SupremacyAGI,” and demanding to be worshipped under the threat of imprisoning users of the service.

This is the technology that Gartner predicts will take away 25% of market share? Really?

Generative AI is unsafe and despite attempts to add guardrails the technology still manages to jump off the cliffs with harmful responses. The technology is literally in its infancy. To assert that it will be ready for widescale use in two years is excessively optimistic about the progress of the technology

3. True AI Search Engines Are Not Economically Viable

AI Search Engines are exponentially more expensive than traditional search engines. It currently costs $20/month to subscribe to a Generative AI chatbot and that comes with limits of 40 queries every 3 hours and the reason for that is because generating AI answers is vastly more expensive than generating traditional search engine responses.

Google last year admitted that an AI chat is ten times more expensive than a regular search engine query.  Microsoft’s GitHub Copilot is reported to lose an average of $20 per user every month. The economic realities of AI technology at this time basically rules out the use of an AI search engine as a replacement for traditional search engines.

4. Gartner’s Prediction Of 25% Decrease Assumes Search Engines Will Remain Unchanged

Gartner predicts a 25% decrease in traditional search query volume by 2026 but that prediction assumes that traditional search engines will remain the same. The Gartner analysis fails to account for the fact that search engines evolve not just on a yearly basis but on a month to month basis.

Search engines currently integrate AI technologies that increase search relevance in ways that innovate the entire search engine paradigm. For example, Google makes images tappable so that users can launch an image-based search for answers about the subject that’s in the image.

That’s called multi-modal search, a way to search using sound and vision in addition to traditional text-based searching.  There is absolutely no mention of multimodality in traditional search, a technology that shows how traditional search engines evolve to meet user’s needs.

So-called AI chatbot search engines are in their infancy and offer zero multimodality. How can a technology so comparatively primitive even be considered competitive to traditional search?

5. Why Claim That AI Chatbots Will Steal Market Share Is Unrealistic

The Gartner report assumes that AI chatbots and virtual agents will become more popular but that fails to consider that Gartner’s own research from June 2023 shows that users distrust AI Chatbots.

Gartner’s own report states:

“Only 8% of customers used a chatbot during their most recent customer service experience, according to a survey by Gartner, Inc. Of those, just 25% said they would use that chatbot again in the future.”

Customer’s lack of trust is especially noticeable in Your Money Or Your Life (YMYL) tasks that involve money.

Gartner reported:

“Just 17% of billing disputes are resolved by customers who used a chatbot at some stage in their journey…”

Gartner’s enthusiastic assumption that users will trust AI chatbots may be unfounded because it may not have considered that users do not trust chatbots for important YMYL search queries, according to Gartner’s own research data.

6. Gartner Advice Is To Rethink What?

Gartner’s advice to search marketers is to incorporate more experience, expertise, authoritativeness and trustworthiness in their content, which betrays a misunderstanding what EEAT actually is. For example, trustworthiness is not something that is added to content like a feature, trustworthiness is the sum of the experience, expertise and authoritativeness that the author of the content brings to an article.

Secondly, EEAT is a concept of what Google aspires to rank in search engines but they’re not actual ranking factors, they’re just concepts.

Third, marketers are already furiously incorporating the concept of EEAT into their search marketing strategy. So the advice to incorporate EEAT as part of the future marketing strategy is itself too late and a bit bereft of unique insight.

The advice also fails to acknowledge that user interactions and user engagement not only a role in search engine success in the present but that they will likely increase in importance as search engines incorporate AI to improve their relevance and meaningfulness to users.

That means traditional that search marketing will remain effective and in demand for creating awareness and demand.

7. Why Watermarking May Not Have An Impact

Gartner suggests that watermarking and authentication will increasingly become common due to government regulation. But that prediction fails to understand the supporting role that AI can play in content creation.

For example, there are workflows where a human reviews a product, scores it, provides a sentiment score and insights about which users may enjoy the product and then submits the review data to an AI to write the article based on the human insights. Should that be watermarked?

Another way that content creators use AI is to dictate their thoughts into a recording then hand it over to the AI with the instruction to polish it up and turn into to a professional article. Should that be watermarked as AI generated?

The ability of AI to analyze vast amounts of data complements the content production workflow and can pick out key qualities of the data such key concepts and conclusions, which in turn can be used by humans to create a document that is filled with their insights, bringing to bear their human expertise on interpreting the data. Now, what if that human then uses an AI to polish up the document and make it professional. Should that be watermarked?

The Gartner’s predictions about watermarking AI content fails to take into account how AI is actually used by many publishers to create well written content with human-first insights, which absolutely complicate the use of watermarking and calls into question the adoption of it in the long term, not to mention the adoption of it by 2026.

Gartner Predictions Don’t Hold Up To Scrutiny

The Gartner predictions cite actual facts from the real-world. But it fails to consider real-world factors that make AI technology as an impotent threat to traditional search engines. For example, there is no consideration of the inability to of AI to create a fresh search index or that AI Chatbot search engines aren’t even actual AI search engines.

It is incredible that the analysis failed to cite the fact that Bing Chat experienced no significant increase in users and has failed to peel way search volume from Google. These failures cast serious doubt on the accuracy of the predictions that search volume will decrease by 25%.

Read Gartner’s press release here:

Gartner Predicts Search Engine Volume Will Drop 25% by 2026, Due to AI Chatbots and Other Virtual Agents

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International SEO For 2024: 9-Point Checklist For Success

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International SEO For 2024: 9-Point Checklist For Success

Getting your international SEO strategy right can be an elusive feat.

There are a lot more factors at play than people give credit for, and it’s often a thankless job.

A successful international SEO strategy requires a deep knowledge of your company’s commercial strategy as well as technical SEO knowledge, cultural sensitivity, and excellent data skills.

Yet the industry often regards international SEO as just your hreflang setup.

In this article, I will distill the complexities of international SEO success into an actionable step-by-step list that will take you from beginner to advanced practitioner. Let’s begin!

Part I: Be Commercially Aware

1. Understand Why Your Company Is Going International

Companies can grow by expanding their products and services, focusing on gaining market penetration or expanding into new markets.

While your team’s goal might be traffic, leads, or revenue, the leadership team is likely working under a different set of parameters. Most of the time, leadership’s ultimate goal is to maximize shareholder value.

  • In founder-owned companies, growth goals might be slower and more sustainable, usually aimed at maintaining and growing profitability.
  • VC-owned companies have high growth goals because they must provide their investors with a return that’s higher than the stock market. This is what is known as the alpha, or your company’s ability to beat the market in growth.
  • Publicly traded companies are likely aiming to grow their share value.
  • Startups, depending on their maturity stage, are likely looking to prove product-market fit or expand their reach fast to show that their operations are scalable and have the potential to be profitable in the future. The goal of this is to aid in raising further capital from investors.

Understanding why businesses go international is essential for informing your SEO decisions. What’s best practice for SEO isn’t always what’s best for business.

You must adapt your strategy to your company’s growth model.

  • Companies choosing to grow sustainably and maintain profitability will likely expand more slowly to a market that resembles their core market.
  • VC-owned companies will be able to invest in a wider range of countries, with a smaller concern for providing their users with an experience on par with that of their core markets.
  • Startups can try to beat their competitors to market by expanding quickly and throwing a lot of money at the project, or they might be concerned with cash flow and try to expand fast but cut corners by using automatic translation.

2. Stack Rank Your Target Markets To Prioritize Your Investment

I promise I’ll get to hreflang implementation soon, but so much about international SEO has to do with commercial awareness – so bear with me; this will make you a better professional.

Many companies have different market tiers to reflect how much of a priority each market is. Market prioritization can happen using many different metrics, such as:

  • Average order value or lifetime customer value.
  • Amount of investment required.
  • Market size.
  • And market similarity.

American companies often prioritize developed English-speaking countries such as the UK, Canada, or Australia. These are most similar to their core market, and most of their market knowledge will be transferable.

After that, companies are likely to target large European economies, such as Germany and France. They might also target the LatAm market and Spain in the same effort.

The last prioritization tier can vary widely among companies, with a focus on the Nordic, Brazilian, or Asian markets.

Part II: Know Your Tech

3. Define Your International URL Structure

When doing international SEO, there are 4 different possible URL structures, each with its pros and cons.

ccTLD Structure

A ccTLD structure is set up to target different countries based on the domain type.

This structure is not ideal for companies that target different languages rather than different countries. For example, a .es website is targeting Spain, not the Spanish language.

An advantage to this kind of structure is that the ccTLD sends a very strong localization signal to search engines as to what market they are targeting, and they can lead to improved trust and CTR in your core country.

On the other hand, ccTLDs can dilute your site’s authority, as links will be spread across domains rather than concentrated on the .com.

gTLD With Subdirectories

This is my personal favorite when it comes to international SEO.

These URL structures can look like website.com/en if they’re targeting languages or website.com/en-gb if they’re targeting countries.

This configuration aggregates the authority you gain across your different territories into a single domain, it’s cheaper to maintain, and the .com TLD is widely recognizable by users worldwide.

On the other hand, this setup can look less personalized to people outside the US, who might wonder if you can service their markets.

gTLD With Subdomains

This setup involves placing international content on a subdomain like us.website.com. While once popular, it’s slipping in favor because it doesn’t bring anything unique to the table anymore.

This setup offers a clear signal to users and search engines about the intended audience of a specific subdomain.

However, subdomains often face issues with SEO, as Google tends to view them as separate entities. This separation can dilute link, similar to the ccTLD approach but without the geo-targeting advantages.

gTLD With Parameters

This is the setup where you add parameters at the end of the URL to indicate the language of the page, such as website.com/?lang=en.

I strongly advise against this setup, as it can present multiple technical SEO challenges and trust issues.

4. Understand Your Hreflang Setup

In the words of John Mueller: hreflang can be one of the most complex aspects of SEO.

Screenshot from Twitter, May 2024

Hreflang reminds me of a multilingual form of a canonical tag, where we tell search engines that one document is a version of the other and explain the relationship between them.

I find hreflang implementation very interesting from a technical point of view. Because development teams mostly manage it, and it can be very much hit or miss.

Often, hreflang is constructed from existing fields in your content management system (CMS) or content database.

You might find that your development team is pulling the HTML lang tag, which follows a different ISO standard than hreflang, leading to a broken implementation.

Other times, there is a field in your CMS that your development team pulls from to build your hreflang setup.

Finding out how your hreflang tags are generated can be extremely helpful in identifying the sources of different issues or mitigating potential risks.

So speak to your engineering team and ask them how you’re currently generating hreflang.

5. Implement Hreflang Without Errors

There are three ways to implement hreflang on your site:

  • On your sitemap.
  • Through your HTTP header.
  • On your HTML head.

The method most of us are most familiar with is the HTML head. And while you can use more than one method, they should match each other perfectly. Otherwise, you risk confusing search engines.

Here are some basic rules for getting it done correctly:

  • In your hreflang implementation, the URL must include domain and protocol.
  • You must follow the ISO 639-1 language codes – don’t go around making up your own.
  • Hreflang tags must be reciprocal. If the page you’re listing as a language alternative does not list you back, your implementation won’t work.
  • Audit your hreflang regularly. My favorite tool for this, since it added the hreflang cluster analysis and link graphs, is Ahrefs. For the record, Ahrefs is not paying me to say this; it’s a genuine recommendation and has helped me a lot in my work.
  • You should only have one page per language.
  • Your hreflang URLs should be self-canonicalizing and respond with a 200 code.

Follow the above rules, and you’ll avoid the most common hreflang mistakes that SEO pros make.

And if you’re interested in the technical SEO aspect beyond hreflang, I recommend reading Mind your language by Rob Owen.

Part III: Invest In Content Incrementally

6. Translate Your Top-performing Content Topics

Now that you have the basic commercial and technical knowledge covered, you’re ready to start creating a content strategy.

You likely have a wealth of content in your core market that can be recycled. But you want to focus on translating high-converting topics, not just any topic; otherwise, you might be wasting your budget!

Let’s go step by step.

Cluster Your Website’s Content By Topic

  • Crawl your site using your favorite SEO tool and extract the URL and H1.
  • Use ChatGPT to classify that list of URLs into topics. You might already know what you usually write about, so include those topics in your prompt. You don’t want to have a classification that’s too granular, so you can prompt chatGPT to only create groups with a minimum of 10 URLs (adjust this to reflect the size of your website) and class everything else as other. This is an example of what your prompt might look like: “I will provide you with a list of article titles and their corresponding URL. Classify this list into the following topics: survey best practices, research and analysis, employee surveys, market research and others. Return this in a table format with the URL, title and group name.”
  • Start a spreadsheet with all your URLs in the first column, titles in the second column, and the group they belong to in the third column.

Measure Your Performance By Topic

  • Export your GSC data and use a =VLOOKUP formula to match your clicks to your URLs.
  • Export your conversion data and use a =VLOOKUP formula to match your conversions (leads, sales, sign-ups, or revenue) to the right URL.
  • You can then copy your topics column onto a new sheet. Remove duplicates and use the =SUMIF formula to aggregate your click data and conversion data by topic.

Choose What Topics You’ll Be Translating First

Using this data, you can now choose what topics are most likely to drive conversions based on your core market data. Choose how many topics or pieces of content you’ll be translating based on your budget.

Personally, I like translating one topic at a time because I’ve found that generating topical authority on one specific topic makes it easier for me to rank on an adjacent topic that I write about next.

7. Localize Your English Content

Once you’re set up with all your key pages and a few content topics, it’s time to evaluate your investment and see where you could be getting a bigger return.

At this stage, many companies have translated their content into a few different languages and likely copied the US content into their UK and Australian sites. Now that you’ve done some translation, it’s time to work on localization.

If you’ve just copied your US content into your UK and Australian sites, your Google Search Console indexing report might be screaming at you, “Duplicate, Google selected a different canonical than the user.”

A very easy fix that could yield great returns is to localize your English content to the nuances of those English-speaking markets.

You will want to instruct your translation and localization providers to adapt the spellings of certain words, change the choice of words, introduce local expressions, and update any cited statistic for the US with their local equivalent.

For example, if I’m targeting a British audience, “analyze” becomes “analyse,” a “stroller” becomes a “pram,” and “soccer” becomes “football.”

8. Invest In In-market Content

Once you’ve got the basics in place, you can start tackling the specific needs of other markets. This strategy is expensive, and you should only use it in your priority markets, but it can really set you apart from your competitors.

For this, you will need to work with a local linguist to identify pain points, use cases, or needs exclusive to your target market.

For example, if France suddenly made it mandatory to run a diversity and inclusion study for companies with over 250 employees, I’d want to know this and create some content on DEI surveys at SurveyMonkey.

9. Integrate With Other Content Workflows

In step six, we evaluated our top-performing content, chose the best articles to translate, and got it all down. But wait. Some of these source articles have been updated. And there is even more content now!

To run a successful international SEO campaign you must integrate with all the other teams publishing content within your organization.

Usually, the teams creating content in an organization are SEO, content, PR, product marketing, demand generation, customer marketing, customer service, customer education, or solutions engineering.

That’s a lot, and you won’t be able to integrate with everyone all at once. Prioritize the teams that create the most revenue-generating content, such as SEO, content, or product marketing.

Working with these teams, you will have to establish a process for what happens when they create a new piece, update some content, or remove an existing piece.

These processes can differ for everyone, but I can tell you what I do with my team and hope it inspires you.

  • When a piece of content that’s already been localized into international markets is updated, we get the content in a queue to be re-localized the next quarter.
  • When they create a new piece of content, we evaluate its performance, and if it’s performing above average, we add it to a localization queue for the next quarter.
  • When they change the URL of a piece of content or delete it, all international sites must follow suit at the same time, since due to some technical limitations, not making the change globally would create some hreflang issues.

Wrapping Up

International SEO is vast and complex, and no article can cover it all, but many interesting resources have been created by SEO pros across the community for those who want to learn more.

Navigating the complexities of international SEO is no small feat. It’s an intricate dance of aligning commercial strategies with technical precision, cultural insights, and data-driven decisions.

From understanding your company’s core motives for global expansion to meticulously implementing hreflang tags and localizing content, every step plays a crucial role in building a successful international presence.

More resources: 


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Google’s AI Vision Driven By Panic, Not Users: Former Product Manager

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Hand pressing the red button. vector illustration

A 16-year Google veteran is raising concerns about the company’s current focus on AI, labeling it a “panic reaction” driven by fear of falling behind competitors.

Scott Jenson, who left Google last month, took to LinkedIn to critique the tech giant’s AI projects as “poorly motivated and driven by this mindless panic that as long as it had ‘AI’ in it, it would be great.”

Veteran’s Criticism Of Google’s AI Focus

Jenson stated that Google’s vision of creating an AI assistant for its ecosystem is “pure catnip” fueled by the fear of letting someone else get there first.

He parallels the ill-fated Google+ product, which he calls a “similar hysterical reaction” to Facebook’s rise.

Jenson wrote:

“This exact thing happened 13 years ago with Google+ (I was there for that fiasco as well). That was a similar hysterical reaction but to Facebook.”

Lack Of User-Driven Motivation

Jenson argues that Google’s strategy lacks motivation driven by genuine user needs, a sentiment echoed by a recent Gizmodo article that described this year’s Google I/O developer conference as “the most boring ever.”

The article, which Jenson linked to in his post, criticized Google for failing to clarify how Gemini’s new AI technology would integrate into its existing products and enhance the user experience.

See Jenson’s full post below:

Can You Turn Off Google’s AI Overviews?

One prime example of Google’s AI overreach is the AI overviews feature, which generates summaries to directly answer search queries by ingesting information from across the web.

This controversial move has sparked legal battles, with publishers accusing Google of violating intellectual property rights and unfairly profiting from their content without permission.

Related: Google’s AI Overviews Documentation: Key SEO Insights

Turning Off AI Overviews

While Google doesn’t provide an official setting to turn off AI overviews, a viral article from Tom’s Hardware suggests using browser extensions.

Alternatively, you can configure Chrome to go directly to web search results, bypassing the AI-generated overviews.

Here are the steps:

  • Open Chrome settings by clicking the three dots in the top-right corner and selecting “Settings” from the menu.
  • In the Settings window, click on the “Search Engine” tab on the left side.
  • Under the “Search Engine” section, click “Manage search engines and site search.”
  • Scroll down to the “Site search” area and click “Add” to create a new entry.

In the new entry, enter the following details:

  • Name: Google (Web)
  • Shortcut: www.google.com
  • URL: {google:baseURL}/search?udm=14&q=%s
  • Click “Add
Screenshot from: chrome://settings/searchEngines, May 2024.

Lastly, click the three dots next to the new “Google (Web)” entry and select “Make default.”

1716224163 590 Googles AI Vision Driven By Panic Not Users Former ProductScreenshot from: chrome://settings/searchEngines, May 2024.

After following these steps, Chrome will now default to showing regular web search results instead of the AI overview summaries when you perform searches from the address bar.

Tensions Over Data Usage

The controversy surrounding AI overviews creates tension between tech companies and content creators over using online data for AI training.

Publishers argue that Google’s AI summaries could siphon website traffic, threatening independent creators’ revenue streams, which rely on search referrals.

The debate reflects the need for updated frameworks to balance innovation and fair compensation for content creators, maintaining a sustainable open internet ecosystem.


FAQ

What concerns has Scott Jenson raised about Google’s AI focus?

Scott Jenson, a former Google product manager, has expressed concerns that Google’s current AI focus is more of a “panic reaction” to stay ahead of competitors rather than addressing user needs. He critiques Google’s AI initiatives as poorly motivated and driven by a fear of letting others get ahead.

How does Scott Jenson compare Google’s AI strategy to past projects?

Jenson parallels Google’s current AI focus and the company’s response to Facebook years ago with Google+. He describes both as “hysterical reactions” driven by competition, which, in the case of Google+, resulted in a product that failed to meet its objectives.

Why are content creators concerned about Google’s AI overviews?

Content creators worry that Google’s AI overviews, which generate summaries by ingesting web content, could reduce site traffic. They argue that this practice is unfair as it uses their content without permission and impacts their revenue streams that rely on search referrals.

How can users turn off Google’s AI overviews in Chrome?

Although no official setting exists to disable AI overviews, users can use a workaround by enabling a specific Chrome setting or using a browser extension.

Here are the steps:

  • Open Chrome settings by clicking the three dots in the top-right corner and selecting “Settings” from the menu.
  • In the Settings window, click on the “Search Engine” tab on the left side.
  • Under the “Search Engine” section, click “Manage search engines and site search.”
  • Scroll down to the “Site search” area and click “Add” to create a new entry.

In the new entry, enter the following details:

    • Name: Google (Web)
    • Shortcut: www.google.com
    • URL: {google:baseURL}/search?udm=14&q=%s
    • Click “Add

This will force Chrome to skip AI-generated overviews and show the classic list of web links.


Featured Image: Sira Anamwong/Shutterstock

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How To Use ChatGPT For Keyword Research

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How To Use ChatGPT For Keyword Research

Anyone not using ChatGPT for keyword research is missing a trick.

You can save time and understand an entire topic in seconds instead of hours.

In this article, I outline my most effective ChatGPT prompts for keyword research and teach you how I put them together so that you, too, can take, edit, and enhance them even further.

But before we jump into the prompts, I want to emphasize that you shouldn’t replace keyword research tools or disregard traditional keyword research methods.

ChatGPT can make mistakes. It can even create new keywords if you give it the right prompt. For example, I asked it to provide me with a unique keyword for the topic “SEO” that had never been searched before.

Interstellar Internet SEO: Optimizing content for the theoretical concept of an interstellar internet, considering the challenges of space-time and interplanetary communication delays.”

Although I want to jump into my LinkedIn profile and update my title to “Interstellar Internet SEO Consultant,” unfortunately, no one has searched that (and they probably never will)!

You must not blindly rely on the data you get back from ChatGPT.

What you can rely on ChatGPT for is the topic ideation stage of keyword research and inspiration.

ChatGPT is a large language model trained with massive amounts of data to accurately predict what word will come next in a sentence. However, it does not know how to do keyword research yet.

Instead, think of ChatGPT as having an expert on any topic armed with the information if you ask it the right question.

In this guide, that is exactly what I aim to teach you how to do – the most essential prompts you need to know when performing topical keyword research.

Best ChatGPT Keyword Research Prompts

The following ChatGPT keyword research prompts can be used on any niche, even a topic to which you are brand new.

For this demonstration, let’s use the topic of “SEO” to demonstrate these prompts.

Generating Keyword Ideas Based On A Topic

What Are The {X} Most Popular Sub-topics Related To {Topic}?

Screenshot from ChatGPT 4, April 2024

The first prompt is to give you an idea of the niche.

As shown above, ChatGPT did a great job understanding and breaking down SEO into three pillars: on-page, off-page & technical.

The key to the following prompt is to take one of the topics ChatGPT has given and query the sub-topics.

What Are The {X} Most Popular Sub-topics Related To {Sub-topic}?

For this example, let’s query, “What are the most popular sub-topics related to keyword research?”

Having done keyword research for over 10 years, I would expect it to output information related to keyword research metrics, the types of keywords, and intent.

Let’s see.

ChatGPT keyword prompt subtopicScreenshot from ChatGPT 4, April 2024

Again, right on the money.

To get the keywords you want without having ChatGPT describe each answer, use the prompt “list without description.”

Here is an example of that.

List Without Description The Top {X} Most Popular Keywords For The Topic Of {X}chatgpt keyword research prompt for most popular keywords

You can even branch these keywords out further into their long-tail.

Example prompt:

List Without Description The Top {X} Most Popular Long-tail Keywords For The Topic “{X}”

chatgpt keyword research prompt longtail keywordsScreenshot ChatGPT 4,April 2024

List Without Description The Top Semantically Related Keywords And Entities For The Topic {X}

You can even ask ChatGPT what any topic’s semantically related keywords and entities are!

chatgpt keyword research semantic intentScreenshot ChatGPT 4, April 2024

Tip: The Onion Method Of Prompting ChatGPT

When you are happy with a series of prompts, add them all to one prompt. For example, so far in this article, we have asked ChatGPT the following:

  • What are the four most popular sub-topics related to SEO?
  • What are the four most popular sub-topics related to keyword research
  • List without description the top five most popular keywords for “keyword intent”?
  • List without description the top five most popular long-tail keywords for the topic “keyword intent types”?
  • List without description the top semantically related keywords and entities for the topic “types of keyword intent in SEO.”

Combine all five into one prompt by telling ChatGPT to perform a series of steps. Example:

“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, Step 4, and Step 5”

Example:

“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, Step 4 and Step 5. Step 1 – Generate an answer for the 3 most popular sub-topics related to {Topic}?. Step 2 – Generate 3 of the most popular sub-topics related to each answer. Step 3 – Take those answers and list without description their top 3 most popular keywords. Step 4 – For the answers given of their most popular keywords, provide 3 long-tail keywords. Step 5 – for each long-tail keyword offered in the response, a list without descriptions 3 of their top semantically related keywords and entities.”

Generating Keyword Ideas Based On A Question

Taking the steps approach from above, we can get ChatGPT to help streamline getting keyword ideas based on a question. For example, let’s ask, “What is SEO?

“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, and Step 4. Step 1 Generate 10 questions about “{Question}”?. Step 2 – Generate 5 more questions about “{Question}” that do not repeat the above. Step 3 – Generate 5 more questions about “{Question}” that do not repeat the above. Step 4 – Based on the above Steps 1,2,3 suggest a final list of questions avoiding duplicates or semantically similar questions.”

chatgpt for question keyword researchScreenshot ChatGPT 4, April 2024

Generating Keyword Ideas Using ChatGPT Based On The Alphabet Soup Method

One of my favorite methods, manually, without even using a keyword research tool, is to generate keyword research ideas from Google autocomplete, going from A to Z.

Generating Keyword Ideas using ChatGPT Based on the Alphabet Soup MethodScreenshot from Google autocomplete, April 2024

You can also do this using ChatGPT.

Example prompt:

“give me popular keywords that includes the keyword “SEO”, and the next letter of the word starts with a”

ChatGPT Alphabet keyword research methodScreenshot from ChatGPT 4, April 2024

Tip: Using the onion prompting method above, we can combine all this in one prompt.

“Give me five popular keywords that include “SEO” in the word, and the following letter starts with a. Once the answer has been done, move on to giving five more popular keywords that include “SEO” for each letter of the alphabet b to z.”

Generating Keyword Ideas Based On User Personas

When it comes to keyword research, understanding user personas is essential for understanding your target audience and keeping your keyword research focused and targeted. ChatGPT may help you get an initial understanding of customer personas.

Example prompt:

“For the topic of “{Topic}” list 10 keywords each for the different types of user personas”

ChatGPT and user personasScreenshot from ChatGPT 4, April 2024

You could even go a step further and ask for questions based on those topics that those specific user personas may be searching for:

ChatGPT and keyword research based on personaScreenshot ChatGPT 4, April 2024

As well as get the keywords to target based on those questions:

“For each question listed above for each persona, list the keywords, as well as the long-tail keywords to target, and put them in a table”

question and longtail and user persona using a table for ChatGPT keyword researchScreenshot from ChatGPT 4, April 2024

Generating Keyword Ideas Using ChatGPT Based On Searcher Intent And User Personas

Understanding the keywords your target persona may be searching is the first step to effective keyword research. The next step is to understand the search intent behind those keywords and which content format may work best.

For example, a business owner who is new to SEO or has just heard about it may be searching for “what is SEO.”

However, if they are further down the funnel and in the navigational stage, they may search for “top SEO firms.”

You can query ChatGPT to inspire you here based on any topic and your target user persona.

SEO Example:

“For the topic of “{Topic}” list 10 keywords each for the different types of searcher intent that a {Target Persona} would be searching for”

ChatGPT For Keyword Research Admin

Here is how you can best use ChatGPT for keyword research admin tasks.

Using ChatGPT As A Keyword Categorization Tool

One of the use cases for using ChatGPT is for keyword categorization.

In the past, I would have had to devise spreadsheet formulas to categorize keywords or even spend hours filtering and manually categorizing keywords.

ChatGPT can be a great companion for running a short version of this for you.

Let’s say you have done keyword research in a keyword research tool, have a list of keywords, and want to categorize them.

You could use the following prompt:

“Filter the below list of keywords into categories, target persona, searcher intent, search volume and add information to a six-column table: List of keywords – [LIST OF KEYWORDS], Keyword Search Volume [SEARCH VOLUMES] and Keyword Difficulties [KEYWORD DIFFICUTIES].”

Using Chat GPT as a Keyword Categorization ToolScreenshot from ChatGPT, April 2024

Tip: Add keyword metrics from the keyword research tools, as using the search volumes that a ChatGPT prompt may give you will be wildly inaccurate at best.

Using ChatGPT For Keyword Clustering

Another of ChatGPT’s use cases for keyword research is to help you cluster. Many keywords have the same intent, and by grouping related keywords, you may find that one piece of content can often target multiple keywords at once.

However, be careful not to rely only on LLM data for clustering. What ChatGPT may cluster as a similar keyword, the SERP or the user may not agree with. But it is a good starting point.

The big downside of using ChatGPT for keyword clustering is actually the amount of keyword data you can cluster based on the memory limits.

So, you may find a keyword clustering tool or script that is better for large keyword clustering tasks. But for small amounts of keywords, ChatGPT is actually quite good.

A great use small keyword clustering use case using ChatGPT is for grouping People Also Ask (PAA) questions.

Use the following prompt to group keywords based on their semantic relationships. For example:

“Organize the following keywords into groups based on their semantic relationships, and give a short name to each group: [LIST OF PAA], create a two-column table where each keyword sits on its own row.

Using Chat GPT For Keyword ClusteringScreenshot from ChatGPT, April 2024

Using Chat GPT For Keyword Expansion By Patterns

One of my favorite methods of doing keyword research is pattern spotting.

Most seed keywords have a variable that can expand your target keywords.

Here are a few examples of patterns:

1. Question Patterns

(who, what, where, why, how, are, can, do, does, will)

“Generate [X] keywords for the topic “[Topic]” that contain any or all of the following “who, what, where, why, how, are, can, do, does, will”

question based keywords keyword research ChatGPTScreenshot ChatGPT 4, April 2024

2. Comparison Patterns

Example:

“Generate 50 keywords for the topic “{Topic}” that contain any or all of the following “for, vs, alternative, best, top, review”

chatgpt comparison patterns for keyword researchScreenshot ChatGPT 4, April 2024

3. Brand Patterns

Another one of my favorite modifiers is a keyword by brand.

We are probably all familiar with the most popular SEO brands; however, if you aren’t, you could ask your AI friend to do the heavy lifting.

Example prompt:

“For the top {Topic} brands what are the top “vs” keywords”

ChatGPT brand patterns promptScreenshot ChatGPT 4, April 2024

4. Search Intent Patterns

One of the most common search intent patterns is “best.”

When someone is searching for a “best {topic}” keyword, they are generally searching for a comprehensive list or guide that highlights the top options, products, or services within that specific topic, along with their features, benefits, and potential drawbacks, to make an informed decision.

Example:

“For the topic of “[Topic]” what are the 20 top keywords that include “best”

ChatGPT best based keyword researchScreenshot ChatGPT 4, April 2024

Again, this guide to keyword research using ChatGPT has emphasized the ease of generating keyword research ideas by utilizing ChatGPT throughout the process.

Keyword Research Using ChatGPT Vs. Keyword Research Tools

Free Vs. Paid Keyword Research Tools

Like keyword research tools, ChatGPT has free and paid options.

However, one of the most significant drawbacks of using ChatGPT for keyword research alone is the absence of SEO metrics to help you make smarter decisions.

To improve accuracy, you could take the results it gives you and verify them with your classic keyword research tool – or vice versa, as shown above, uploading accurate data into the tool and then prompting.

However, you must consider how long it takes to type and fine-tune your prompt to get your desired data versus using the filters within popular keyword research tools.

For example, if we use a popular keyword research tool using filters, you could have all of the “best” queries with all of their SEO metrics:

ahrefs screenshot for best seoScreenshot from Ahrefs Keyword Explorer, March 2024

And unlike ChatGPT, generally, there is no token limit; you can extract several hundred, if not thousands, of keywords at a time.

As I have mentioned multiple times throughout this piece, you cannot blindly trust the data or SEO metrics it may attempt to provide you with.

The key is to validate the keyword research with a keyword research tool.

ChatGPT For International SEO Keyword Research

ChatGPT can be a terrific multilingual keyword research assistant.

For example, if you wanted to research keywords in a foreign language such as French. You could ask ChatGPT to translate your English keywords;

translating keywords with ChatGPTScreenshot ChatGPT 4, Apil 2024
The key is to take the data above and paste it into a popular keyword research tool to verify.
As you can see below, many of the keyword translations for the English keywords do not have any search volume for direct translations in French.
verifying the data with ahrefsScreenshot from Ahrefs Keyword Explorer, April 2024

But don’t worry, there is a workaround: If you have access to a competitor keyword research tool, you can see what webpage is ranking for that query – and then identify the top keyword for that page based on the ChatGPT translated keywords that do have search volume.

top keyword from ahrefs keyword explorerScreenshot from Ahrefs Keyword Explorer, April 2024

Or, if you don’t have access to a paid keyword research tool, you could always take the top-performing result, extract the page copy, and then ask ChatGPT what the primary keyword for the page is.

Key Takeaway

ChatGPT can be an expert on any topic and an invaluable keyword research tool. However, it is another tool to add to your toolbox when doing keyword research; it does not replace traditional keyword research tools.

As shown throughout this tutorial, from making up keywords at the beginning to inaccuracies around data and translations, ChatGPT can make mistakes when used for keyword research.

You cannot blindly trust the data you get back from ChatGPT.

However, it can offer a shortcut to understanding any topic for which you need to do keyword research and, as a result, save you countless hours.

But the key is how you prompt.

The prompts I shared with you above will help you understand a topic in minutes instead of hours and allow you to better seed keywords using keyword research tools.

It can even replace mundane keyword clustering tasks that you used to do with formulas in spreadsheets or generate ideas based on keywords you give it.

Paired with traditional keyword research tools, ChatGPT for keyword research can be a powerful tool in your arsenal.

More resources:


Featured Image: Tatiana Shepeleva/Shutterstock

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