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How AI-generated images can streamline your SEO game with DALL-E 2

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How AI-generated images can streamline your SEO game with DALLE-2

30-second summary:

  • SEOs are always on the lookout for innovative technology that can help them amplify content creation effectively
  • One such innovation that is on the cusp of being the next big thing in SEO and content creation is OpenAI’s DALL-E 2
  • What is it, how does it work, and how can SEOs use it (or at least start experimenting with it)?

Have you ever wanted to feel like Salvador Dali? Maybe even create a small cute robot that could look like WALL-E? Your dreams very well might come true with the recent development of the technology behind AI. If that sounds interesting, let’s dive a bit deeper into this topic. Let’s talk about DALL-E 2.

Ok Google, what does AI Do?

Artificial intelligence (AI) aims to create unique algorithms that can behave like people in specific situations – recognize human speech and various objects, write and read texts, and the like. This technology is already far ahead of human capabilities in many spheres involving data processing. Until recently, AI was encroaching mainly on the fields that are linked with technical tasks – predictive analytics, robotization, image, and speech recognition. Today AI surpasses people by 40 percent on trivia

But can AI also take on creative functions? It seems this is the last field to be mastered by neural networks. Art is a complicated combination of skill, creativity, and aesthetic taste, which all are very human elements. However, in April 2022, the OpenAI group proved otherwise by releasing a powerful text-to-image convertor, DALLE – 2, that can transform any text caption into a visual presentation that has never existed before. Its most winning feature is that the tool can precisely and logically convey relationships between objects it displays.

What is DALLE-2?

This neural network was created by OpenAI. Originally, it was GPT-2, a technology that could work with languages – answer questions, complete text, analyze content, and make conclusions. It was improved to GPT-3 – its capabilities expanded beyond textual information and enabled it to work with the images. 

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Already in January 2021, this technology was followed by its new mind-blowing version that could build a connection between text and images. This neural network was called DALLE. The most remarkable thing is that it can come up not only with objects known to us but also produce completely new combinations, creating objects that do not exist in nature. In simple words, DALLE is a transformer consisting of the decoder, which processes a sequence of 1280 tokens. These are 256 text tokens and 1024 image part tokens. The algorithm treats image regions in the same way as words in a text and generates new images identically to how GPT-3 generates new text. In 2022, the project was scaled to DALLE-2. The improved version creates an image just from a text prompt.

How does DALLE-2 work?

It is not the first attempt to create a text-to-image generation system. However, the capabilities of DALLE-2 are much broader. This neural network can effectively link textual and visual abstractions and provide a true-to-life image. How does the system know how a particular object is interacting with the environment? The algorithm is quite difficult to be explained in detail. Still, roughly it consists of several stages and uses other OpenAI models – CLIP (Contrastive Language-Image Pre-training) and GLIDE (Guided Language-to-Image Diffusion for Generation and Editing).

  • Mapping the image description to its space presentation via the CLIP text encoder. CLIP is trained on hundreds of millions of images and their associated captions, figuring out how a particular piece of text relates to an image. The model does not predict the caption but learns how it is related to the image. This comparative approach allows establishing the relationship between textual and visual representations of the same abstract object. This stage is critical to the creation of images by the neural network.
  • Encoding the CLIP-learned image. The next task is to create the image, the details of which have been suggested by CLIP. Now, DALLE-2 uses a modified version of another OpenAI model, GLIDE, to create this image. It is based on a diffusion model – data is generated by reversing the process of gradual image noise. The learning process is supplemented with additional textual information, which ultimately leads to the creation of more accurate images. 

Based on the above, DALL-E 2 can generate semantically consistent images that naturally fit any object in the surrounding space.

DALLE-2 for SEO

The vast potential of AI image generation immediately attracted the attention of SEO specialists. They spend a lot of time finding appropriate pictures to support their text content. However, it becomes increasingly difficult to invent something that is not just copied and stitched together from the web. So DALLE-2 can become a great source of a never-ending flow of wholly unique and non-standard images. Interestingly, users will have exclusive rights to use the images they create, including for commercial use.

How it can help SEO

Nowadays, website and content promotion are not possible without attractive visuals. Images add more value to your SEO efforts – your site wins more user engagement and accessibility. But sourcing enough appropriate pictures has always been a headache. DALLE-2 can solve this task with ease. You just need to print a descriptive prompt of your future image, and AI will come up with a result. The text should not exceed 400 characters. But users should be ready to train a little to create explicit requests. It is highly advisable to study Prompt Book and master the basics to avoid weird results. You will learn the most valuable tips on how to get the most out of this fantastic image generator.

If you’d like to further automate your image creation process this tool will allow you to generate a prompt that can be used on DALLE-2.

Use cases (blog posts, product images, designs, digital art, thumbnails)

AI algorithms were already used in SEO before for naming objects on the images and creating descriptions for them based on data. With DALLE-2, this process is flipped around, and now you can generate images based on text prompts. No matter whether you are running an online blog or a store – you need lots of visuals to attract new customers and followers. And DALLE-2 can successfully be integrated into any project where you need image supplements –  create illustrations for your blog posts, product descriptions, design sketches, and much more. Moreover, you can further modify already created images. 

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You can already see some successful use cases of DALLE-2. 

  • Blog thumbnail optimization. The Deephaven blog thumbnails have been replaced by images fully generated by DALLE-2. It took a couple of minutes and several prompts per image to get the desired result. However, it is a significant time saving compared to what would have been spent on the search for stock images. A nice bonus is that DALLE-2-generated images are fully unique and memorable.
  • Design development. DALLE-2 can become an efficient tool in the design field. And it looks like its capabilities are endless. For example, a picture of the existing garden was taken, and a rectangular swimming pool was applied to it via DALLE-2. It helps the client envision how it might look in reality.

For more use cases and live community discussions join r/dalle.

Currently, users are just experimenting with DALLE-2, but there is no doubt it will be soon actively applied in business, architecture, fashion, and other spheres.

Examples of DALL-E 2

DALL-E 2 is launched in beta version with a credit-based model open to 100,000 users. Another million applicants are waiting for approval to test this AI product. Some users have already shared their first experience with the converter, and the results are impressive. DALL-E 2 processes the craziest requests and offers its interpretation. Here are a few examples:

Prompt #1

A sad beaver in the sweater sitting in front of the screen and thinking about apples.

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Examples of AI-generated images can streamline your SEO game with DALLE-2 - Sad beaver

Source: Twitter

Prompt #2

A charcuterie board floating in a pool on the Amalfi coast.

Examples of AI-generated images can streamline your SEO game with DALLE-2 - Amalfi coast
Source: Twitter

Prompt #3

Source: Twitter

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Prompt #4

A person in the space suit walking on Mars near the creator with dried-out grass and remnants of the Voyager.

Examples of AI-generated images can streamline your SEO game with DALLE-2 - Space man
Prompt:A person in the space suit walking on Mars near the creator with dried-out grass and remnants of the Voyager

Source: LinkedIn

Prompt #5

A Ukrainian on the field harvesting crops.

Source: Twitter

Conclusion

DALL-E 2 is a revolutionary text-to-image converter today. It will help you instantly generate a variety of unique images with only a short text prompt in failry shorter time spans than you would spend on photo stock sites. This technology is an absolute game changer and can rearrange a lot of things in SEO in the coming years. Yet, more live testing is still needed to benefit from DALL-E 2 to the fullest.

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Dima Makei is Head of SEO at Omnicom Media Group. He is also passionate about teaching and has previously served as a Marketing Professor at Seneca College. Find him on Twitter @dima_makei.

Subscribe to the Search Engine Watch newsletter for insights on SEO, the search landscape, search marketing, digital marketing, leadership, podcasts, and more.

Join the conversation with us on LinkedIn and Twitter.

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56 Google Search Statistics to Bookmark for 2024

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56 Google Search Statistics to Bookmark for 2024

If you’re curious about the state of Google search in 2024, look no further.

Each year we pick, vet, and categorize a list of up-to-date statistics to give you insights from trusted sources on Google search trends.

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  1. Google has a web index of “about 400 billion documents”. (The Capitol Forum)
  2. Google’s search index is over 100 million gigabytes in size. (Google)
  3. There are an estimated 3.5 billion searches on Google each day. (Internet Live Stats)
  4. 61.5% of desktop searches and 34.4% of mobile searches result in no clicks. (SparkToro)
  5. 15% of all Google searches have never been searched before. (Google)
  6. 94.74% of keywords get 10 monthly searches or fewer. (Ahrefs)
  7. The most searched keyword in the US and globally is “YouTube,” and youtube.com gets the most traffic from Google. (Ahrefs)
  8. 96.55% of all pages get zero search traffic from Google. (Ahrefs)
  9. 50-65% of all number-one spots are dominated by featured snippets. (Authority Hacker)
  10. Reddit is the most popular domain for product review queries. (Detailed)
  1. Google is the most used search engine in the world, with a mobile market share of 95.32% and a desktop market share of 81.95%. (Statista)
    63.41% of all US web traffic referrals come from Google.63.41% of all US web traffic referrals come from Google.
  2. Google.com generated 84.2 billion visits a month in 2023. (Statista)
  3. Google generated $307.4 billion in revenue in 2023. (Alphabet Investor Relations)
  4. 63.41% of all US web traffic referrals come from Google. (SparkToro)
  5. 92.96% of global traffic comes from Google Search, Google Images, and Google Maps. (SparkToro)
  6. Only 49% of Gen Z women use Google as their search engine. The rest use TikTok. (Search Engine Land)
  1. 58.67% of all website traffic worldwide comes from mobile phones. (Statista)
  2. 57% of local search queries are submitted using a mobile device or tablet. (ReviewTrackers)
    57% of local search queries are submitted using a mobile device or tablet. 57% of local search queries are submitted using a mobile device or tablet.
  3. 51% of smartphone users have discovered a new company or product when conducting a search on their smartphones. (Think With Google)
  4. 54% of smartphone users search for business hours, and 53% search for directions to local stores. (Think With Google)
  5. 18% of local searches on smartphones lead to a purchase within a day vs. 7% of non-local searches. (Think With Google)
  6. 56% of in-store shoppers used their smartphones to shop or research items while they were in-store. (Think With Google)
  7. 60% of smartphone users have contacted a business directly using the search results (e.g., “click to call” option). (Think With Google)
  8. 63.6% of consumers say they are likely to check reviews on Google before visiting a business location. (ReviewTrackers)
  9. 88% of consumers would use a business that replies to all of its reviews. (BrightLocal)
  10. Customers are 2.7 times more likely to consider a business reputable if they find a complete Business Profile on Google Search and Maps. (Google)
  11. Customers are 70% more likely to visit and 50% more likely to consider purchasing from businesses with a complete Business Profile. (Google)
  12. 76% of people who search on their smartphones for something nearby visit a business within a day. (Think With Google)
  13. 28% of searches for something nearby result in a purchase. (Think With Google)
  14. Mobile searches for “store open near me” (such as, “grocery store open near me” have grown by over 250% in the last two years. (Think With Google)
  1. People use Google Lens for 12 billion visual searches a month. (Google)
  2. 50% of online shoppers say images helped them decide what to buy. (Think With Google)
  3. There are an estimated 136 billion indexed images on Google Image Search. (Photutorial)
  4. 15.8% of Google SERPs show images. (Moz)
  5. People click on 3D images almost 50% more than static ones. (Google)
  1. More than 800 million people use Google Discover monthly to stay updated on their interests. (Google)
  2. 46% of Google Discover URLs are news sites, 44% e-commerce, 7% entertainment, and 2% travel. (Search Engine Journal)
  3. Even though news sites accounted for under 50% of Google Discover URLs, they received 99% of Discover clicks. (Search Engine Journal)
    Even though news sites accounted for under 50% of Google Discover URLs, they received 99% of Discover clicks.Even though news sites accounted for under 50% of Google Discover URLs, they received 99% of Discover clicks.
  4. Most Google Discover URLs only receive traffic for three to four days, with most of that traffic occurring one to two days after publishing. (Search Engine Journal)
  5. The clickthrough rate (CTR) for Google Discover is 11%. (Search Engine Journal)
  1. 91.45% of search volumes in Google Ads Keyword Planner are overestimates. (Ahrefs)
  2. For every $1 a business spends on Google Ads, they receive $8 in profit through Google Search and Ads. (Google)
  3. Google removed 5.5 billion ads, suspended 12.7 million advertiser accounts, restricted over 6.9 billion ads, and restricted ads from showing up on 2.1 billion publisher pages in 2023. (Google)
  4. The average shopping click-through rate (CTR) across all industries is 0.86% for Google Ads. (Wordstream)
  5. The average shopping cost per click (CPC) across all industries is $0.66 for Google Ads. (Wordstream)
  6. The average shopping conversion rate (CVR) across all industries is 1.91% for Google Ads. (Wordstream)
  1. 58% of consumers ages 25-34 use voice search daily. (UpCity)
  2. 16% of people use voice search for local “near me” searches. (UpCity)
  3. 67% of consumers say they’re very likely to use voice search when seeking information. (UpCity)
  4. Active users of the Google Assistant grew 4X over the past year, as of 2019. (Think With Google)
  5. Google Assistant hit 1 billion app installs. (Android Police)
  1. AI-generated answers from SGE were available for 91% of entertainment queries but only 17% of healthcare queries. (Statista)
  2. The AI-generated answers in Google’s Search Generative Experience (SGE) do not match any links from the top 10 Google organic search results 93.8% of the time. (Search Engine Journal)
  3. Google displays a Search Generative element for 86.8% of all search queries. (Authoritas)
    Google displays a Search Generative element for 86.8% of all search queries. Google displays a Search Generative element for 86.8% of all search queries.
  4. 62% of generative links came from sources outside the top 10 ranking organic domains. Only 20.1% of generative URLs directly match an organic URL ranking on page one. (Authoritas)
  5. 70% of SEOs said that they were worried about the impact of SGE on organic search (Aira)

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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.

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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.

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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.

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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:

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“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.”

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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.

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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.

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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.

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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.

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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;

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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.

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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.

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Featured Image: Tatiana Shepeleva/Shutterstock

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OpenAI Expected to Integrate Real-Time Data In ChatGPT

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OpenAI ChatGPT announcement

Sam Altman, CEO of OpenAI, dispelled rumors that a new search engine would be announced on Monday, May 13. Recent deals have raised the expectation that OpenAI will announce the integration of real-time content from English, Spanish, and French publications into ChatGPT, complete with links to the original sources.

OpenAI Search Is Not Happening

Many competing search engines have tried and failed to challenge Google as the leading search engine. A new wave of hybrid generative AI search engines is currently trying to knock Google from the top spot with arguably very little success.

Sam Altman is on record saying that creating a search engine to compete against Google is not a viable approach. He suggested that technological disruption was the way to replace Google by changing the search paradigm altogether. The speculation that Altman is going to announce a me-too search engine on Monday never made sense given his recent history of dismissing the concept as a non-starter.

So perhaps it’s not a surprise that he recently ended the speculation by explicitly saying that he will not be announcing a search engine on Monday.

He tweeted:

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“not gpt-5, not a search engine, but we’ve been hard at work on some new stuff we think people will love! feels like magic to me.”

“New Stuff” May Be Iterative Improvement

It’s quite likely that what’s going to be announced is iterative which means it improves ChatGPT but not replaces it. This fits into how Altman recently expressed his approach with ChatGPT.

He remarked:

“And it does kind of suck to ship a product that you’re embarrassed about, but it’s much better than the alternative. And in this case in particular, where I think we really owe it to society to deploy iteratively.

There could totally be things in the future that would change where we think iterative deployment isn’t such a good strategy, but it does feel like the current best approach that we have and I think we’ve gained a lot from from doing this and… hopefully the larger world has gained something too.”

Improving ChatGPT iteratively is Sam Altman’s preference and recent clues point to what those changes may be.

Recent Deals Contain Clues

OpenAI has been making deals with news media and User Generated Content publishers since December 2023. Mainstream media has reported these deals as being about licensing content for training large language models. But they overlooked a a key detail that we reported on last month which is that these deals give OpenAI access to real-time information that they stated will be used to give attribution to that real-time data in the form of links.

That means that ChatGPT users will gain the ability to access real-time news and to use that information creatively within ChatGPT.

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Dotdash Meredith Deal

Dotdash Meredith (DDM) is the publisher of big brand publications such as Better Homes & Gardens, FOOD & WINE, InStyle, Investopedia, and People magazine. The deal that was announced goes way beyond using the content as training data. The deal is explicitly about surfacing the Dotdash Meredith content itself in ChatGPT.

The announcement stated:

“As part of the agreement, OpenAI will display content and links attributed to DDM in relevant ChatGPT responses. …This deal is a testament to the great work OpenAI is doing on both fronts to partner with creators and publishers and ensure a healthy Internet for the future.

Over 200 million Americans each month trust our content to help them make decisions, solve problems, find inspiration, and live fuller lives. This partnership delivers the best, most relevant content right to the heart of ChatGPT.”

A statement from OpenAI gives credibility to the speculation that OpenAI intends to directly show licensed third-party content as part of ChatGPT answers.

OpenAI explained:

“We’re thrilled to partner with Dotdash Meredith to bring its trusted brands to ChatGPT and to explore new approaches in advancing the publishing and marketing industries.”

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Something that DDM also gets out of this deal is that OpenAI will enhance DDM’s in-house ad targeting in order show more tightly focused contextual advertising.

Le Monde And Prisa Media Deals

In March 2024 OpenAI announced a deal with two global media companies, Le Monde and Prisa Media. Le Monde is a French news publication and Prisa Media is a Spanish language multimedia company. The interesting aspects of these two deals is that it gives OpenAI access to real-time data in French and Spanish.

Prisa Media is a global Spanish language media company based in Madrid, Spain that is comprised of magazines, newspapers, podcasts, radio stations, and television networks. It’s reach extends from Spain to America. American media companies include publications in the United States, Argentina, Bolivia, Chile, Colombia, Costa Rica, Ecuador, Mexico, and Panama. That is a massive amount of real-time information in addition to a massive audience of millions.

OpenAI explicitly announced that the purpose of this deal was to bring this content directly to ChatGPT users.

The announcement explained:

“We are continually making improvements to ChatGPT and are supporting the essential role of the news industry in delivering real-time, authoritative information to users. …Our partnerships will enable ChatGPT users to engage with Le Monde and Prisa Media’s high-quality content on recent events in ChatGPT, and their content will also contribute to the training of our models.”

That deal is not just about training data. It’s about bringing current events data to ChatGPT users.

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The announcement elaborated in more detail:

“…our goal is to enable ChatGPT users around the world to connect with the news in new ways that are interactive and insightful.”

As noted in our April 30th article that revealed that OpenAI will show links in ChatGPT, OpenAI intends to show third party content with links to that content.

OpenAI commented on the purpose of the Le Monde and Prisa Media partnership:

“Over the coming months, ChatGPT users will be able to interact with relevant news content from these publishers through select summaries with attribution and enhanced links to the original articles, giving users the ability to access additional information or related articles from their news sites.”

There are additional deals with other groups like The Financial Times which also stress that this deal will result in a new ChatGPT feature that will allow users to interact with real-time news and current events .

OpenAI’s Monday May 13 Announcement

There are many clues that the announcement on Monday will be that ChatGPT users will gain the ability to interact with content about current events.  This fits into the terms of recent deals with news media organizations. There may be other features announced as well but this part is something that there are many clues pointing to.

Watch Altman’s interview at Stanford University

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Featured Image by Shutterstock/photosince

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