ChatGPT: how can a neural network be used in the work of an SEO specialist

ChatGPT is an extremely powerful text neural network that became available to the world community more than 2 years ago. Despite the fact that during this period of time dozens of alternatives have appeared, endowed with their own specifics, features, and distinctive features, the relevance of this chatbot remains at a consistently high level. Moreover, it continues to develop, gaining new functional capabilities. It is convenient that you can use the basic version even without creating an account, but if you are interested in deeper and more professional capabilities, then you will need to pay attention to one of the paid versions: Plus or Pro.

Among the main functional capabilities and operating modes of ChatGPT, it is worth highlighting the analysis of documents, images, generation of texts and pictures, the ability to reason, continuous voice mode, almost indistinguishable from a regular live conversation, code execution and much more. Moreover, today it is possible to create customized versions of ChatGPT, tailored to solve specific problems. All these features make this tool attractive to a wide segment of users, including those who conduct professional activities on the Internet. Among other things, this neural network will be useful for SEO specialists.

In today's review, we will dwell in detail on what functional capabilities of the AI service can be used to promote a site and attract a new audience to its pages. We will tell you how the paid and free versions of the neural network differ, and also highlight the difference between GPT-3 and GPT-4o. We will talk about the limitations of the functionality and what prompting techniques can be used today when working with this neural network. We will talk in detail about what SEO tasks ChatGPT can be used to solve. Let's get acquainted with useful extensions for this neural network and make a brief overview of the nearest alternatives worthy of attention.

Paid and free version of ChatGPT: main differences

Despite the high popularity and advancement of the free version of ChatGPT, in professional activities, experts still recommend using the paid analogue. The fact is that with its help you can solve much more important problems, in particular:

• Fast and efficient processing of large data arrays. You can simply attach all the files that you would like to send for analysis to your request. There are no special requirements here, the main thing is that the format corresponds to the one that the bot can process, namely PNG, CSV, JPG, DOCX, XLS, PDF.
• The ability to generate high-quality and accurate images based on the description. It is also possible to process the received images directly in the built-in editor.
• Creating personal GPT assistants for various tasks. This solution will be very convenient for various businesses, as it allows you to take into account their specifics and individuality. In particular, you can teach them how to directly write and edit code, develop scripts for computer games, and more. In this case, the training process for such assistants will be carried out based on the existing database, personal knowledge of specialists, books, etc. It is noteworthy that no special knowledge and skills in the field of programming are required here.
• The ability to remember the context of dialogues even when they are transferred to new chats. This is a kind of "bot memory". That is, you will only need to write down once everything that you would like to say about your company, explain what answers you expect from the neural network, and then ChatGPT will use the received data in other answers.

If we talk about the free version, then with its help you will not be able to generate images, create your personal GPT assistants. But with such tasks as processing large data arrays, generating texts, automatically recording information into memory, as well as using already created GPT assistants, you can use it.

Common and differences in versions GPT-3 and GPT-4o

Before you start working with ChatGPT, it is important to decide on the language version that you will use in your work, namely GPT-3 or GPT-4o. Both of these products are developed by OpenAI. GPT-3 was released to the market at the end of May 2020, while GPT-4o appeared on the market almost 4 years later. Thus, GPT-4o (omni) can work not only with text content, but also process voice commands, graphic materials. Alternatively, with its help you can analyze photos, get a fairly high-quality translation of the text, as well as recommendations for its improvement.

Moreover, specialists who tested both versions of ChatGPT note the higher speed and efficiency of GPT-4o. But there are limitations for the free version of the neural network. In particular, you can send no more than 10 requests daily. After this limit is exhausted, the system will automatically redirect you to the stripped-down version of GPT-4o mini. In principle, it will also provide you with relevant answers, but the quality of its work with complex queries leaves much to be desired.

To make the difference between GPT-3 and GPT-4o more clear, let's consider a few more differences:

1. GPT-3 is not able to provide up-to-date information about the latest events, news, since it does not have direct access to the Internet. In its work, it uses only the data that was embedded in it at the machine learning stage. GPT-4o already provides for integration with the Internet, which significantly increases the correctness of the provided answers to queries, including those related to current events.
2. GPT-3 is quite poorly oriented in context. In order for you to be able to get a more or less intelligible answer, you will need to ask very clear prompts containing a lot of detail. GPT-4o also shows itself better in working with detailed queries and task descriptions, but still, deep detailing is not required here.
3. In GPT-3, the reliability of responses to your requests is highly questionable. In practice, it has repeatedly turned out that the information provided does not correspond to reality even with an elementary check. The accuracy of GPT-4o responses turns out to be higher, but still, experts do not recommend relying entirely on it. That is, it would still be optimal to double-check the received data through third-party sources.

The most suitable version of ChatGPT for your work should be chosen depending on what tasks you set for yourself. But even from this brief comparison it is clear that version 4 will still be more accurate and reliable to use.

What are the limitations in the functionality of ChatGPT today?

The limitations in the operation of ChatGPT in terms of using this neural network in SEO optimization were quite significant until the release of the latest updated version at the end of last fall. But now, if we do not nitpick too much, then in the free versions of GPT-3 and GPT-4o it is worth highlighting only 2 key points:

1. The neural network is capable of remembering only a limited amount of information within one session. That is, you will not be able to process large volumes of information, long articles and multi-layered tasks with its help.
2. There is no direct access to specialized SEO tools. First of all, I would like to highlight such software solutions as Serpstat and Ahrefs, which are widely used by specialists to check the frequency of key queries. So, you will not be able to access them through ChatGPT directly.

Whether these shortcomings will be so significant in practice is up to the specialists working with this tool in practice. But they can be minimized if you do not rely entirely on the neural network, but additionally check the information, take into account your own knowledge, practical experience. And another very important point can be the presence of certain knowledge in such a field as prompt engineering. We will talk about this in more detail.

What is prompt engineering

Prompt engineering is a direction closely related to ChatGPT and neural networks in general. It involves the development of queries by relevant specialists, which will be sent for subsequent processing by the neural network in order to obtain useful and relevant answers. The quality and completeness of the answers received directly depend on how well these works are implemented. In order to perform such work efficiently, you do not need to have deep knowledge in this niche. It will be enough to simply use a number of techniques when forming queries for ChatGPT.

In particular, to write a high-quality prompt, it is recommended:

• Be as specific as possible. Try to avoid vague, incomprehensible phrases, ambiguity. If there are specific details, then they must be specified without fail. The more detailed your prompt is, the more accurate and professional the answer you will receive.
• Don't stop at the first option you come across. In order to get a good result in the end, it is important to try different queries, compare the answers received, and in some cases even compare them with third-party sources. This way, you will be able to understand which prompt helped to get the most correct and accurate result. In the future, you can also use it as a basis.
• Add context to your query, which will help the neural network better understand what you want to get at the output and, accordingly, provide you with the most relevant answers. Imagine that you need to explain something to a child at a moment. Follow this same principle when preparing a query for ChatGPT.
• Be sure to analyze the results. If something does not suit you, if you have identified an inaccuracy, think about how you need to formulate your query again in order to get a more correct answer. You may have to repeat several iterations, but in the end you will still be able to get a result that will meet your expectations.

And now a little about what prompt engineering techniques are used by modern specialists when working with ChatGPT.

Prompt engineering techniques that are relevant today

To understand such an issue as prompt engineering and learn how to create such prompts for neural networks that can give the best results in practice, it is important to understand what methods are used today in this area and which of them give the best results in practice. In particular, here we will highlight the following technologies:

1. Zero/Few-Shot. This technique for creating a prompt involves writing a request without using examples. That is, in this case, we have neither input nor output data on the basis of which the model should be trained. In practice, they are used in cases where an existing model is capable of independently solving such a problem or, based on the instructions themselves, the neural network can determine what exactly they want to get from it at the output. It is also suitable in cases where specifying examples can force the model into too narrow a framework, when it is not possible to provide an example for each of the cases.
2. Few-shot. This technology already assumes feeding a request with examples. That is, here, on specific cases, input or output data, the motel is trained. It is used in cases where we do not have instructions with a clear description or you want to get an answer that will differ from the generally accepted one. But in this case, you must understand that all this information that you have at your disposal can be used to train ChatGPT, that is, it is reliable and complete.
3. Role based. The basis of such a prompt will be a description of a certain role or a point of view for the model. It is worth using in practice when you want to get answers containing a certain perspective. Alternatively, you can ask the neural network to describe how it sees the danger of global warming from an environmental or economic perspective. As a result, you can get a fairly relevant context. But in any case, it is very important to test your request on different roles, and then make the most correct choice based on one of the results obtained.
4. Chain-Of-Thought. This request involves step-by-step processing by a neural network. As a result, you can get a solution that will be quite similar to real human reasoning. They will contain conclusions, a consistent presentation of thoughts. That is, each new step will be processed based on the information that was obtained at the previous stage. Thanks to this breakdown, you will be able to see at what stage ChatGPT began to deviate from reality and will be able to return the reasoning to the right track through additional clarifications and questions. This solution will be especially relevant when working with complex multi-level tasks.
5. Chain-of-Verification. This technique for writing a prompt involves constantly returning the model to previous steps for their additional verification before taking a new action. This is a kind of extension of the previous version, increasing the quality and reliability of the final result. That is, if the neural network comes to a false answer as a result of its reflections, it will be able to go back a few steps and understand at what stage the mistake was made and correct it.
6. Chain-of-Note. In the case of such a technology, when solving a particular problem, the model will leave a kind of "notes". If, in the course of further reasoning, the neural network makes conclusions that contradict each other, it will not be able to give a high-quality answer. If it constantly records its thoughts, namely key aspects, then it will be able to rely on them in the future and not make any mistakes. Figuratively speaking, if you indicate in such a note that the apple is green, then all further reasoning, such as about the usefulness of the product, the neural network will conduct with reference to the green, and not to the red or yellow apple.
7. Chain-of-Knowledge. In this case, when preparing a response to a new request, the neural network will already use the knowledge that it managed to obtain at the previous stages. Unlike Chain-Of-Thought, the model will not make any conclusions on its own. It simply relies on known facts, building a consistent chain of reasoning on their basis, which will ultimately lead to the formation of a certain answer. Alternatively, the neural network is unlikely to be able to derive its own theorem, but it is quite capable of solving a geometry problem based on certain formulas and proven knowledge. And here there will be no distortions of reality, no guesswork.

In most cases, to solve a particular SEO task, it is worth choosing a format for the prompt that will be most effective in a particular case. There are no universal solutions that will work equally well when working with different issues.

Now let's move directly to getting acquainted with the tasks that can be solved during SEO optimization of the site using ChatGPT.

TOP SEO optimization tasks that ChatGPT will help solve

Many of us are used to using ChatGPT to generate text, images, article titles, descriptions for online store categories and individual products. But this is not the end of the functionality of this neural network. They are much broader, although not everyone knows about it. In particular, an SEO specialist can use ChatGPT to solve such related tasks as:

1. Selecting synonyms for keywords and queries.
2. Developing a content plan for filling a blog.
3. Generating micro-markup.
4. Adding regular expressions and formulas in Google Sheets
5. Creating a block with the most common questions and answers.

Let's consider all these tasks in more detail.

Selecting synonyms for keywords and queries

If you have already collected a semantic core, but understand that it turned out to be too limited, insufficient for the implementation of your SEO optimization strategy, you can turn to ChatGPT for help. In practice, a lack of keywords is very often observed when working with foreign content or in a fairly narrow topic. In this case, the neural network will offer you additional keywords that you can add to your content. Alternatively, when working with text in a foreign language, AI can offer you more natural expressions and synonyms, in the case of technical materials - phrases that are used in this segment by specialists and are little known to people far from this issue.

But here you must understand that the neural network will not have direct access to real information about the frequency of requests. And this means that you will need to additionally run all the generated keywords, synonyms through specialized services, such as the same Serpstat or Ahrefs. Only in this way will you be able to assess the popularity of phrases among the consumer audience and decide on the advisability of adding them to the content.

Developing a content plan for filling a blog

If you have worked with ChatGPT before, you probably know how well it can generate ideas for future articles and create content clusters. Try using these features to develop a content plan for filling a blog, select new topics that will be relevant for the current period of time and will interest the audience. Alternatively, using a neural network, you can:

• Generate clusters by topic. AI can offer you several subtopics that are interconnected and allow you to fully cover a topical issue. That is, this way you can fully cover your main topic and explain all its nuances to the target audience.
• Think through internal linking as effectively as possible, based on the clusters already developed. This way, you can guide your audience from one question to another, and you can explain the overall structure of your content to the search engine in more detail.
• Segment your blog articles by level of complexity, from the simplest to the deep, expert ones. This will make your content relevant to all blog readers: those who are just starting to get acquainted with the topic and those who are already quite deeply immersed in it.
• Suggest a content publishing sequence that allows you to systematically immerse yourself in your topic. The so-called content funnel will help increase conversion.
• Suggest original content formats that can diversify your blog posts, which, among other things, will also help retain the audience's attention. Alternatively, along with classic articles, you can sometimes add longer reviews, videos, infographics, etc.
• If you work with seasonal products, then ChatGPT can offer you so-called seasonal planning, which involves taking into account current trends or events during this period of time.

With such help, you can simplify the upcoming work, delegate the solution of problems related to the processing of large amounts of data to AI. Moreover, you can ask ChatGPT to develop a detailed technical task for the subsequent writing of texts on each of the proposed topics. This will also significantly save your time and effort.

Generating micro-markup

Those who have already encountered the development of micro-markup in practice probably know how difficult this process is to implement. This is especially true for non-standard, complex tasks. But now you can delegate their solution to ChatGPT. AI will literally generate a micro-markup template for you in a few seconds, which will contain all the main elements. It will also indicate what information should be contained in a particular field, which will ultimately greatly simplify filling out the document and the subsequent work of the SEO specialist in general.

In order to get an excellent result in practice, it is important to consider the following recommendations when working with a neural network:

• provide maximum information about your request: the more details ChatGPT knows, the more nuances it will take into account and, accordingly, less revision will be required in the future;
• when writing a prompt, use the Chain-Of-Thought technique, that is, a model with step-by-step processing, making adjustments and clarifying data at each step;
• experiment with the wording of your request, analyze the results obtained, as this is the easiest way to get an accurate result at the output.

But here you must understand that the resulting micro-markup is — this is just a basis, not a finished result. You will need to carefully double-check everything, make revisions and adapt it to the task. It will also not be superfluous to check the quality of the finished micro-markup through specialized services before implementing it on the site. This will allow you to minimize subsequent adjustments.

Adding Regular Expressions and Formulas to Google Sheets

Excel has a set of basic functions that involve working with text and formulas. This also applies to Google Sheets, because the basis of both platforms is identical. In their work, SEO specialists often encounter the need to use regular expressions - patterns that allow you to search for text based on them. We will not go too deep into the theory, but let us note that ChatGPT can significantly simplify this work. Let's say you have a Google Sheet containing a set of URLs. At the moment, you are faced with the task of selecting those that contain https in the name. Doing this work manually would take quite a long time, although there is nothing complicated about it. But a neural network will solve this problem in literally a matter of seconds. That is, you need to write a prompt indicating that you are interested in all URLs containing https in the name and attach the document itself.

Additionally, you can ask to consider the IF parameter to get customized answers "Safe" or "Dangerous". If you do not use this function, then in the final table you will see the standard value "True" or "False". A similar action can also be performed in relation to the search for formulas. Only here we want to draw your attention to the fact that ChatGPT often uses a comma as a separator. That is, you will most likely have to replace it with a semicolon for more correct display.

Creating a block with the most common questions and answers to them

The vast majority of sites will keep a section such as FAQ, adding to it the most common questions among the user audience and, accordingly, competent answers to them. Such a block will help expand the semantic core and show that you adhere to the EEAT principle when preparing content. You can also entrust this work to ChatGPT. In practice, this will work in the following sequence:

• You set the neural network a topic and key queries. Based on the information received, the AI will generate relevant questions.
• Relevant answers are generated taking into account the specifics of the topic, as well as keywords and additional LSI queries.
• The received answers are adapted to the characteristics of the target audience and the voice of the brand.
• The resulting block structure is checked to ensure good user experience indicators, as well as the convenience of future indexing by search bots.
• Generating micro-markup in accordance with the previously specified formats. Let us repeat that you will ultimately need to additionally check it in the validator before adding it to the site.

You can increase the information content of this block if you use information collected using Google Search Console and Google Analytics as the initial data, and also provide for the breakdown of questions into thematic groups. We would also like to draw your attention to the fact that the FAQ block on your site is not a permanent phenomenon. You will need to regularly review the questions here and make adjustments based on changing trends and user behavior.

What ChatGPT extensions can SEO specialists use in practice

Despite the fact that the basic version of the neural network itself is a fairly powerful and advanced tool, its functionality in most cases may not be enough to solve the problems facing specialists at the stage of website promotion. This situation can be corrected in a fairly simple way, namely by using special extensions. Today, there are quite a lot of such tools, but we would like to dwell in more detail on the three most common options:

1. GPT for Sheets. You can integrate such a tool directly into Google Sheets in order to generate text directly in the cells of automatic filling of empty blocks based on the context, as well as analysis of the contained data and formation of formulas. It is worth using this extension in cases when you are faced with processing large amounts of data, for example, during the optimization of meta tags for a large number of pages, generation of text content, etc. But here you need to monitor the number of tokens that will be required to process the text. ChatGPT has its own standardization depending on the language in which the work is carried out. As an option, the cheapest solution is English, where the first word will be approximately equal to 1.3 tokens. If you prepare content in Russian, then here you will have to pay about 3.3 tokens for 1 word. The most expensive option is Hindi, because for the generation of 1 word here the system will withdraw about 6.4 tokens from your account.
2. AIPRM Extention. This is an extension containing a set of ready-made projects for solving various problems. In particular, here you can find a library of ready-made queries for classic SEO tasks, you can choose one of the most suitable languages for yourself from more than 100 available options (there are, among others, quite specialized, rare ones). Also, you can not only create, but also save your prompts, categorize them for faster search in the future. The tone of the response can be set to emotional or standard, additional sorting by date added, popularity rating can be provided. Also here you can select the AI model: GPT-3 or GPT-4o. There are also several possible tariff plans that differ in functionality and price.
3. WebPilot Extension. Thanks to this tool, the neural network will interact with Internet pages in real time, and will also be able to extract deep data. In practice, this solution turns out to be optimal for the most detailed data collection, as well as the generation of text content based on the collected information. This extension is available to users in both free and paid versions, which will differ in the set of options. If you are interested in advanced search, then it is better to choose a paid product.

In most cases, free versions of such extensions will be enough for you to evaluate the efficiency and convenience of software products and, as a result, make the most appropriate decision on the need to use them in practice.

Neural networks that can become a worthy analogue of ChatGPT

Yes, ChatGPT can rightfully be called a pioneer in the field of artificial intelligence. But this is far from the only solution that can be used in practice in the process of SEO optimization of a site. In the modern market, more than enough alternative AI tools are presented to buyers. I would like to draw special attention to the following solutions:

• Claude.Ai. The neural network appeared on the market about 2 years ago. It is capable of processing data in real time, providing users with up-to-date information. It has high analytical capabilities and accuracy in technical and scientific topics. But the situation with solving creative problems is somewhat worse.
• Gemini. This is an AI model developed by Google and appeared on the market at the end of 2023. It has high integration rates with other company products and is available as part of a Google One AI Premium subscription. You can use this tool for free for 2 months, and then you will need to pay about $20 for each month of use. It has good performance in processing text and graphic content. The disadvantages include the high cost of the subscription.
• Copilot. This is an AI assistant developed by Microsoft and integrated into Windows 11. You can use it to work with office applications, write code, generate images. One of the most significant advantages is deep integration with the entire Microsoft ecosystem. But the versatility here will be somewhat lower than that of its closest analogues. You will also need a subscription to Microsoft 365 in order to generate text and analyze data.

Perhaps one of these products will interest you and you will decide to use it in your work.

Let's summarize

As you can see, artificial intelligence technologies do not stand still. They are actively developing, affecting more and more new directions, areas. This applies, among other things, to SEO-promotion of sites. With the help of ChatGPT additional extensions and related neural networks, you can make your work as functional, fast, convenient as possible, automate the process of collecting and processing large amounts of data. The volume of tasks that can be solved using AI is quite wide, which each of you can personally evaluate in practice.

But we want to draw your attention to the fact that most of these tools are not available in all regions. Many of them do not work in the Russian Federation. Among other things, this also applies to ChatGPT. But today there is an effective solution to this problem - the use of mobile proxies from the MobileProxy.Space service. With their help, you can choose the most suitable geolocation for yourself, thereby bypassing regional access restrictions. You also guarantee yourself confidential, safe work on the network, which is also very important today. You can learn more about the features of these mobile proxies and find out the current rates at the link https://mobileproxy.space/en/user.html?buyproxy.

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