ChatGPT for SEO and Sentiment Analysis

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This article is an excerpt from the book, Modern Generative AI with ChatGPT and OpenAI Models, by Valentina Alto. Master core data architecture design concepts and Azure Data & AI services to gain a cloud data and AI architect’s perspective to developing end-to-end solutions.

Introduction

In the ever-evolving landscape of digital marketing, the emergence of AI-powered tools has redefined the way businesses engage with their audience. At the forefront of this transformation is ChatGPT, a versatile language model that is proving to be a game changer in two critical domains: Search Engine Optimization (SEO) and Sentiment Analysis. In this article, we embark on a journey to explore how ChatGPT is revolutionizing SEO strategies, enabling businesses to soar in search rankings, and how it wields its prowess in sentiment analysis to decipher customer feedback and enhance product quality.

Boosting Search Engine Optimization (SEO)

Another promising area for ChatGPT to be a game changer is Search Engine Optimization (SEO). This is the key element behind ranking in search engines such as Google or Bing and it determines whether your websites will be visible to users who are looking for what you promote.

Definition

SEO is a technique used to enhance the visibility and ranking of a website on search engine results pages (SERPs). It is done by optimizing the website or web page to increase the amount and quality of organic (unpaid) traffic from search engines. The purpose of SEO is to attract more targeted visitors to the website by optimizing it for specific keywords or phrases.

Imagine you run an e-commerce company called Hat&Gloves, which only sells, as you might have guessed, hats and gloves. You are now creating your e-commerce website and want to optimize its ranking. Let’s ask ChatGPT to list some relevant keywords to embed in our website:

Figure 7.18 – Example of SEO keywords generated by ChatGPT

As you can see, ChatGPT was able to create a list of keywords of different kinds. Some of them are pretty intuitive, such as Hats and Gloves. Others are related, with an indirect link. For example, Gift ideas are not necessarily related to my e-commerce business, however, it could be very smart to include it in my keywords, so that I can widen my audience.

Another key element of SEO is search engine intent. Search engine intent, also known as user intent, refers to the underlying purpose or goal of a specific search query made by a user in a search engine. Understanding search engine intent is important because it helps businesses and marketers create more targeted and effective content and marketing strategies that align with the searcher’s needs and expectations.

There are generally four types of search engine intent:

• Informational intent: The user is looking for information on a particular topic or question, such as What is the capital of France? or How to make a pizza at home.
• Navigational intent: The user is looking for a specific website or web page, such as Facebook login or Amazon.com.
•  Commercial intent: The user is looking to buy a product or service, but may not have made a final decision yet. Examples of commercial intent searches include best laptop under $1000 or discount shoes online.
• Transactional intent: The user has a specific goal to complete a transaction, which might refer to physical purchases or subscribing to services. Examples of transactional intent could be buy iPhone 13 or sign up for a gym membership.

By understanding the intent behind specific search queries, businesses, and marketers can create more targeted and effective content that meets the needs and expectations of their target audience. This can lead to higher search engine rankings, more traffic, and ultimately, more conversions and revenue.

Now, the question is, will ChatGPT be able to determine the intent of a given request? Before answering, it is worth noticing that the activity of inferring the intent of a given prompt is the core business of Large Language Models (LLMs), including GPT. So, for sure, ChatGPT is able to capture prompts’ intents.

The added value here is that we want to see whether ChatGPT is able to determine the intent in a precise domain with a precise taxonomy, that is, the one of marketing. That is the reason why prompt design is once again pivotal in guiding ChatGPT in the right direction.

                                                                      Figure 7.19 – Example of keywords clustered by user intent by ChatGPT

Finally, we could also go further and leverage once more the Act as… hack, which we already mentioned in Chapter 4. It would be very interesting indeed to understand how to optimize our website so that it reaches as many users as possible. In marketing, this analysis is called an SEO audit. An SEO audit is an evaluation of a website’s SEO performance and potential areas for improvement. An SEO audit is typically conducted by SEO experts, web developers, or marketers, and involves a comprehensive analysis of a website’s technical infrastructure, content, and backlink profile.

During an SEO audit, the auditor will typically use a range of tools and techniques to identify areas of improvement, such as keyword analysis, website speed analysis, website architecture analysis, and content analysis. The auditor will then generate a report outlining the key issues, opportunities for improvement, and recommended actions to address them.

Let’s ask ChatGPT to act as an SEO expert and instruct us on what an SEO audit report should look like and which metrics and KPIs should include:

We can also ask you to give us an example of one of ChatGPT’s suggestions as follows:

Figure 7.20 – Example of ChatGPT acting as an SEO expert

ChatGPT was able to generate a pretty accurate analysis, with relevant comments and suggestions. Overall, ChatGPT has interesting potential for SEO-related activities, and it can be a good tool whether you are building your website from scratch or you want to improve existing ones.

Sentiment analysis to improve quality and increase customer satisfaction

Sentiment analysis is a technique used in marketing to analyze and interpret the emotions and opinions expressed by customers toward a brand, product, or service. It involves the use of natural language processing (NLP) and machine learning (ML) algorithms to identify and classify the sentiment of textual data such as social media posts, customer reviews, and feedback surveys.

By performing sentiment analysis, marketers can gain insights into customer perceptions of their brand, identify areas for improvement, and make data-driven decisions to optimize their marketing strategies. For example, they can track the sentiment of customer reviews to identify which products or services are receiving positive or negative feedback and adjust their marketing messaging accordingly.

Overall, sentiment analysis is a valuable tool for marketers to understand customer sentiment, gauge customer satisfaction, and develop effective marketing campaigns that resonate with their target audience.

Sentiment analysis has been around for a while, so you might be wondering what ChatGPT could bring as added value. Well, besides the accuracy of the analysis (it being the most powerful model on the market right now), ChatGPT differentiates itself from other sentiment analysis tools since it is artificial general intelligence (AGI).

This means that when we use ChatGPT for sentiment analysis, we are not using one of its specific APIs for that task: the core idea behind ChatGPT and OpenAI models is that they can assist the user in many general tasks at once, interacting with a task and changing the scope of the analysis according to the user’s request.

So, for sure, ChatGPT is able to capture the sentiment of a given text, such as a Twitter post or a product review. However, ChatGPT can also go further and assist in identifying specific aspects of a product or brand that are positively or negatively impacting the sentiment. For example, if customers consistently mention a particular feature of a product in a negative way, ChatGPT can highlight that feature as an area for improvement. Or, ChatGPT might be asked to generate a response to a particularly delicate review, keeping in mind the sentiment of the review and using it as context for the response. Again, it can generate reports that summarize all the negative and positive elements found in reviews or comments and cluster them into categories.

Let’s consider the following example. A customer has recently purchased a pair of shoes from my e-commerce company, RunFast, and left the following review:

I recently purchased the RunFast Prodigy shoes and have mixed feelings about them. On one hand, the shoes are incredibly comfortable and provide great support for my feet during my daily runs. The cushioning is top-notch and my feet feel less fatigued after my runs than with my previous shoes. Additionally, the design is visually appealing and I received several compliments on them.

However, on the other hand, I’ve experienced some durability issues with these shoes. The outsole seems to wear down rather quickly and the upper material, while breathable, is showing signs of wear after only a few weeks of use. This is disappointing, considering the high price point of the shoes.

Overall, while I love the comfort and design of the RunFast Prodigy shoes, I’m hesitant to recommend them due to the durability issues I’ve experienced.

Let’s ask ChatGPT to capture the sentiment of this review:

Figure 7.21 – ChatGPT analyzing a customer review

From the preceding figure, we can see how ChatGPT didn’t limit itself to providing a label: it also explained both the positive and negative elements characterizing the review, which has a mixed feeling and hence can be labeled as neutral overall.

Let’s try to go deeper into that and ask some suggestions about improving the product:

Figure 7.22 – Suggestions on how to improve my product based on customer feedback

Finally, let’s generate a response to the customer, showing that we, as a company, do care about customers’ feedback and want to improve our products.

Figure 7.23 – Response generated by ChatGPT

The example we saw was a very simple one with just one review. Now imagine we have tons of reviews, as well as diverse sales channels where we receive feedback. Imagine the power of tools such as ChatGPT and OpenAI models, which are able to analyze and integrate all of that information and identify the pluses and minuses of your products, as well as capturing customer trends and shopping habits. Additionally, for customer care and retention, we could also automate review responses using the writing style we prefer. In fact, by tailoring your chatbot’s language and tone to meet the specific needs and expectations of your customers, you can create a more engaging and effective customer experience.

Here are some examples:

• Empathetic chatbot: A chatbot that uses an empathetic tone and language to interact with customers who may be experiencing a problem or need help with a sensitive issue
• Professional chatbot: A chatbot that uses a professional tone and language to interact with customers who may be looking for specific information or need help with a technical issue
• Conversational chatbot: A chatbot that uses a casual and friendly tone to interact with customers who may be looking for a personalized experience or have a more general inquiry
• Humorous chatbot: A chatbot that uses humor and witty language to interact with customers who may be looking for a light-hearted experience or to diffuse a tense situation
• Educational chatbot: A chatbot that uses a teaching style of communication to interact with customers who may be looking to learn more about a product or service

In conclusion, ChatGPT can be a powerful tool for businesses to conduct sentiment analysis, improve their quality, and retain their customers. With its advanced natural language processing capabilities, ChatGPT can accurately analyze customer feedback and reviews in real-time, providing businesses with valuable insights into customer sentiment and preferences. By using ChatGPT as part of their customer experience strategy, businesses can quickly identify any issues that may be negatively impacting customer satisfaction and take corrective action. Not only can this help businesses improve their quality but it can also increase customer loyalty and retention.

Conclusion

In this article, we learned to enhance SEO analysis, and capture the sentiment of reviews, social media posts, and other customer feedback.

As ChatGPT continues to advance and evolve, it is likely that we will see even more involvement in the marketing industry, especially in the way companies engage with their customers. In fact, relying heavily on AI allows companies to gain deeper insights into customer behavior and preferences.

The key takeaway for marketers is to embrace these changes and adapt to the new reality of AI-powered marketing in order to stay ahead of the competition and meet the needs of their customers.

Author Bio

Valentina Alto graduated in 2021 in data science. Since 2020, she has been working at Microsoft as an Azure solution specialist, and since 2022, she has been focusing on data and AI workloads within the manufacturing and pharmaceutical industry. She has been working closely with system integrators on customer projects to deploy cloud architecture with a focus on modern data platforms, data mesh frameworks, IoT and real-time analytics, Azure Machine Learning, Azure Cognitive Services (including Azure OpenAI Service), and Power BI for dashboarding. Since commencing her academic journey, she has been writing tech articles on statistics, machine learning, deep learning, and AI in various publications and has authored a book on the fundamentals of machine learning with Python.