Last week, I attended Google’s Paris livestream and was hit with an existential question: what happens when search and AI collide? To find out, I turned to Google and Microsoft’s latest AI-powered search technologies, Bard and Bing respectively.

The only problem? Bard is exclusively available to the cool kids club of “trusted” testers, and I’m stuck in waitlist limbo for Bing. But hold the phone, because I managed to score a one-on-one with the legendary ChatGPT from OpenAI – the OG of the Search Wars.

Our chat didn’t always go smoothly, with some downright ugly moments where I had to call out ChatGPT on their BS. But it was a beautiful night, and in the end we agreed that delivering personalized answers based on user intent and context is the key to success in the new age of AI-driven search.

Want to know more? Keep reading for the full lowdown, folks.

How will SEO be impacted by AI-powered search platforms such as Bing?

The integration of AI into search platforms is expected to have a significant impact on SEO (Search Engine Optimization). With AI-powered search algorithms, the focus is shifting from keyword-based optimization to a more comprehensive approach that takes into account the user’s intent, context, and overall search experience.

AI-powered search algorithms:

  1. Place a greater emphasis on providing a positive user experience, which means that websites that offer a good user experience are likely to rank higher in the search results.
  2. Are designed to provide more relevant results, which means that websites that offer relevant content and information are likely to rank higher.
  3. Are more likely to rank websites with high-quality, original, and informative content higher in the search results.
  4. Are designed to understand the intent behind search queries and provide results that match the user’s intent. This means that websites that use natural language and provide clear, concise, and relevant information are likely to rank higher.

What can I do to improve my AI-powered search performance as Bing takes into account a user’s intent, context, and overall search experience?

  1. Make sure your website is easy to navigate, has a clear structure, and provides relevant and high-quality content. This will help improve the overall user experience and increase the likelihood your website will rank higher in the search results.
  2. Make sure your content is relevant to the search queries you want to rank for. Use keywords that accurately reflect the content on your website and make sure your content is informative, accurate, and up-to-date.
  3. Make sure your content is original and high-quality. This will increase the likelihood your website will provide a better user experience and rank higher in the search results.
  4. Make sure your content is written in natural language that is easy to understand. Use clear, concise, and informative language, and avoid using technical jargon or overly complex sentences.
  5. Consider optimizing your website for voice search, as an increasing number of users are using voice-activated devices to search for information online.
  6. Regularly monitor your website’s performance on AI-powered search platforms, and make any necessary changes to improve your ranking in the search results.

Name current SEO strategies that will no longer be relevant with AI-powered search engines such as Bing.

As AI-powered search engines such as Bing become more sophisticated, certain traditional SEO strategies are becoming less relevant.

AI-powered search engines are designed to:

  1. Understand the context and intent behind search queries, so the use of keyword stuffing, where keywords are repeated multiple times in a piece of content, is likely to become less relevant.
  2. Understand the quality and relevance of websites, so the use of link building techniques, such as buying links or participating in link schemes, is likely to become less relevant.
  3. Understand the content on a website, so the excessive use of meta tags, such as meta keywords and meta descriptions, is likely to become less relevant.
  4. Understand the uniqueness and originality of content, so the use of duplicate content is likely to become less relevant.
  5. Understand the structure and content of websites, so the use of hidden text and links is likely to become less relevant.

Everything you mentioned in the previous response are tactics that are already outdated.

My apologies! You are correct, the strategies I mentioned in the previous response are outdated and no longer considered best practices in modern SEO. I apologize for the confusion and any misinformation provided.

Apology accepted. Please go on…

In modern SEO, the focus is on creating high-quality, relevant, and valuable content that provides a positive user experience. Other important factors include a strong website structure, optimized images and videos, and the effective use of structured data and schema markup.

Additionally, building a strong online presence through social media, link building, and local search optimization is also considered important for modern SEO. Modern SEO is about creating a comprehensive and integrated digital presence that provides value to users and is optimized for search engines.

Lastly, it is important to stay up-to-date with the latest best practices and advancements in SEO to ensure that your website continues to rank well.

It sounds like SEO best practices won’t change much with the rise of AI-powered search.

You are correct, the core principles of SEO are unlikely to change with the rise of AI-powered search engines such as Bing. The focus on providing relevant and high-quality content, a positive user experience, and a strong online presence will continue to be important for SEO success.

However, the implementation of these principles may change as AI-powered search engines become more sophisticated and able to better understand the intent behind search queries, the context of a search, and the overall user experience.

As a result, SEO strategies will need to evolve to keep up with these advancements in AI-powered search.

For example, SEO strategies may need to place a greater emphasis on natural language processing and structured data, as AI-powered search engines become better at understanding the context and intent behind search queries.

Additionally, SEO strategies may need to focus on providing a more personalized user experience, as AI-powered search engines become better at understanding the individual needs and preferences of users.

Explain search intent, search context, and the overall user experience in more detail.

  1. Search intent refers to the purpose behind a search query. It is the reason why someone is searching for a particular piece of information, product, or service. Understanding the search intent behind a query is critical for providing relevant and accurate results.
  2. Search context refers to the context in which a search query is being made. It includes factors such as the location, time, and device being used, as well as the user’s previous search history and other contextual clues. Understanding the context in which a search query is being made is important for providing relevant results that match the user’s needs and preferences.
  3. The overall user experience refers to the quality and ease of use of a website or application. This includes factors such as the website’s design, navigation, and content, as well as the speed and reliability of the website. A positive user experience is important for improving the visibility of a website in the search results and increasing engagement and conversions.

By understanding the intent behind search queries, the context in which they are being made, and the overall user experience, you can improve the visibility of your websites in the search results and provide a better user experience.

The concepts of search intent, search context, and the overall user experience are becoming increasingly important with the rise of AI-powered search engines.

Give me ten examples of different search intent.

  1. Navigational: The user is searching for a specific website or web page, such as “Facebook login.”
  2. Informational: The user is looking for information on a specific topic, such as “What is the capital of France?”
  3. Transactional: The user is looking to make a purchase, such as “Buy Nike shoes online.”
  4. Commercial investigation: The user is researching a product or service with the intention of making a purchase, such as “Best camera for vlogging.”
  5. Local: The user is searching for a local business or service, such as “Pizza restaurants near me.”
  6. Navigational with local intent: The user is searching for a specific website or web page with a local focus, such as “Starbucks locations near me.”
  7. Question answering: The user is searching for an answer to a specific question, such as “What is the population of India?”
  8. Comparison: The user is searching to compare products or services, such as “iPhone vs Samsung.”
  9. Image search: The user is searching for images related to a specific topic, such as “Cute cat pictures.”
  10. Video search: The user is searching for videos related to a specific topic, such as “How to make sushi.

These are just a few examples of the many different types of search intent that exist. Understanding the intent behind a search query is critical for providing relevant and accurate results and improving the visibility of a website in the search results.

You mentioned search context includes factors such as the location, time, and device being used, as well as the user’s previous search history and other contextual clues. Give me examples of “other contextual clues.”

Sure! Here are some examples of “other contextual clues” that are included in search context:

  1. Language: The language in which the search query is made can provide important contextual information about the user’s location, culture, and background.
  2. Personalization: The user’s personal preferences and search history can provide important contextual information about the user’s needs and interests.
  3. Seasonality: The time of year and current events can provide important contextual information about the user’s needs and interests. For example, searches for “beach vacations” might be more common in the summer, while searches for “ski resorts” might be more common in the winter.
  4. User behavior: The user’s behavior, such as the websites they have visited and the pages they have clicked on, can provide important contextual information about the user’s needs and interests.
  5. Device type: The type of device being used can provide important contextual information about the user’s location, preferences, and behavior. For example, searches made on a mobile device might be more focused on local results and immediate actions, while searches made on a desktop computer might be more focused on research and planning.
  6. Social media: The user’s social media activity, such as posts and shares, can provide important contextual information about the user’s interests and preferences.

These are just a few examples of the many different contextual clues that can provide important information about the user’s needs and preferences. Understanding these contextual clues is critical for providing relevant and accurate results and improving the visibility of a website in search results.

How will AI help search engines such as Bing get better at discerning search intent, search context, and the overall user experience?

AI can help search engines such as Bing get better at discerning search intent, search context, and the overall user experience in several ways.

AI-powered search engines:

  1. Use natural language processing (NLP) algorithms to understand the intent behind search queries and provide results that match the user’s intent. NLP algorithms can analyze the words used in a search query, as well as the context in which the query was made, to determine the user’s intent.
  2. Use machine learning algorithms to learn from and improve upon past search results. By analyzing large amounts of data, machine learning algorithms can identify patterns and trends in user behavior, allowing search engines to better understand the context in which a search query is being made and provide more relevant results.
  3. Use machine learning algorithms to personalize search results based on a user’s previous search history, location, device, and other factors. This allows search engines to provide a more personalized user experience and improve the relevance of the search results.
  4. Can use structured data, such as schema markup, to better understand the content on a website and provide more accurate results. Structured data can provide important information about a website’s content, such as the type of content, the author, and the date it was published, allowing search engines to provide more relevant results.

That’s it for now. Thank you. I’m sure will talk again soon.

I look forward to it!