Another month, and Google releases Anotha One. (And yes, John Mueller is the DJ Khaled of SEO). 

Over the last couple months, one of the most complicated challenges that search engines (especially Google) have been trying to solve is how to deal with AI generated content. This core update addresses that. It’s been a long time coming (tsk tsk September 2023), and it’s long overdue. This will not be the last update in this topic, but it’s a good start. 

This article dives into the August 2024 Google Core Update, the importance of targeting content by user journey stages, the bottleneck (spoiler alert : misaligned incentives for LLM and search providers), and how to create a winning content strategy.

Google’s August 2024 Core Update

On August 15, 2024, Google announced a pivotal update to its core search algorithm, known as the "Helpful Content Update." This update marks a significant shift in Google's approach, emphasizing the importance of user-first content and demoting content created solely for search engine optimization (SEO) purposes. 

John Mueller, Search Advocate at Google, wrote:

“Today, we launched our August 2024 core update to Google Search. This update is designed to continue our work to improve the quality of our search results by showing more content that people find genuinely useful and less content that feels like it was made just to perform well on Search.”

Google said this update aims to promote useful content from small and independent publishers, after Google listened to feedback it received since the release of the March 2024 core update. Mueller added:

“This latest update takes into account the feedback we’ve heard from some creators and others over the past few months. As always, we aim to connect people with a range of high quality sites, including ‘small’ or ‘“’independent’ sites that are creating useful, original content on relevant searches. This is an area we’ll continue to address in future updates.”

This August 2024 core update “aims to better capture improvements that sites may have made, so we can continue to surface the best of the web,” Mueller added.

The Importance of User-First Content

Google's Helpful Content Update is a clear indication of the search giant's commitment to enhancing user experience by prioritizing content that genuinely serves the user's needs. This shift aligns with Google's long-standing E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) guidelines, which emphasize the value of providing relevant, high-quality, and trustworthy information. Let's delve deeper into why user-first content is crucial for both users and businesses.

Building Trust and Credibility

User-first content focuses on delivering value to the audience, which in turn helps build trust and credibility. When users find content that addresses their needs and provides solutions to their problems, they are more likely to trust the source and engage with it. This trust can lead to increased brand loyalty, repeat visits, and ultimately, conversions.

Learning about a product / service from a trusted source / having third party validation has been proven to increase conversion rates, engagement rates, and boost organic growth. This is why UGC, Influencer, and Referral campaigns are almost always used in some way, shape or form by companies across B2B, B2C, D2C, and E-Commerce. It’s time to incorporate the same principles in content production.

Enhancing User Engagement

Content that prioritizes user needs is more likely to engage readers. Engaging content encourages users to spend more time on a website, explore additional pages, and interact with the brand. This increased engagement can lead to lower bounce rates, higher click-through rates, and improved search rankings. There are several ways to increase engagement, but at the core of it lies writing content that targets what the user is trying to solve for right now. This translates to understanding the user’s buying journey, and curating content that supports them across the journey.

Understanding the User's Buying Journey

The buying journey typically consists of three stages: Awareness, Consideration, and Decision. Each stage presents unique opportunities for content creation.

Awareness Stage

At the awareness stage, users are beginning to recognize a need or problem. They are seeking information to better understand their situation and explore potential solutions. Content at this stage should be informative and educational, addressing common pain points and questions. Examples of content for the awareness stage include:

• Blog Posts and Articles: Create in-depth articles that explore common industry challenges and provide insights into potential solutions.

• Infographics: Use visual content to simplify complex topics and make information more accessible.

The awareness stage must target informational intent - the user is searching to learn more, and your content must provide them value and educate them on the topic. Much like this article 😀

Consideration Stage

During the consideration stage, users are evaluating their options and comparing different solutions. They are looking for detailed information to help them make informed decisions. Content at this stage should include detailed comparisons, reviews, and case studies. Examples of content for the consideration stage include:

• Product Comparisons: Create comparison guides that highlight the features, benefits, and drawbacks of different products or services.

• Case Studies: Share success stories that demonstrate how your product or service has helped others achieve their goals.

• Webinars and Live Demos: Offer interactive sessions that allow users to see your product or service in action and ask questions.

This stage is where content must target both informational and commercial / transactional keywords and topics, with an approximately even split. The goal is that you’re educating the user on our product / service, while at the same time giving them light nudges to make a purchasing decision with you.

Decision Stage

At the decision stage, users are ready to make a purchase. They need reassurance and motivation to choose your product or service. Content at this stage should feature clear calls-to-action, testimonials, and offers to facilitate conversions. Examples of content for the decision stage include:

• Testimonials and Reviews: Showcase positive feedback from satisfied customers to build trust and credibility.

• Special Offers and Discounts: Provide incentives to encourage users to make a purchase.

• Clear Calls-to-Action: Use persuasive language and design elements to guide users toward the desired action.

This stage must target commercial and transactional keywords and topics. We know the user wants to buy something, now it’s about closing the loop and enabling them to make the decision.

Conducting PAA and SERP Analysis

To create content that meets user needs and ranks well in search results, it's essential to conduct thorough "People Also Ask" (PAA) and Search Engine Results Page (SERP) analysis. These tools provide valuable insights into user queries and content opportunities.

Understanding "People Also Ask" (PAA)

The "People Also Ask" feature in Google search results provides a list of related questions that users commonly search for. Analyzing PAA boxes can help content creators identify common user queries and tailor their content to address these questions. This approach not only improves content relevance but also enhances visibility in search results.

This is even more important today - Google often creates featured snippets and AI Overviews based on finding exact matches with questions asked, which would put you in Position 0 - before any ad, or organic listing! Other search engines like Perplexity also seem to prioritize citations based on exact questions that people ask.

Conducting SERP Analysis

SERP analysis involves examining the search engine results pages for specific keywords to understand the competitive landscape and identify content gaps. By analyzing the top-ranking pages, content creators can gain insights into the type of content that performs well and identify opportunities to create unique and valuable content. Key elements to consider during SERP analysis include:

• Content Format: Determine the most effective content formats for your target keywords, such as blog posts, videos, or infographics.

• Content Length: Analyze the length of top-ranking content to understand user preferences and expectations.

• Content Quality: Assess the quality and depth of information provided by competitors to identify areas for improvement.

SERP analysis is essential to understand what type of content is ranking well for different searches, and also provides a good starting point for competitive analysis. Much like ads, or any other growth channel : every brand need not reinvent the wheel for SEO. Learning from your search competitors and building on top of that is a great starting point.

Optimizing Content for AI-Powered Search Engines

With the rise of AI-powered search engines like Perplexity, You, Claude, and ChatGPT, content optimization strategies need to evolve. These platforms prioritize conversational, question-based content and have unique characteristics that require tailored approaches.

Optimizing for Perplexity AI

Anyone who knows me, knows that I absolutely love Perplexity. As an engineer, Perplexity is where I start my search when learning about different packages, documentations, etc. Given it’s almost real time indexing of web data, Perplexity is also my source of news. And no, I’m not getting paid to say this (sadly 😞). But it’s not just me - Perplexity’s market share is increasing month on month, has over 2M monthly searches, and I do believe that over the next 5 years it will make at least 5-10% of global search volume. 

Perplexity AI excels at understanding and answering natural language queries. To optimize content for Perplexity:

• Focus on Question-Based Content: Structure your content around questions and answers to align with Perplexity's format.

• Create Comprehensive FAQs: Use Perplexity's follow-up questions feature to identify common queries and craft detailed answers.

• Incorporate Citations: Perplexity values credibility, so include relevant citations and authoritative sources within your content.

• Update Content Regularly: Ensure your content is up-to-date with the latest data and insights.

Optimizing for Other AI Search Engines

For platforms like You, Claude, and ChatGPT, similar principles apply:

• Conversational Tone: Use a natural, conversational tone to engage users and improve content relevance.

• In-Depth Information: Provide thorough and well-researched content that covers topics exhaustively.

• Logical Structure: Organize content with clear headers and subheaders to enhance readability and comprehension.

As these search engines mature, I do expect them to take out of Google’s playbook and release search data (akin to a Google Search Console), to empower users and incentivize them to optimize for specific platforms.

The Bottleneck Part I: Creating AI Generated Content 

It’s no surprise : the strongest use case of LLMs today is to create content. We’ve seen unicorns and rapidly growing companies come up in this space. To name a few (that I’ve used myself and really like) : OpenAI, Anthropic, Jasper, Writesonic, Blaze. While this opens up the floodgates and makes content creation accessible to the masses, it does bring about some ethical and quality challenges. People and companies are using these companies to programmatically create thousands of content pieces and publish them with the sole goal of increasing traffic. There are several problems with this form of usage:

Lack of Originality and Depth

AI-generated content is often based on existing data and patterns, which can result in generic and repetitive content. This lack of originality can lead to a poor user experience and reduced engagement. Additionally, AI-generated content may lack the depth and nuance required to address complex topics effectively.

Lack of Experience and Trustworthiness

Experience and Trustworthiness are 2 of the 4 components of E-E-A-T. Experience comes from actually using a product / service, or having worked with / used them in the past. An AI / LLM trained on generic data can attempt to mimic this, but will fail almost all the time. This then leads to a lack of trust : if you can’t get your readers to trust what you’re saying, what’s the point?

Increasing Focus on Quality by Search Engines

Google's Helpful Content Update specifically targets low-quality, AI-generated content that clutters search results. By prioritizing user-first content, Google aims to reduce the prevalence of generic and shallow content, ensuring that users receive valuable and relevant information. And I’m sure other folks out there are trying to do the same thing, otherwise the results of these search engines will be increasingly spammy. As search engines become “smarter”, companies that have been using this mass generated AI content strategy will suffer and lose out in the long term (which is probably within the next couple months itself).

The Bottleneck Part II : Monitoring AI Generated Content

This is where folks like Google come in : to programmatically figure out what is human vs. AI generated, and potentially give these types of content different weights of importance. The problem is that it is not trivial to say what is human generated vs. AI. 

LLMs were trained on Human data

ChatGPT and other LLMs were trained on human articles. They are made with the goal of mimicking human writing style. We’ve not reached that stage yet, but it is not unreasonable to assume that as these models improve, it will be virtually impossible to tell the difference between human and AI generated content. 

AI Detectors are not in sync

Now, there are companies coming up in the space of determining content is human vs. AI generated, or even giving a score like 50% was AI generated. The problem is that the scoring algorithms of different companies often do not align, and actually end up giving contradictory results! We’ve experimented with some leading ones like WriteHuman, ByPass, Writesonic, and we’ve seen that the same article receives different classifications from different platforms. 

Misaligned incentives for LLM and Search Providers

Lastly, it seems a bit contradictory that search engines want to penalize AI generated content, and at the same time want people to use its technology to create AI generated content. Take Google and Google’s Gemini, or ChatGPT Search and ChatGPT, or Perplexity Search and Perplexity, and so on and so forth. 

Realistically, it is very possible that AI generated content by different LLMs (like a Gemini, OpenAI, Perplexity, Anthropic, etc) leave fingerprints, or patterns that the company’s themselves can use to detect if it was created using their own models. In fact, OpenAI has been rumored to intentionally include such patterns that help them determine if something was created by ChatGPT. However, making these fingerprints public is not feasible, and may also involve releasing intellectual property which these companies will not want to do.

The Winning Content Strategy : Human-in-the-Loop Approach

Now, don’t get me wrong : I’m not saying to not use these amazing tools and technology to create content. What I’m saying is that we need a Human in the Loop approach to Content creation. This involves leveraging tools and platforms to do the analysis, potentially using these tools to create preliminary drafts (and they do a great job at that), and then work with experienced content creators to edit / add / redraft the pieces to incorporate best practices and actually humanize it. This "human-in-the-loop" system ensures that content remains informative, engaging, and aligned with user needs. And of course, it ensures that no matter what core updates come our way, we’re aligned with best practices and continuing to rank well on different topics!

And that’s what Passionfruit does. We’re tech-first, data-driven SEO mavericks who are integrated with all these tools, but combine AI expertise with a team of SEO experts and Content Creators to ensure that quality is never compromised. Our stellar content team has successfully created and managed blogs for clients that have helped them grow organic traffic, and revenue by over 30% month of month across geographies, industries, and target demographics!