Let’s face it: there’s nothing worse than putting effort into creating something and feeling the anticipation and excitement of putting it online, only to have it not be seen by anyone. It’s hard not to take it personally, but this has little to do with how good your content actually is and more to do with getting ranked on search engines, Google being the big dog in the game.
It’s no secret that Google has a lot of power and with the emergence of AI in their search experiences, it’s fundamentally reshaping the way we receive information online. After the rollout of Google’s Search Generative Experience (SGE), the traditional rules of SEO and digital visibility are evolving fast, which means that marketers need to pay attention and evolve with them. No longer limited to static links and simple keyword matching, Google’s new AI search delivers more contextual, conversational, and predictive results, further streamlining user experience. For marketers, this is a double-edged sword, presenting both new challenges and unprecedented opportunities to connect with audiences in smarter, more meaningful ways. In this blog we’ll tell you why this shift matters, and how you can stay ahead of the game and finally get the recognition you deserve.
What Is the Search Generative Experience (SGE)?
Powered by artificial intelligence, this new platform leverages advanced AI models to provide dynamic and intuitive search results in order to anticipate user intent. Long story short, the goal of SGE is to use AI to improve our online search experience.
Google initially announced SGE in May of 2023 at their annual I/O conference as part of a push to integrate generative AI into search. Since late 2023 onwards, they have expanded search functionality with more interactive elements like coding help, definitions, and more visual results and while it continues to evolve, it still remains in an experimental phase.
What are the key features of SGE?
AI Summaries (Snapshot)
Nowadays, you’ll probably notice that when you search something in Google, oftentimes there is an AI generated summary at the top of the results page. This is a concise, experimental summary sourced from multiple sites in response to complex or multi-part queries, and it’s often linked for credibility.
Insights Pane
This sidebar appears to offer deeper insights, definitions, or topics related to the original search which can prove useful for exploring a topic in context without ever leaving the results page. What’s more, it’s often enhanced with visuals or other interactive elements, making it more engaging for users.
Conversational Follow-ups
The quest for knowledge doesn’t usually stop at the initial search. If you’re like the majority of users, you’ll have follow up questions and SGE has the answers. After an initial query, users can ask follow-up questions in a chat-like interface keeping the context of the conversation contained in a chatbot and enabling a deeper search journey.
How does SGE differ from traditional SERPs?
There are many differences in the format and user flow of SGE versus those of traditional SERPs. Firstly, the links and snippets of information published in the search results of SGE are AI generated and as opposed to being ranked by the search engine, they are aggregated from multiple sources and displayed transparently. Additionally, the focus of a traditional SERP is to navigate users to a website whereas the goal of SGE is information synthesis. Naturally, this makes the interactivity with the user more conversational and contextual whereas a traditional SERP experience is more static.
Still confusing? Here’s an example. In traditional search results, users typically see a list of blue links accompanied by brief snippets of text. This format requires users to click through multiple links to gather comprehensive information. The need for multiple clicks is reduced with SGE since the interface integrates AI-generated summaries directly into the search results, putting concise information at the top of the page. SGE aims to move away from a former link-centric approach to search and streamline information retrieval, making it more intuitive and context-aware.
AI‑Powered Answer Blocks and Their Impact on Click Behavior
Google AIOs are designed with the user in mind, providing immediate, synthesized information on the search results page directly. Components like text snippets and generated summaries address the user’s queries first hand, citing and linking sources referenced in the text.
AIOs have addressed user pain points by placing ready-made information at their fingertips. Consequently, there’s been a shift in user behavior and since users no longer have to navigate from the results page to obtain relevant information, we’ve seen a reduction in website traffic.
Various studies including one by Search Engine Journal have noted a decline in click through rates for organic listings, and informational queries dropped by over 7% in the last quarter of 2024. Similarly, other sources like the CEO of SparkToro Rand Fishkin suggest that in 2024, nearly 60% of all Google searches resulted in zero clicks due to all of the relevant information being on the results page.
While this trend has certainly caused a decline in organic traffic, paid search ads still continue to capture user attention, suggesting that businesses might need to start allocating more of the budget to SEA in order to maintain traffic.
What is Long‑Tail Content and Why is it Back in the Spotlight?
Up until now SEO has been crucial for content to rank and reach the user but since they’re no longer scrolling down the list of blue links to obtain information, your content won’t reach them even if it is ranked highly on Google. If your content isn’t showing up in these AI responses or isn’t structured in a way that AI can easily digest, it risks becoming invisible.
However, in the midst of this seismic change there is one silver lining: long-tail content is becoming increasingly more valuable. But what is long-tail content? It’s any content that targets highly specific key words or phrases that users enter into search engines. While these queries typically have less search volume, they are more precise in their intent and because they are less competitive than broad words, it is easier to rank for them. An example of long-tail content would be, “How to use Google Analytics for tracking SEO performance in 2025.” This targets a specific niche in the digital marketing world and users who want updated, advanced strategies. The benefit to long-tail content is that it targets users like these with very niche interests, connecting them with exactly what they’re looking for which leads to more relevant traffic and an increase in conversions.
Since Google’s SGE encourages users to ask more natural, conversational queries, content that addresses these specific questions has a better chance of being featured in AI-generated results. The key is creating high-quality, intent-driven content that mirrors how real people ask real questions.
The Challenges of Broad Queries in Google’s SGE
As Google continues to evolve its search experience with AI-powered summaries, marketers face a new challenge; broad queries can sometimes lead to oversimplified or generalized answers that fail to fully address a user’s specific needs. Although SGE offers quick, concise summaries, they risk leaving out crucial nuances or deeper insights that users are often searching for. For broad or vague queries, SGE pulls from various sources to produce high-level summaries that provide a general answer. This is great for users who need a quick overview but doesn’t necessarily serve those looking for detailed, authoritative content.
Here’s an example: If a user is searching for “SEO Writing Best Practices” Google might provide a brief, AI generated response with general tips that aren’t up to date and won’t suffice for users who are looking for in-depth case studies.This is where long-tail content comes in. By providing detailed, comprehensive answers, it can become a critical asset for cutting through these generic AI summaries and delivering the insights that users truly want. This type of content is less likely to get lost in the sea of generative summaries and attract users who want more comprehensive insights. And as Google increasingly values authoritative, well-researched content, it also has a higher chance of being featured in AI-generated responses.
Tactical Takeaways for Marketers: Adapting to Google’s GSE
As Google’s Search Generative Experience (SGE) reshapes the future of search results and how they are displayed, marketers need to take a new approach to creating content that stands out in a new, AI-driven environment. Here are some key tactics to help marketers stay ahead.
Optimizing Headings and Structured Data for AI Pull-Through
Google’s SGE relies on structured data and well-organized content to generate AI-powered summaries and rich snippets. To increase the likelihood of your content being featured in these AI summaries:
- Use clear, descriptive headings: To help search engines and AI systems easily understand and pull relevant information, structure your content using H1, H2, and H3 headings that accurately reflect what the content covers. As opposed to using a vague heading like “Tips,” use something more specific like “10 Expert Tips for setting up a remote office in a small workspace”
- Incorporate structured data (Schema Markup): Add structured data like FAQs, how-to schemas, and product reviews to your content, to make it easier for Google’s AI to extract the most relevant answers for search queries. The richer the results, the greater the likelihood of appearing directly in AI summaries or answer blocks. To implement this, you can use Google’s Structured Data Markup Helper.
- Write answer-focused sections: Format your content with clear, concise answers directly under headings. This increases the likelihood of your content being featured as a direct answer or snippet within SGE. For example, in a guide about “How to start a blog,” include a section that clearly answers the question in a short paragraph or bulleted list, kind of like what we’re doing in this blog right now!
Balancing Short “Snackable” Answers with Long-Form Deep Dives
While long-form, in-depth content is essential for comprehensive topics, Google’s SGE prioritizes quick answers for short, broad queries. Therefore, marketers are tasked with striking a balance. That means creating content that caters to immediate queries as well as that for users looking for in-depth, authoritative answers.
“Snackable” content consists of short, clear, and concise answers between 40-100 words. Ensure the answer to the question is directly stated within the first few sentences of the content, as SGE may pull this information into its AI-powered summary. A prime example could be a search query like “What is SEO?” which could lead to a quick definition presented in a short paragraph at the top of a page.
For more complex topics, long-form content of 2000 words or more is essential for a deep dive into the subject matter. Use long-form content to provide thorough explanations, case studies, or step-by-step guides to establish authority because above all, Google still values authoritative, well-researched content.
One way to create balanced content is to use a layered content strategy where short, snappy answers serve as an introduction or summary, followed by a detailed, long-form explanation, catering to the needs of all users in one go.
Measure Performance by Combining Google Search Console, Analytics, & AI-Metric Tools
As AI-powered search continues to dominate, traditional metrics like clicks and impressions may not provide a full picture of how your content is performing. Here’s how you can leverage a combination of tools to effectively measure success and optimize your strategy:
- Google Search Console: Use this tool to track rankings, impressions, and click-through rates in SGE and look out for increases in zero-click searches. This means users are engaging directly with Google’s AI-generated responses instead of clicking through to your website. If you see high impressions but low CTR, your content may need to be optimized for better AI pull-through.
- Google Analytics: Analytics helps to monitor user behavior, including how long people are staying on your pages, bounce rates, and conversion rates. If your content is being featured in an AI-generated snippet, users may not visit your site, but they may interact with your brand in other ways, like through your social channels or brand searches. You can gauge effectiveness by measuring engagement beyond click-throughs.
- Other AI-driven performance tools: The best way to beat AI, is to leverage it. AI-driven content optimization tools like Clearscope or SurferSEO provide information about how Google’s AI evaluates content with insights into keyword relevance, content structure, and readability. You can also keep an eye on AI-powered SERPs with tools like RankRanger or SEMrush that track how often your content is being featured in AI-generated summaries.
GoViral Conclusion
Just like life, search behavior changes, and continues to change everyday. This also means that if marketers want their content to be seen, they have to change with it and stay on top of search behavior trends. The emergence of Google’s SGE requires marketers to regularly audit content and optimize it for AI visibility by focusing on creating niche, long-tail content that addresses specific user needs. By staying agile and creating high-quality, targeted content marketers can thrive in this new, AI-driven search landscape. You know the saying, if you can’t beat ‘em join ‘em!