How to Adjust—and Measure—Your Content Strategy for Google's SGE

Just a few months ago, Google’s new Search Generative Experience (SGE) experiment officially entered more than 120 new countries and, according to a new report, is set to power 84% of query results—marking yet another pivotal moment in the evolution of search. While chatbots and generative AI have been the media-facing darlings for quite some time, it’s the growing impact that SGE is having on search behavior that will now be felt far and wide, fundamentally reshaping how we interact with search engines and discover information online. That said, it’s important to note that this new era isn't just about getting answers faster; it's about forging a dynamic dialogue with search engines, rooted in even higher levels of relevancy and personalization. This is a step toward a one-to-one conversation. For brands, this presents both new challenges and opportunities for findability. While it’s not entirely certain at present what the true impact of SGE will be, it’s moving quickly, and brands that stay ahead by defining adaptive strategies will be better positioned in the long run. For those unsure where to begin, here are three important considerations when building an updated search strategy that considers the future with SGE. Google Is Paying Publishers to Test an Unreleased Gen AI Platform Master the art of conversation To harness its full potential, teams building content strategies must see SGE for what it is: not a search engine but a chatbot—or more specifically, a conversational snapshot of what the Google engine surfaces from its large language model (LLM). Remember, Google is more than just a search engine; it's an unfiltered database of human intentions. Gone are the days of keyword cramming—the future now belongs to content that anticipates user intent and proactively addresses needs. To achieve this, brands need to understand their target audience thoroughly—pain points, needs, consumption habits, etc. Only then can content move beyond informative to become proactive, conversational and insightful (and maybe even a little witty) to meet and exceed modern user expectations. Brands now engage not only with humans seeking answers to specific questions but with an LLM resembling a discerning editor critiquing an article. This requires meticulous content scrutiny and identifying areas for improvement, such as confusing language, missing context or lack of follow-up information. It’s also very important to build brand signals across the sources in which the LLMs are being trained (for example, Reddit), as topical relevance and the occurrence or citation of a brand will likely become a top relevancy signal. Building on the shift in brand engagement, the transition to SGE points to a noteworthy departure from traditional searches. SGE’s ability to recall the original query enables seamless modifications without requiring the user to retype or change the initial search. This approach allows for multiple seamless pathways, enriching the overall user experience. Consequently, any anticipated follow-ups or related information would need to be incorporated into a brand’s content plan. To navigate this dynamic, approaching content development in the age of SGE requires a heightened focus on intention and purpose. Utilizing clearer, more concise language that not only addresses user inquiries but also anticipates their curiosity and fosters deeper engagement is key. Adapt measurement and visibility strategies In the zero-click landscape of SGE, user queries are often answered directly on the search page, rendering some traditional metrics obsolete. Since few clear and concrete metrics exist as of yet, marketers must exercise a bit more creativity and imagination when defining success. One proactive approach involves utilizing tools like Google Search Console (GSC) to investigate top keywords associated with SGE results. Despite being a manual process at present, marketers would be able to scrutinize historical and current data to identify shifts in metrics, particularly focusing on clickthrough rates. This allows for a nuanced analysis to discern whether there has been an increase or decrease in user engagement. By detecting these changes, marketers have better insight into potential issues or opportunities that may arise due to SGE. Another approach would be embracing advanced analytics to track and compare subtle shifts in user behavior that may be attributed to SGE, such as dwell time and changes in the types of queries leading to the site. These are also highly valuable insights, not only for brand awareness and engagement—revealing how users interact with a brand in a more conversational capacity—but also a helpful baseline to better understand SGE’s role in driving qualified traffic to the website. Finally, in light of Google's testing of third-party cookie restrictions, brands should also focus on leveraging first-party data to monitor topical authority growth and track multichannel attribution. This approach enables marketers to comprehend the holistic impact of organic efforts on the entire customer journey, providing a comprehensive understanding of how SGE fits into the broader marketing strategy. Double down on trust and quality Amid all this change, one’s initial reaction might be to toss their once tried-and-true playbook in the trash and start from scratch. While the adaptations mentioned above are worth considering, it’s still vital that brands do not neglect the fundamentals of findability. Introducing Small Language Models, the Ad Industry’s Latest Gen-AI Fix By keeping Google’s foundational guidelines of experience, expertise, authoritativeness and trustworthiness (EEAT) top of mind, brands can better ensure content is crawled and indexed. Further, things like rank scraping and tracking are poised to become even more antiquated because of how volatile and personalized search results pages will become. This means even with SGE, Google is still going to prioritize the essentials of findability. One thing that SGE’s onset should not encourage, however, is the creation of AI-generated content that will ultimately tarnish quality across the internet. Fresh and original content will be increasingly rewarded and will win out in the end. AI assistance will help human counterparts better understand user intent for a more personalized user experience, enabling teams to think strategically about conversational, question-based content that aligns with the types of queries LLMs are likely to prioritize in search rankings. Right now, Google’s SGE is still considered an experiment and is very much in its infancy, but it’s clear that generative AI is here to stay. Brands need to take these evolutionary shifts seriously—taking no action is not an option. Embrace conversational AI, adapt your measurement and visibility strategies, and hold fast to the pillars of trust and quality to stay ahead.