Google’s AI Search Updates: What Marketers Need to Know
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!
5 Signs to Identify AI Content on Instagram
When you want to find out an answer quickly, which do you go to first – Google or Chat GPT? Gemini?
Artificial Intelligence is integrating itself into every aspect of life and speeding up processes that used to be time-consuming.
The marketing space has been overtaken with AI as many are using it for project management tools, scheduling, and the mundane tasks that come with doing admin. A huge area that AI has slid into is the content creator space, especially on Instagram.
Meta has unlocked many features this year, from chatbots to AI-Generated Images.
AI is helping businesses and creators create content in a quicker timeframe but what are the concerns around AI? How do we know what’s real and what’s AI-Generated?
In this month’s blog, we’re going to discuss the advancement of AI, 5 signs that an Instagram post was made using AI, and what does “made with AI” mean attached to an image.
Let’s dive into it.
The Advancement of AI on Instagram
Did you know AI integration on Instagram began in 2010?
The filters to adjust your images brightness or add a different tone to the image is all done by AI.
The suggested accounts that pop up in your feed exist because of Instagram’s machine-learning algorithm.
When you hear people talk about keywords, SEO, hashtags, this is the reason. In 2010, the algorithm was at its most basic, using image recognition to categorize photos based on content.
As Instagram switched from its basic capabilities to more advanced, machine learning techniques like “word embedding” analyze the content and categorize it in terms of relatedness.
Who said words don’t matter? Your bio (the small description you have on your instagram), the captions, the hooks, the copy under the post is all being scanned to categorize your account.
So pay attention to your words!!
The transformation of AI capabilities since 2010 to the present moment in 2024 have become far more advanced at a rapid pace.
Let’s take a look at the timeline.
Between 2010 and 2014, AI was focused mainly on image enhancement like brightness and contrast, cropping your photos, personalized content based on your interactions and preferences.
From 2015 to 2019, the features began to roll out quicker.
- The explore tab was enhanced using a more advanced machine learning algorithm, improving personalization and content discovery.
- “Word embedding”, keywords and hashtags, helped analyze the content to recommend accounts based on interactions.
- Seed accounts, created by instagram,used to test new features, algorithms, or functionalities before rolling them out to the general public.
- AR and Virtual reality began to be rolled out as well as the use of NLP, Natural Language Processing, machines to scan for offensive comments and limit spam and misinformation.
- The birth of IGTV with AI recommendations personalized video content for each user based on interactions and preferences.
- AI-Enhanced shopping features were created to recommend products and target ads based on user behavior.
From 2020 onwards, the creation of tools for content creation like automated caption suggestions and hashtag recommendations began to roll out as well as conversational AI assistants that would answer queries, provide content recommendations and help in generating posts.
In 2024, the rollout of Meta AI on Instagram is even more powerful compared to what it was in 2010.
The implementation of AI on the platform has saved content creators, businesses, brands hours of work but a major issue that has caused controversy is when people use it for potential harmful reasons.
Because of the advancement of AI, it now has the ability to create images that look eerily real, making it harder to know what’s AI created and what’s REAL content.
This is down to generative AI which works by creating new data that mimics human creations.
If you struggle to distinguish between superficiality and reality, never fear because here are our top five signs that an image was AI-Generated.
The 5 signs of an AI-Generated Image
We all want to know whether an Instagram post is made with AI because Instagram is known to be the “highlight” reel, the best bits.
Ensuring the user is informed about what’s AI-Generated and what’s not is something Mark Zuckerberg, head of Meta, wants to make sure is maintained.
Here’s five pointers to spot AI going from the easiest to hardest to spot.
1. Distorted Backgrounds:
If a door looks like it has a bump in it or is twisted into another shape, it’s a clear indication something was done to the image. This is one of the easiest ways to spot an image was
2. Something feels.. Off
We wrote about AI influencers in our last blog (read more on it here) and there’s a slight unease when looking at the image.
They say you can read a person by looking into their eyes. When you see an AI-Generated image of a “person”, there’s nothing.
Almost like a blank stare. Like it’s not… real. AI influencers on Instagram have risen in popularity with many brands like Chanel and Red Bull using them for online promotions.
3. Pay attention to the small details
We’re scrolling 24/7 (hopefully not!), and are scanning images and text at a quicker pace. This means we miss the finer details.
Don’t take an image at face value if you feel like something isn’t right. AI images are created by taking data from other photos and creating a new image.
AI programs often struggle with details you may see less frequently in other pictures.
AI tends to get the smaller details like logos and text wrong as you can see below.
4. If it looks too good to be true, it probably is
As much as we want to look perfect all the time, we don’t. We’re humans, imperfection is perfection.
You can tell if something is too good to be true if the image looks smooth and no texture because well, we have texture.
So don’t be fooled by an image looking picture perfect because it most likely isn’t real.
5. Reverse Search
You know the TV show “Catfish”? If you don’t, it’s a programme where the hosts bring on a person who writes to the show about their relationship.
They write in because they’ve never met the person and want to make sure they are the real deal. One of the first things the hosts do is reverse search the image.
They do this because they want to see if the person is using someone else’s photos.
This is the same when it comes to images on Instagram.
If in doubt, reverse image search because if it is AI-Generated, there won’t be a lot of information which tells us something is fishy.
“Made with AI”
You might have spotted on Instagram recently under some images and videos are a tag saying “Made with AI”.
This feature was recently introduced however, there has been some controversy especially for photographers.
How it works
When you upload an image to Instagram, the algorithm will read the metadata of the image to clarify whether it’s real or AI-generated.
This is great BUT what if you just enhanced the brightness? Enhanced the sound so it’s clearer? Removed the blemish from your face that was annoying you?
Instagram smacked the tag of “made with AI” on it. The problem for photographers is the wording.
Saying an image was made with AI sounds like it was superficial, that they didn’t put the hard work into capturing a beautiful moment like a wedding or someone’s birthday.
Some argued for it to be changed to “edited with AI” which clarifies that the image has been enhanced but it was taken professionally, not created superficially.
Because of the backlash, from July this year, the made with AI feature has been changed to AI Info.
This is a step in the right direction to distinguish the difference between an image being AI-Generated and one that’s a real-life photo.
GoViral Conclusion
Our advice is to always be cautious about images that are posted online.
If something isn’t sitting right with you, there’s a reason why. Our five pointers will give you more clarity around AI-Generated photos and with the introduction of “AI Info” on images,
It can help you distinguish between superficial and reality.
As many new features are being added to social media platforms every day, it’s important to stay up-to-date with the new trends and implementations.
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