Ecommerce Management Advisors
Ecommerce Management Advisors
Google leads organic search with 94.8% traffic, but AI tools and smaller engines show growing competition.
In the fast-paced world of PPC advertising, marketers are constantly seeking ways to streamline their workflows and improve performance.
Managing PPC campaigns efficiently requires a delicate balancing act of multiple tasks:
While AI and machine learning have been around in PPC for years, a new wave of AI tools for streamlining productivity and workflows has made its way into the PPC scene.
Whether it’s automating repetitive tasks, enhancing audience targeting, or analyzing vast datasets, AI tools are reshaping how PPC professionals work.
Who doesn’t want to save time doing repetitive, busy work tasks?
In this article, we’ll explore several unconventional ways AI tools can help PPC marketers save time, increase efficiency, and make smarter decisions.
PPC campaigns can generate enormous amounts of data that need to be consistently analyzed and interpreted.
AI tools outside of the standard Google and Microsoft Ads platforms can help streamline this process by helping with tasks like:
These insights can enable marketers to move from data to action faster.
If you’d rather not manually sift through reports identifying changes in performance metrics changes, you can actually feed campaign data into ChatGPT (or similar AI tools) to receive summaries that highlight performance trends.
For example, they can help identify seasonal changes in performance or pinpoint potential issues, such as a sudden dip in conversion rate.
Say you run 20 different campaigns in Google Ads and start to see a significant drop in conversion rates from the platform. It can be daunting to immediately pinpoint the cause of the issue.
By processing raw performance data from your campaigns, these AI tools can quickly analyze the data and provide insight into not only where the problem(s) can lie, but also glean insights as to why performance has shifted, like:
Using AI tools in this capacity helps marketers cut down on analysis time while helping to identify core issues faster, allowing for quicker optimization.
This automation saves hours of manual work, enabling you to focus on more strategic decision-making instead of spending time analyzing large datasets.
Keeping up with competitors is crucial in the PPC landscape, but the task at hand can be time-consuming and complex.
AI tools simplify this process by providing insights into competitors’ strategies, allowing you to stay one step ahead.
There are plenty of tools to help drive competitor insights, whether in the Google Ads platform, third-party tools, or AI tools.
If you’re looking to take the analysis a step further, you can input reports from other competitive analysis tools into ChatGPT (or a similar tool) to receive a quick summary that highlights a competitor’s recent actions.
For example, this could include information like:
Based on this data, the AI tools can suggest ways to adjust your own campaigns or suggest counter-strategies to stay competitive.
By automating competitor analysis tasks, you can gain valuable insights faster, which allows for quicker, more informed decision-making and strategic actions.
Managing campaigns across multiple platforms – whether it’s Google Ads, Microsoft Ads, Meta, or others – means compiling huge data sets from different sources.
Trying to put together a compelling, holistic story about your marketing campaigns can take up a lot of time as you navigate from platform to platform.
This is where the power of AI tools can come in to help aggregate reports and create cohesive summaries.
Multi-channel reporting is often a daunting task, especially when managing accounts across Google, Microsoft, and social platforms.
By inputting performance data from these platforms into ChatGPT, marketers can receive a single, unified report that summarizes key performance indicators (KPIs) across channels.
For example, say you manage several campaigns across Google Ads, Microsoft Ads, and Meta Ads.
Instead of switching between dashboards and manually pulling data, you can input the performance metrics from each platform into your AI tool of choice.
The tool can summarize the top-performing platforms, highlight underperforming campaigns, and suggest where to reallocate budgets to maximize ROI.
AI’s ability to consolidate multi-channel data helps reduce reporting time, enabling marketers to spend more time optimizing campaigns and less time on administrative tasks.
Keyword research is at the core of every PPC strategy, and expanding keyword lists can be labor-intensive.
AI tools can make the process more efficient by identifying relevant keywords, negative keywords, and keyword variations that are often missed in traditional tools.
While tools like the Google Keyword Planner are great at providing keyword recommendations, AI tools can take it a step further.
They can generate items like long-tail keyword variations and help identify opportunities for new targeting strategies.
Additionally, they can analyze an existing keyword list and suggest related keywords that reflect user intent or emerging trends.
For example, say you manage PPC campaigns for an ecommerce retailer. You input a list of current top-performing keywords with your latest KPI performance data into your AI tool of choice.
From there, the tool can generate suggestions for new long-tail keywords that may have lower volume, but higher intent to purchase.
Additionally, you can ask the tool to suggest negative keywords to eliminate irrelevant traffic, which improves both relevance and cost efficiency.
To really kick this into high gear, you can then ask the tool to format these new keywords and negative keywords into a format that allows you to upload them into Google Ads Editor, saving you hours of manual work adding each one individually.
Using AI tools beyond the ad platforms can help marketers discover new opportunities faster, ensuring more comprehensive targeting with minimal manual effort.
There’s no debate that A/B testing is critical to campaign optimization, but interpreting results and making decisions about the next steps is where most people fall flat.
Using AI tools to streamline this process can aid you in analyzing test data and suggest optimizations based on performance.
Say you want to test two different versions of a headline in a PPC campaign. You can upload your test performance data into an AI tool for analysis.
Not only will it summarize which headline performed better, but it goes a step further to help answer why one headline outperformed the other.
By providing insights into which elements contributed to success, it can save you time in the long run and help keep those driving factors top of mind for the next test.
Effective budget management is essential for optimizing PPC performance.
The ad platforms are great at automating tasks like changing daily budgets based on scripts, but what about strategic budget allocation decisions?
Using AI tools to assist budget allocation across campaigns or platforms by forecasting potential outcomes based on past performance data can streamline the process of deciding where to invest – and when.
For example, a retail client has an upcoming holiday sale and they want to know if they can expect a higher return than last year’s sale.
Inputting last year’s campaign performance into AI tools like ChatGPT can help analyze performance, while also taking into consideration current market trends.
The output could be to suggest how much of the budget should be allocated to high-performing keywords or certain product categories.
It can also provide a forecast of expected returns based on historical data, current CPC trends, and consumer behavior trends to help you make informed budget decisions ahead of time.
AI-driven budget forecasting helps ensure that resources are allocated to the right areas, reducing wasted spend and improving overall campaign performance.
Market trends can shift quickly, and staying ahead of these changes is key to successful PPC campaigns.
AI tools can analyze search trends, consumer behavior, and historical campaign data to predict future shifts in demand and help marketers prepare.
For instance, AI tools can identify trends in consumer searches in real time, helping you adjust your campaign strategies proactively.
For example, you manage Google Ads campaigns for a fitness brand, and you’re noticing a seasonal uptick in searches for [home workout equipment].
By using AI tools to analyze Google Trends data, you can forecast how that demand will continue to rise or fall in the coming months, and even if certain geographical areas are driving the high demand.
This allows you to adjust bids based on location, increase overall budgets if necessary to help capture demand, and create relevant ad copy that speaks directly to the emerging trend.
AI is revolutionizing PPC workflows, allowing marketers to work smarter, not harder.
Whether you’re leveraging Google Ads’ AI capabilities, like Gemini’s conversational ad creation or integrating third-party tools for deeper insights, AI is becoming indispensable in managing and optimizing PPC campaigns.
From automating bid management and audience targeting to optimizing ad creatives and providing actionable insights, AI offers opportunities to boost efficiency without sacrificing effectiveness.
As AI tools continue to evolve, those who embrace these technologies will find themselves better equipped to deliver superior results, whether managing in-house campaigns or serving clients.
By integrating both Google’s AI features and powerful third-party tools, you can unlock new levels of performance, save time on manual tasks, and focus on strategy and innovation.
More resources:
Featured Image: 3rdtimeluckystudio/Shutterstock
Understanding search engine results pages (SERPs) is critical for anyone serious about increasing their website’s visibility.
Search engines use SERPs to display results for user queries, and the primary goal for SERP analysis is understanding why certain pages earn top rankings and what elements contribute to their success.
Analyzing these pages can unlock valuable insights into ranking factors, search intent, and what content types perform best.
Conducting SERP analysis helps you develop content strategies that align with search engine preferences and user expectations.
In this comprehensive guide, we’ll explain the fundamentals of SERP analysis, why it matters, and how you can master it to improve your SEO strategy.
Today’s search results pages are more complex, featuring many elements beyond the traditional organic blue links. Here are the key SERP features you need to know:
Position zero results that provide immediate answers to queries, typically in the form of paragraphs, lists, or tables.
These snippets are extracted directly from top-ranking pages and appear above organic results.
Screenshot from search for [How does photosynthesis work in desert plants], Google, January 2025Google’s AI-generated summaries synthesize information from multiple sources to provide comprehensive answers.
These appear at the top of results and often include citation links to source material.
![Screenshot from search for [ai overviews], Google, January 2025](https://ecommerceedu.com/wp-content/uploads/2025/02/ai-overviews-google-search-12-30-2024_12_16_pm-981.png)
Screenshot from search for [ai overviews], Google, January 2025Enhanced search listings that display additional information through structured data, such as:
![Screenshot from search for [chocolate chip cookie recipe], Google, January 2025](https://ecommerceedu.com/wp-content/uploads/2025/02/rich-snippets-435.png)
Screenshot from search for [chocolate chip cookie recipe], Google, January 2025These are information boxes appearing on the right side of desktop searches, displaying key facts about entities like:
![Screenshot from search for [HigherVisibility], Google, January 2025](https://ecommerceedu.com/wp-content/uploads/2025/02/highervisibility-google-search-12-30-2024_12_17_pm-288.png)
Screenshot from search for [HigherVisibility], Google, January 2025Expandable sections showing related questions and answers, helping users explore topics in greater depth.
Screenshot from search for [how do solar panels work], Google, January 2025Groups of three local business listings with maps, particularly prominent for location-based queries.
![Screenshot from search for [pizza near me], Google, January 2025](https://ecommerceedu.com/wp-content/uploads/2025/02/local-pack-471.png)
Screenshot from search for [pizza near me], Google, January 2025![Screenshot from search for [wireless headphones], Google, January 2025](https://ecommerceedu.com/wp-content/uploads/2025/02/wireless-headphones-google-search-12-30-2024_12_18_pm-359.png)
Screenshot from search for [wireless headphones], Google, January 2025
Screenshot from Google News, January 2025SERP analysis is a cornerstone of any SEO strategy because it provides actionable insights about your competition, audience preferences, and search engine ranking factors.
Here’s why it’s so important:
Search intent is the motivation behind a user’s query.
For example, a user might want to learn how to complete a specific task, compare different products or services, or make a purchase.
Analyzing the top-ranking pages for a keyword is the best way to infer the search intent behind that term. This is because search engine algorithms are fine-tuned to surface content that best matches what users expect to see.
So, if most of the results for a given keyword are tutorial-based articles, it’s safe to assume that users searching for that keyword are looking for step-by-step instructions or educational content.
Meanwhile, if the results consist primarily of product pages or reviews, the intent is likely transactional, with users looking to make a purchase or compare options before buying.
Further reading: How People Search: Understanding User Intent
Studying top results helps you identify what your competitors are doing right.
This includes the depth and structure of their content, their use of multimedia formats like videos or infographics, keyword optimization tactics, and the strength of their backlink profiles.
By closely examining these factors, you can uncover patterns in the strategies across competitors that drive their success.
What’s more, SERP analysis helps you pinpoint gaps in your competitors’ strategies – such as overlooked topics, under-optimized keywords, or weak content in high-ranking positions – giving you opportunities to create more comprehensive, engaging, and authoritative content that outperforms them.
Further reading: SEO Competitive Analysis: The Definitive Guide
Not all keywords are equally competitive.
SERP analysis can help you find low-hanging fruit – keywords with manageable competition that still attract significant search volume.
By identifying these overlooked or underserved keywords, you can create targeted content to capture untapped traffic and build authority.
These opportunities are especially valuable for smaller websites or those just beginning to build domain authority.
They allow you to focus your efforts on achievable wins while steadily growing your traffic and credibility.
Further reading: Keyword Research: An In-Depth Beginner’s Guide
Appearing in SERP features (as we discussed earlier) can significantly increase your visibility and click-through rates.
Because even if you don’t achieve the highest rankings, your site can still claim some valuable SERP real estate and capture user attention.
SERP analysis helps you identify which features appear for your target keywords and what type of content Google pulls into them.
For example, featured snippets often prioritize concise, well-structured answers, while PAA boxes highlight responses to commonly searched follow-up questions.
By tailoring your content to match the requirements of these features – whether it’s using clear formatting, answering common questions, or implementing structured data – you can boost your chances of appearing in these prominent positions, ultimately driving more traffic to your site.
Start by choosing the keywords you want to target.
The goal here isn’t just to pick any search terms that are relevant to your business.
Remember, not all keywords offer the same value – some are highly competitive, while others may not attract enough search traffic to be worthwhile.
Instead, focus on keywords that are:
Look for terms that reflect the type of content your target audience will likely find valuable, whether it’s solutions to their problems, product recommendations, or in-depth information on a particular topic.
Focus on terms that match your immediate business objectives, such as building brand awareness, generating leads, or directing traffic to specific product pages.
Avoid going after highly competitive keywords dominated by well-established brands unless you have the resources to compete.
Instead, look for long-tail keywords or niche terms that give you a better chance at standing out.
As a rule, keywords with high search volumes tend to be the hardest to rank for.
That said, you don’t need to aim for the highest-volume keywords to see results.
Instead, focus on keywords with moderate search volume that are still relevant to your audience and achievable for your domain authority.
When examining search results, consider:
Desktop Vs. Mobile Differences:
Location And Personalization Impact:
SERP Feature Opportunities:
Next, you’ll need to examine the top-performing content in a little more depth.
The goal is to figure out what makes these pages rank so highly so you can reverse-engineer their success and apply similar strategies to your own content.
Here are some things to consider:
So, if you find that the top pages for your keyword average 2,000+ words, cover multiple subtopics, and include custom visuals and quotes from industry experts, creating a 500-word blog post probably won’t cut it.
To compete, you’ll need to create a more detailed, engaging resource that provides value users can’t get elsewhere.
This leads us to the final step.
Here, the goal is to find opportunities to differentiate yourself by looking at where existing top-ranking content falls short.
Ask yourself:
For example, if top-ranking pages lack practical examples, recent data, exclusive quotes from industry leaders, or high-quality visuals, incorporating these elements will help give you an edge over your competitors.
This step is all about going above and beyond the quality of existing content. By filling these gaps, you’ll provide a more valuable reading experience for users.
SERP analysis has evolved beyond simply studying organic rankings. Success requires understanding the full spectrum of SERP features and how they interact with user intent and behavior patterns.
By implementing the strategies outlined in this guide and staying current with new SERP features as they emerge, you’ll be better positioned to capture valuable SERP real estate and drive meaningful traffic to your site.
Remember to regularly review and update your SERP analysis approach as search engines continue to evolve and introduce new features that can impact your visibility and performance.
More Resources:
Featured Image: Gorodenkoff/Shutterstock
Alphabet Inc., Google’s parent company, reported strong fourth-quarter results for fiscal 2024, primarily driven by its commitment to AI.
Alphabet announced revenues of $96.5 billion for Q4 2024, up 12% from last year.
Google Services, including Search and YouTube ads, grew by 10% to $84.1 billion.
Google Cloud increased revenues by 30% to $12.0 billion as more businesses adopted its AI services.
Operating income rose by 31%, and net income increased by 28% to $26.5 billion.
CEO Sundar Pichai highlighted the company’s AI achievements and recent launches during the earnings call.
Pichai said:
“Q4 was a strong quarter driven by our leadership in AI and momentum across the business. We’re making dramatic progress across compute, model capabilities, and in driving efficiencies. We’re rapidly shipping product improvements, and seeing terrific momentum with consumer and developer usage.”
Alphabet is investing heavily in its infrastructure, launching new data centers and subsea cable projects to improve global connectivity.
Pichai stated:
“We broke ground on 11 new Cloud regions and data center campuses in places like South Carolina, Indiana, Missouri, and around the world. We also announced plans for seven new subsea cable projects, strengthening global connectivity.”
These efforts will support the growth of AI services, as data centers now provide nearly four times more computing power for the same energy.
Google reported that its AI-powered search features are gaining traction. AI Overviews are now available in more than 100 countries.
Circle to Search, available on over 200 million Android devices, is popular among younger users, who now use it for more than 10% of their searches.
SEO professionals and digital marketers should brace for further changes, as Pichai declared that “2025 is going to be one of the biggest years for Search innovation yet.”
The company’s $75 billion capital expenditure plan for 2025 suggests significant investments in search technology and AI capabilities.
Google’s Q4 results highlight its focus on AI. Overall revenue increased 12%, and the cloud business grew 30%. Profits increased as well, with operating income rising 31%.
The company’s investments in data centers and undersea cables will support global AI growth.
New AI features, such as Search Overviews and Circle to Search, are changing user behavior, so SEO teams should prepare for more changes in 2025.
Keep an eye on Google’s $75 billion spending plan to expand AI technology.
Featured Image: Dennis Diatel/Shutterstock
This is my official eulogy for the SEO keyword, which died many years ago, but no one has noticed.
As a result, many marketing teams make sub-par decisions, and decision-makers lose trust in SEO as a channel. Just look at the recent “SEO is dead” reactions to HubSpot’s traffic decline.
Since January 20, Google has required JavaScript for Search, which makes rank tracking more expensive.
This is the latest move in a long-standing battle between SEO pros and Google.
Rank trackers (Semrush, Ahrefs, SEOmonitor, etc.) have been operating in a gray zone. Google tolerates them but officially doesn’t allow it.
Now, with JavaScript as a hard requirement, rank tracking needs more RAM, which increases the cost of every data point.
The result is that the cost of doing SEO is rising. But rank tracking lost its value long before Google switched to JavaScript crawling.
Image Credit: Kevin IndigWith all the elements in the SERPs and the unrepresentative data we get, it’s hard to project impact and measure success purely based on keyword ranks.
On one hand, a single webpage can rank for thousands of keywords as long as those keywords express the same intent and the page gives a good answer to all implied questions. This has been the case for many years now.
On the other hand, more and more keywords don’t deliver traffic because all clicks go to a SERP Feature that keeps people in the search results, or a click isn’t necessary – searchers get the answer in the search results.
Sparktoro found that +37% of searches end without a click, and +21% result in another search.3
Image Credit: Kevin IndigA couple of months ago, I rewrote my guide to in-house SEO and started ranking in position one. But the joke was on me. I didn’t get a single dirty click for that keyword.
Over 200 people search for [inhouse seo], but not a single person clicks on a search result.
By the way, Google Analytics only shows 10 clicks from organic search over the last three months.
So, what’s going on? The 10 clicks I actually got are not reported in GSC (privacy… I guess?), but the majority of searchers likely click on one of the People Also Asked features that show up right below my search result.
The bigger picture is that the value of keywords and ranks has tanked.
Our response can be two-fold:
We’re still operating with the old model of SEO, which is where we track a list of keywords to measure success and set targets.
But how much sense does that make given pages rank for many keywords? How much sense does it make a given search to move from a list of results to LLM answers?
The keyword doesn’t have a future in search. What does is intent, and LLMs are much better at understanding it.
So, here is my suggestion: Instead of focusing on keywords, we should focus on organic traffic aggregated on the page or domain level.
Some traps to watch out for:
To track how well a domain or page is doing, we can still look at keywords; the direction of organic traffic is more indicative of whether it does well or not.
One big issue I have with keywords is that search volume has many flaws and is so unrepresentative of what’s actually going on.
The term “in-house seo” has a reported search volume of 90-200 in the biggest rank trackers but doesn’t actually deliver any clicks.
To know what pages to create without keyword research, talk to customers and analyze what topics and questions they care about.
Analyze platforms like Reddit and YouTube for engagement and reverse engineer what topics work.
And, we can – and probably will have to – use paid search data to inform SEO because it’s more reflective of topics with the way that Google shows (Performance Max) ads to users in Search, which are similar to user intent.
To project traffic, look at domains or pages that are already visible for topics we care about, just not on the keyword level.
Clickstream data that reflects how users browse the web is much better because it doesn’t project potential traffic based on a keyword position.
Where keywords still make (some sense) is for analyzing historical search volume to project whether a topic is growing or shrinking, but I suggest using only large amounts of keywords.
A huge benefit of the aggregate traffic approach is that it transfers well to LLM because they don’t give us queries either, but we can track referral traffic on the domain and page level.
ChatGPT even adds a URL parameter to outgoing clicks that makes tracking easier.
Image Credit: Kevin IndigThe real reason Google enforces JavaScript crawling is not to hurt SEO professionals but GenAI competitors.
ChatGPT and Perplexity are gaining significant ground. ChatGPT has already surpassed the traffic of Bing and Google’s Gemini. Perplexity is on the way there.
However, LLM crawlers can’t execute JavaScript, which means they can now no longer crawl Google’s search results to ground their answers.
(By the way, you need to make sure your content is accessible without JavaScript. Otherwise, LLMs can’t crawl it, and you can’t appear in their answers.)
The quality of some LLMs might decrease due to Google enforcing JavaScript, but only temporarily. LLMs can still get SERP data in other ways.
But one potential consequence of Google’s decision is that LLM developers build their own models or web indices to weigh answers and become independent of search engines.
The second-order effect of that would be that it’s no longer enough to do good SEO to appear in LLMs. We would have to reverse engineer LLM results like we did with Google.
If SEO is a game, winning in SEO now requires adjusting based on the flow (intent) of the game instead of counting cards (keywords).
The future of search is not keywords but intentions.
Let this be my official eulogy.
Image Credit: Kevin Indig2 Almost Half of GSC Clicks Go to Hidden Terms – A Study by Ahrefs
3 2024 Zero-Click Search Study
Featured Image: Paulo Bobita/Search Engine Journal
This post was sponsored by Bright Data. The opinions expressed in this article are the sponsor’s own.
Struggling to adapt your SEO strategy to ever-changing AI-driven SERPs?
Have the most recent Google updates left your rank-tracking methods outdated?
What happens when you can no longer deliver key information on traffic sources?
Generative AI (GenAI) technologies like Google Gemini and Bard are reshaping search results.
This is creating unprecedented challenges, especially when it comes to the elephant in the room: “The New Position 0.”
In this article, we’ll help tackle the key ways to:
Just this week, Google rolled out unexpected changes to SERP structures, causing widespread disruptions for many SEO strategies that rely on SERP rankings.
These updates led to outages and inaccurate data across the industry, forcing many businesses to quickly adapt to avoid prolonged disruptions.
“The disruptions caused by Google’s latest SERP changes left many platforms unable to deliver accurate data to their users. Our clients, however, were unaffected thanks to our immediate response and robust infrastructure. If not for the media and search community, they wouldn’t have known there were any changes.” – Ariel Shulman, VP Product at Bright Data
Generative AI has fundamentally altered how search engines deliver results.
Classic SERP features have become central to understanding user intent and the user journey.
Until now.
The SERP layout we know and love has changed.
These overall changes present challenges for rank-tracking platforms tasked with capturing and analyzing SERPs:
The challenge for rank-tracking platforms is clear: adapt to these AI-driven shifts or risk leaving users without the insights they need to thrive.
Position 0 on Google refers to any of the featured snippets that appear at the very top of the search engine results page (SERP), above all organic search results.
It’s a special box that highlights concise information in response to a query, often in the form of a paragraph, list, or table.
For example, if you search for “How to tie a tie,” the featured snippet might display step-by-step instructions directly at the top. Being in Position 0 can boost your SEO strategy significantly since it’s considered premium real estate in search rankings.
The featured snippet is designed to provide users with quick answers to their questions without requiring them to click on a website. It’s highly coveted by website owners because it significantly increases visibility and click-through rates.
However, it’s becoming more difficult to track what is ranking in position 0 due to 5 different issues that baffle the current MarTech stack.
So, let’s dive deeper: What did Google change that you’ll need to change?
As we’re seeing in real-time, AI technologies like Google Gemini (previously Bard) and Microsoft’s Bing AI are reshaping SERP layouts.
So far, SERP structures are evolving rapidly with AI updates.
Elements like conversational answers or rich media snippets appear inconsistently, requiring you to constantly adapt your SEO strategy and data collection methods.
Instead of seeing Google Ads placements, featured snippets, positions 1-3, and People Also Ask, we’ll now be seeing:
However, this is not its final state. The new layout of SERPs is dynamic; it will continue to change, and you have to be ready.
With position 1 pushed down at least 3 scroll lengths, this is no longer the top clicked result.
Additionally, the layout of a searcher’s query will also vary based on new advances in SERP personalization.
Now, clicks are possible in many new locations on the SERP, such as in a cited link for Google’s AI Overview (AIO).
These are not as easily trackable nor attributable.
SEO analysts and SEO strategists will see a massive impact on their traffic data and how they optimize their content to display above the fold.
Finally, position 1 on Google SERPs has seen its decline from providing at least 33% of organic search clicks to just 11% as of January 2025 depending on the search term.
Organic CTR declined ~70% when an AIO was present on the SERP.
AIO not only makes it difficult to obtain clicks, but one final change has made it nearly impossible to attribute clicks to positions.
In short:
What does this mean?
Google AIO and other dynamic SERP features are the new Position Zero.
Many SERP elements, especially those influenced by AI, load dynamically based on user interaction.
As we know from past SEO knowledge, dynamic and lazy-loading content cannot be seen by bots and scrapers until something triggers the content to load.
Therefore, to retrieve all the necessary data, you’ll need to simulate interactions like clicks and scrolls, which adds complexity and latency.
As you can see so far, dynamic and personalized search results are more prominent.
Your favorite SEO keyword research and rank-tracking tools rely on bots to crawl the web for key data to help you build your SEO strategy.
However, Google has removed a large piece that makes that data scraping possible: bots.
Google’s evolving anti-bot measures further complicate real-time data collection, pushing platforms to the brink of what their systems can handle.
Sophisticated anti-bot defenses, such as CAPTCHA challenges, IP-based blocking, and JavaScript obfuscation, make real-time data collection a significant hurdle. Many traditional scraping tools cannot meet these challenges.
Control data is something that remains the same from one experiment to another. It enables you to have direct comparisons to build conclusions from when you’re building your SEO strategy.
The old SERP’s control data was the standardized layout. SERP layouts and results were similar enough for the same search query, meaning you could compare multiple searches for the same query to create conclusions that drove your strategy.
Now, user-specific factors like location, language, and device type create unique SERP views with vastly different orders of results.
It’s no longer simple to look at SERP data for [What is a 5-star hotel?] and know which link was clicked from which position:
Capturing this variability at scale while maintaining accuracy is critical yet immensely difficult.
AI-generated responses are constantly updated, with position-zero content shifting based on new data and context.
These AI-generated responses are part of an evolution of Search Engine Optimization (SEO) called Answer Engine Optimization (AEO).
You’ll need tools that have been updated to extract data from Answer Engines in real-time.
To regain your lost traffic, you’ll need to refer to more sophisticated tools to gain access to new SERP data streams to inform your organic traffic strategy.
Tools that previously helped you understand your position on SERPs are now outdated.
Rank-tracking platforms that have upgraded should be ready and able to collect data using more modern sources that align with the roadblocks above.
These tools don’t just need to collect data, they need to deliver actionable insights to help their users optimize for “The New Position 0” based on the data and AIO’s best practices. By extracting the right data and presenting it clearly, platforms empower users to improve their strategies effectively.
Here’s how platforms are leveraging Data from GenAI results:
Platforms will need insights into which content types (e.g., FAQs, schema markup, and structured data) are prioritized by AI-driven search engines. This will help their users create concise, authoritative content that aligns with SERP preferences, improving visibility and relevance in position zero.
They will need metrics such as click-through rates (CTR), impressions, and engagement specific to position zero. These metrics will help their users monitor performance and refine their strategies to maintain or improve their rankings.
Platforms will need geo-targeted and device-specific data to provide segmented insights. This will help their users tailor their optimization efforts to specific regions, languages, or devices, ensuring their strategies are more precise and effective.
They will need data on conversational and intent-driven search queries. This will help their users align their content with how large language models prioritize conversational patterns, resulting in higher engagement and relevance.
SEO tools using Bright Data’s toolkit have access to all this data in real-time and at scale. That’s why the leading SEO tools choose Bright Data as their go-to data provider. Platforms leveraging these insights position themselves as indispensable tools for helping their users dominate “The New Position 0.”
As “The New Position 0” continues to redefine search, rank-tracking platforms face mounting challenges in delivering accurate, actionable data. Choosing the right data collection partner is no longer optional, it’s the key to staying ahead. Platforms leveraging Bright Data’s SERP API are equipped to meet these challenges, empowering their users to succeed in an AI-driven search landscape.
Bright Data’s proactive approach meant their clients experienced uninterrupted services during the disruptions that affected many in the industry. SEO tools leveraging Bright Data’s SERP API maintained seamless operations, continuing to deliver accurate, real-time insights to their users without issue.
Integrating your platform with Bright Data’s SERP API is quick and straightforward. Want to see what it’s all about? Check out the documentation here or test it out in the SERP API playground to see if it’s the perfect match for your SEO tool. When data matters, companies choose Bright Data.
This article has been sponsored by Bright Data, and the views presented herein represent the sponsor’s perspective.
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Enterprise SEO platform BrightEdge published results on current AI Search trends, showing that Google AI Overviews (AIO) has expanded its presence by up to 100% in increasingly complex search queries. The changes suggest growing confidence in AI for search, with indications that Google is relying on authoritativeness and greater precision in context awareness for matching queries to answers, particularly in relation to content modality.
The data shows that AI Overviews (AIO) has evolved from showing featured snippet style answers to being capable of handling multi-turn, complex search queries. The takeaway is that Google is increasingly comfortable with AI’s ability to surface precise answers for longer queries and this is a trend that may continue to rise.
Google continues to show confidence in their AI Overviews (AIO) search feature as BrightEdge has discovered that more keyword phrases are triggering AI answers now than at any point since the feature was rolled out last year.
25% of search queries using 8 words or more are displaying AI Overviews (AIO), which is a clear upward trend indicating that Google continues to refine the accuracy of AIO and is better able to handle increasingly complex search queries.
A graph shows how the keywords with 8, 9, and 10 words continued to increasingly show AI Overviews
Keyword phrases with less than four words continue to show an increasing amount of AIO but the growth in longer more precise keywords is growing significantly faster.
BrightEdge provided additional data that looks at specific topic categories, showing how queries for some topics consolidating to answers from big brand sites.
For example, in the healthcare category where accuracy and trustworthiness are paramount Google is increasingly showing search results from just a handful of websites. Content from authoritative medical research centers account for 72% of AI Overview answers, which is an increase from 54% of all queries at the start of January.
15-22% of B2B technology search queries are derived from the top five technology companies such as Amazon, IBM, and Microsoft.
BrightEdge data reveals that AIO answers follow certain patterns that reveal qualities that Google feels make content more relevant.
For educational queries AIO shows a preference toward concise answers with a clean visual presentation. In the below example Google is hiding content that has additional information that answers additional questions beyond the main query. This may relate to Google’s information gain patent which is about anticipating additional information that a user will be interested in after receiving the answer to their original search query.
An interesting pattern picked up by BrightEdge is that YouTube technical tutorials have increased by 40% in AIO while health related queries that show YouTube videos are trending downward by 31%.
Of particular interest is that the high volume search queries (100k+ search volume) that trigger YouTube content have decreased by 18.7%. This may reflect a change in user needs and Google’s ability to identify that context and understand that it’s not served well by video content.
What all of this means is that it’s increasingly important to think about context awareness, the appropriateness of the content to the query. The question to ask is what kind of content best serves the context and to expand that answer across modalities like images, sound, video, and text, then within those formats think in terms of how-to, data dump, informative, etc.
BrightEdge observes:
“Most Interesting Pattern:
AI Overviews are developing sophisticated, context-aware citation models. While YouTube citations are declining for health queries (e.g., “symptoms,” “diet”), they’re increasing for technical how-to content, jumping from 2.0% to 2.8% of citations in this category.Pay Attention:
1. Context is King – Focus video content where it’s gaining traction (technical tutorials, DIY) and pivot to text for topics where traditional authority is preferred (health, finance)
2. Match Your Industry’s Pattern – In sectors with distributed authority (like B2B tech at 15-22% per source), focus on direct citations; in consolidated spaces (like healthcare at 72% institutional),partner with established authorities
3. Monitor Actively – With citation patterns shifting dramatically in just one month, weekly monitoring of your space is crucial to spot new opportunities before competitors”
A way to make sense of the data is that it Google AI Overviews appear to be increasingly relying on the authoritativeness of the content as the stakes go higher with more complex search queries.
Authoritativeness isn’t just about being a big brand but it may have to do with simply being meaningful to the Internet audience as a go-to source for a particular topic. Trustworthiness and other related factors are important and this has nothing to do with superficial SEO activities like author bios and so on.
Read the data:
How AI Giants Are Carving Distinct Territory in the Search Landscape
Write a summary for this article using no more than 20 words that would be suitable for a news publication
A new report shows that AI Overviews (AIOs) in Google’s search results are uncommon but significantly affect visibility and user engagement.
Authoritas’s study examines how generative AI Overviews impact organic search performance. In December, the team analyzed search data for 10,000 keywords across seven U.S. industries.
The report highlights the growing impact of AI Overviews and explains trends, user intent, and the search volume levels that trigger AI-driven results.
AI Overviews appeared for 29.9% of the 10,000 keywords studied but made up only 11.5% of the total search volume.
High-volume keywords are less likely to have an AI Overview than mid-range search terms, with monthly search volumes between 501 and 2,400. About 42% of keywords in this mid-range featured an AI Overview.
Takeaway: While AI Overviews are limited in overall presence on search engine results pages (SERPs), they are more common for mid-volume queries. This indicates that there are opportunities in areas with lower competition.
Telecommunications had the highest percentage of keywords linked to AI Overviews at 56%, while Beauty and Cosmetics had the lowest at 14%.
Queries aimed at solving problems or asking specific questions most often triggered AI Overviews at rates of 74% and 69%, respectively.
Conversely, navigational queries, like searching for a specific website, rarely resulted in AI Overviews. This shows that AI Overviews focus on general information rather than direct navigation.
Takeaway: Content that answers questions or solves problems is more likely to appear in AI Overviews. Brands in more straightforward industries should explore topics where complexity or perceived risk drives research.
About 33.3% of non-brand searches show an AI Overview, while only 19.6% of brand searches do.
Brand searches usually happen closer to purchasing, but AI Overviews for informational brand queries can still help shape how people view a brand.
Takeaway: AI Overviews might slow potential customers’ buying process, but they can help influence how users see a brand in the early and mid-decision-making stages.
When you expand the AI Overview on desktop by clicking “Show more,” the page moves down by about 220 pixels. This shift often lowers organic search results on the screen.
On mobile devices, only one or two organic listings are visible without scrolling, making it harder for SEO professionals.
Takeaway: Since AI Overviews occupy significant space at the top of the search results page, brands must find ways to stay visible. They should focus on appearing in the AI Overview’s answer links and the regular organic results below.
High-ranking URLs are likelier to appear in AI Overviews, but this isn’t always true.
About half of the top-ranking pages are included in AI Overviews, and some pages outside the top ten may appear too.
Featured Snippets often coexist with AI Overviews. If you have a Featured Snippet, there’s a better than 60% chance you’ll also be mentioned in the AI Overview.
Takeaway: A high rank or Featured Snippet doesn’t guarantee an AI Overview link, but optimizing for these can improve your chances. To remain competitive, keep producing clear and authoritative content.
Websites known for their expertise, especially in finance and healthcare, are commonly included in AI Overviews.
In contrast, despite having strong rankings in search results, sites like Reddit and Quora are mentioned less often in AIOs.
Takeaway: Websites with reliable voices, verified information, and trustworthy content will likely be cited in AI Overviews.
AI Overviews are still relatively new, but their impact is significant, especially for common or problem-solving questions.
If your website is in an industry requiring detailed research or high stakes, you may see more AI Overviews and tougher competition for top citations.
Even if you don’t see many AI Overviews in your area now, this could change as Google improves its language models and collects more user information.
For SEOs and advertisers, there are two main concerns:
The complete study and accompanying whitepaper offer more granular insights into the appearance of AI Overviews.
Google’s John Mueller shared Jeffrey Zeldman’s Bluesky post reminding publishers and SEOs of proper alt text usage, including a link to the W3C decision tree for guidance. The most important takeaway is that the decision process for alt text is not primarily an SEO decision.
The W3C (World Wide Web Consortium) is an international standards making body for the Internet. A lot of the guidance that Google provides about how Googlebot crawls HTML and treats server response codes are based on the web standards developed by the W3C, so it’s always a good idea to go straight to the source to understand exactly how to deploy HTML (like alt text) because doing it the right way will very likely align with the same standards that Google is using.
A decision tree is basically a decision making tool or diagram that asks a yes or no question. If the answer is “no” then the tree leads to another branch. Answering “yes” leads to a node that advises on what to do. The purpose of the W3C Alt Text decision tree is to guide publishers and SEOs on the proper use of alt text, which is for accessibility.
The decision tree that Zeldman linked to has five questions:
John Mueller did a repost on Bluesky with the additional insight that the decision making process for alt text is not “primarily” an SEO decision, meaning that accessibility should be the first consideration when deciding how to use alt text.
This is what John Mueller said about alt text:
“The choice of ALT text is not primarily an SEO decision.
If you like working with structured processes, check out, bookmark, share, and use this decision tree of when & what to use as ALT text, when it comes to accessibility.”
Zeldman’s post praised the simplicity of the decision tree:
“So straightforward, so good. An ALT text decision tree. “
Someone else posted a link to an interactive version of the decision tree called the “Alt text decide-o-matic” which is a different way to interact with the decision tree.
Check out the W3C Alt text decision tree here or try the decide-o-matic to become better acquainted with alt text best practices and become a better SEO and publisher in the process.
Featured Image by Shutterstock/Master1305