Diving into the world of SEO can be exciting yet overwhelming. As someone early in their SEO journey, I’ve realized the importance of grasping the business context, mastering search intent, understanding technical basics, and conducting hands-on research before jumping into using AI tools.
Working in SEO means constantly staying on top of trends in a fast-paced, marketing-focused industry. When I started, it often felt like navigating without a map. However, establishing a strong foundation made all the difference.
SEO is multifaceted, with specializations emerging as one advances in their career — including local, technical, content, and more. However, as a newbie, I found it beneficial to first gain a broad understanding of SEO before delving into specific areas.
1. Start with the Business
When I begin an SEO project, whether in-house or at an agency, it’s tempting to jump straight into optimizing meta tags or backlinks. But instead, I’ve learned to start by thoroughly understanding the business itself.
Key questions I consider while exploring the website include:
What product or service is being offered?
Who is the target audience?
What sets the company apart from its competitors?
If I get the chance, I always ask broader questions about the company’s goals and plans to better tailor my SEO strategies.
2. Be Curious, Ask Questions
SEO touches nearly every aspect of digital marketing, making curiosity a critical trait. I continuously ask questions not only to expand my understanding but also to foster collaboration with other departments.
Asking questions, no matter how basic they seem, is a great way to learn quickly and thoroughly.
3. Build from the Foundations of SEO
Starting with basics like understanding website fundamentals and how Google displays search results was crucial for me. Analyzing competitors’ search rankings provided practical insights and helped improve my SEO strategies.
Trying simple exercises, like comparing search results with current page optimization, helped me identify areas for improvement and align more closely with what Google values.
4. Get Technical and Network with Developers
While diving into the technical side of SEO can seem daunting, I found learning from developers to be incredibly rewarding. Building these relationships opened doors for deeper technical insights and support.
Coding courses and personal projects enabled me to enhance my technical skills at a comfortable pace.
5. Familiarize with Google’s Search Features
The evolution of Google’s search result presentations introduced me to a diverse range of features, challenging my ability to optimize different types of content effectively.
Understanding these features not only enhanced my SEO approach but also kept my strategies aligned with Google’s user-focused developments.
6. Understand Query Intent
Grasping the varying intents behind search queries allowed me to create content that aligns more closely with user needs, improving engagement and relevance.
Using Google’s guidelines to classify intents significantly refined my keyword strategies and content planning.
7. Conduct Research Independently Before Using AI
While AI can streamline SEO tasks, I’ve found invaluable learning by initially executing projects manually. This hands-on experience has been critical to my strategic development and understanding of SEO complexities.
Resisting the allure of AI solutions early on helped me build a solid foundation that AI could later enhance without overshadowing the fundamentals.
8. Know How GEO/AEO Differs
Understanding the distinctions between traditional SEO and emerging channels like GEO/AEO has equipped me to advise on brand visibility throughout diverse platforms and optimize accordingly.
Exploring how LLMs work, their training data, and how to effectively influence their output, has added a strategic layer to my SEO toolkit.
Laying the Groundwork for SEO Success
By focusing on the core elements of business understanding, search results, and user intent, I’ve laid a robust foundation that continuously supports my SEO growth and adaptability.
Engaging deeply with the basics has empowered me to navigate the complexities of SEO strategically and effectively.
I’ve realized that many of us, myself included, might be tracking the wrong SEO metrics lately. We need to shake things up, especially with 2026 approaching.
Picture this: I present an impressive chart depicting a 47% increase in site traffic. But instead of excitement, I’m met with puzzled looks from the CMO, wondering why revenue remains stagnant. Or, I celebrate a top-three ranking for a keyword nobody searches for.
The SEO metrics that boosted my confidence back in 2019 might just be steering me wrong in 2026. With AI Overviews taking over search results and zero-click searches becoming the new standard, clinging to outdated metrics might jeopardize my strategy and budget.
I’m ready to take you through the precise metrics that our SEO team should retire and which new, revenue-focused metrics to prioritize instead.
Traffic Metrics
1. Organic Traffic
Organic traffic has been my go-to KPI in SEO reports ever since I started. But relying solely on it doesn’t provide enough context.
Not all traffic is equally valuable. A thousand visitors who bounce instantly are not beneficial. However, a hundred visitors converting at an 8% rate? That’s a success story.
I witnessed a local HVAC company whose traffic dropped by 22%, year on year. Panic, right? Yet, organic revenue increased by 31%. We focused on enriching high-intent service pages, pruning low-intent content. Fewer visitors, but better ones.
Before panicking over traffic drops, I always reassess where traffic is declining. If losses involve informational articles and customer login pages, it’s not a revenue issue. That’s just noise exiting my dashboard.
2. Total Impressions Without Intent Segmentation
This metric can mislead. A million impressions from merely informational queries like “what is SEO” might build some awareness, but they contribute zero revenue. Meanwhile, ten thousand impressions from business-driven queries like “best enterprise SEO agency” could significantly boost my pipeline.
Google Search Console offers this data, but many teams, myself included, often fail to segment it intelligently.
3. Traffic Growth Without Revenue Correlation
This is a risky trap for SEO teams. Bringing a 35% increase in organic traffic to a quarterly review sounds impressive, right until the CFO asks, “And how does this translate to revenue?” If I can’t answer that, I’m just reporting noise.
Ranking Metrics
4. Average Keyword Position
This metric might look compelling in a dashboard, but it doesn’t hold up under scrutiny. If I rank first for a keyword with ten monthly searches and fiftieth for one with 50,000, my average position might seem okay, but I’m losing where it matters most.
The average position treats all keywords as identical when they aren’t. With personalized search results, an “average position” can vary greatly by user and location.
5. Isolated Keyword Tracking
Searchers these days don’t typically use isolated keywords. They pose questions, explore themes, and adjust their queries. Google’s focus has shifted toward semantic search and topic modeling.
Tracking a solitary keyword like “lawyer” is pointless without understanding intent — are searchers interested in criminal defense, divorce services, or merely looking up what lawyers do?
6. Share of Top 10 Rankings
This metric sounds clever until it’s clear that 80% of my top-10 rankings might involve low-intent, low-volume queries. Meanwhile, competitors claim the top-three spots for crucial commercial queries in my niche.
Achieving a No. 1 ranking for a high-converting transactional keyword is more valuable than holding 50 top-10 positions for low-value informational queries.
Authority and Engagement Metrics
7. Domain Authority and Domain Rating
DA and DR might not align with Google’s metrics. They’re proprietary scores from SEO tool companies. Yet, teams often set misguided goals like boosting DA from 42 to 50 by Q3.
I’ve seen how backlink volume is often overrated. Google’s algorithm prioritizes link quality, relevance, and context over sheer volume.
A single link from a high-quality, relevant site outweighs hundreds of low-grade directory links. I’ve seen sites with 100,000+ backlinks struggle to rank for meaningful terms because most links lacked quality.
9. Bounce Rate
I’ve found bounce rate misunderstood for years. If someone searches for my company’s business hours, finds them on the contact page, and leaves, that’s a success with a 100% bounce rate.
Google replaced bounce rate with “engagement rate” in GA4 for a reason. Similarly, session duration and pages per session need context. A high pages-per-session score on my pricing page may indicate confusion, not engagement.
Why These SEO Metrics Are Failing Now
I’ve noticed the search landscape shifting quite a bit. Up to 58.5% of U.S. and 59.7% of EU Google searches now conclude without a click, as per SparkToro’s zero-click study. This means, for every 1,000 searches, only 360 result in a visit to a site.
AI technologies are capturing and synthesizing information, bypassing the need for a click. My content can gain visibility and influence without contributing to sessions in Google Analytics.
Wynter’s latest B2B buyer research indicates nearly 24% of CMOs now utilize AI tools like ChatGPT for research, a significant rise from last year.
Buyers discover brands via AI tools and use Google to validate those discoveries. This alters my SEO focus from merely driving traffic to ensuring my brand is visible during pivotal decision-making stages.
Modern customer journeys can be erratic. Often, users who initially find us through organic search might return through paid ads or direct links. If we use last-click attribution, the true value of SEO is obscured, although this organic start was critical for conversion.
For ecommerce, I aim to track revenue from organic sessions by product category and landing pages. For lead-generation, I’ll track how many leads convert to customers. Integrating with a CRM helps in connecting those dots.
No one’s interested in your DA if you can demonstrate $1.2 million in revenue attributed to organic channels.
Conversion-weighted Visibility
I’ll focus on visibility for high-value terms that lead to conversions.
A franchise client noticed they dominated low-intent queries but were invisible for crucial local terms. We adjusted priorities, and their qualified leads doubled in four months.
Topic Cluster Performance
This metric supersedes individual keyword rankings. Monitoring how I rank across full topic clusters, and the aggregate visibility and conversions from these clusters, gives a comprehensive view of topic authority.
SERP Real Estate Ownership
By gauging control over the entirety of search pages, not just listings, including snippets and local packs, I can effectively keep competitors at bay for crucial queries.
AI Platform Visibility and Brand Mentions
My focus will also be on how frequently my brand is mentioned in AI responses. Mentions are becoming as crucial as click-through rates.
For instance, if I secure a favorable recommendation rate across multiple AI platforms for vital topics, it’s a win, even if website traffic appears unchanged.
While tools are emerging to monitor this, manual spot checks can reveal valuable insights, enhancing authority and awareness, eventually leading to brand searches and conversions.
Branded Search and Direct Traffic as AI Visibility Proxies
I notice when buyers find out about my brand through zero-click searches, they often search the brand name directly instead of clicking through. This reflects in my branded and direct traffic rather than organic metrics.
If I see no change in nonbranded organic traffic but an increase in branded search and direct visits, it usually indicates that my content gains attention in AI Overviews.
How to Transition My Reporting
Revamping reporting around new metrics might feel daunting. Stakeholders are comfortable with old metrics.
I start by evaluating my current dashboard, ensuring relevant metrics face business outcomes directly rather than just tallying activities.
Transition by gradually omitting vanity metrics. If organic traffic was my focal KPI, I now introduce it segmented by intent and accompany it with organic-attributed revenue. Gradually, I pivot focus and phase out the dated metrics.
When I introduce new metrics, I frame them in relatable terms. Avoid using “conversion-weighted visibility.” Opt for “visibility metrics for top-converting terms.”
The Metrics That Prove SEO’s Value
The metrics we’ve relied upon — organic traffic, average keyword position, domain authority, bounce rate — aren’t inherently harmful. They’re just incomplete, providing a potentially false sense of security while others prioritize revenue-generating metrics.
Newly adopted metrics — revenue contributions, conversion-oriented visibility, topic authority, SERP dominance, AI platform mentions — directly relate SEO to tangible business outcomes. They prove ROI, justify budgets, and align strategies with business growth.
Consider which metrics in your dashboard lend false impressions of activity over effectiveness. Retire them. Replace them.
Ultimately, no one’s concerned with traffic numbers or DA scores. They want to know if SEO drives growth. Make sure your metrics affirm it.
I’ve discovered how essential it is to integrate trusted search intelligence across our enterprise. With the Conductor Data API, we’re extending these capabilities in ways I hadn’t imagined.
Seeing our data work harmoniously across platforms feels transformative, allowing us to leverage AI infrastructure like never before. This powerful insight has reshaped how we view our enterprise integration strategies.
When I first stumbled upon the concept of query fan-out, I realized how misunderstood it often is in the world of AEO and SEO. It’s fascinating how AI searches can take a single prompt and transform it into numerous sub-queries, expanding the scope of search in unimaginable ways.
Understanding this process opened my eyes to the hidden potential these sub-queries hold. By leveraging the data generated from them, I discovered new strategies to enhance SEO effectiveness, making my digital marketing efforts more robust.
I recently came across a fascinating Datos/SparkToro report revealing a significant change in our search habits. It’s no surprise that U.S. Google users are searching less than they did a year ago. While Google isn’t losing users, it’s clear they’re experiencing fewer repeat searches.
Why this matters to me. Google still reigns supreme in the search world, but fewer searches mean dwindling opportunities for clicks, ads, and traffic—even if the total search volume seems stable.
The numbers speak for themselves. The report showed a nearly 20% year-over-year decline in desktop searches per U.S. user, based on data from millions of users.
This sharp decline is unlike the European trend, where searches only fell by 2-3%.
Despite fewer searches per person, traditional search still constitutes about 10% of all U.S. desktop activity—a share that held steady throughout 2025.
Reasons behind the drop. The rise of AI-powered answers and instant results appears to be the main culprit:
Users now get the information they need without conducting multiple follow-up searches.
Zero-click searches remain high but have leveled off in the low-20% range by year-end.
Little change is observed in repeat searches and clicks within Google-owned properties, hinting at a plateau in user behavior.
The reshaping of search by AI. AI isn’t pulling users away from search; rather, it’s enhancing it. Despite ongoing AI buzz, the report discovered:
AI tools contribute to less than 1% of total U.S. desktop activity (0.77%), though they’ve seen remarkable growth.
Google AI Mode remains small, accounting for about 0.06% of U.S. desktop events by December, with steady adoption increase.
Query evolution. One notable behavior change is how we phrase our searches:
Mid-length queries of six to nine words are increasing rapidly in the U.S.
Very long queries (15 words or more) are still rare but show significant experimentation and volatility.
People seem to find it easier to express complex needs directly in their searches.
Discovery becomes a challenge. With concentrated search-driven discovery, breaking into post-search destinations is tougher:
YouTube, Reddit, Amazon, Wikipedia, and Facebook remain dominant.
ChatGPT soared to No. 7 among U.S. search destinations, a rare significant mover.
Meanwhile, Quora has fallen out of the top 15.
AI’s few dominators. AI-driven traffic largely directs users to already established platforms like Google, YouTube, GitHub, and Wikipedia rather than new or independent publishers. When it comes to AI platforms:
ChatGPT is the leading tool in the U.S., reaching around one-quarter to one-third of desktop AI users.
Google’s Gemini emerged as a strong No. 2, consistently growing throughout 2025 and surpassing DeepSeek.
Other tools like Claude, Perplexity, and Copilot stay niche with modest reach.
Industry insight. Rand Fishkin, co-founder and CEO of SparkToro, highlighted in the report:
“The big highlight here is the decline in # of Google searches/searcher from 2024–2025. It’s a nearly 20% decline in the US, though only 2–3% in the EU/UK. Other studies have shown that Google is sending less traffic than in years past, especially to the long-tail of the web, and I suspect that AI answers have dramatically altered the way many users engage with Google, answering their questions before they ever need to click on an organic result or perform a second/third/fourth search.”
Have you heard the news? Google has just launched the Universal Commerce Protocol (UCP), an innovative open standard that integrates AI agents throughout the entire shopping experience. From discovering products to making purchases and even receiving support after the sale, UCP facilitates it all.
In exciting developments for retailers, Google is also rolling out new AI tools. These include branded shopping agents and ad formats that enhance AI-driven discovery, making the shopping experience more streamlined and engaging.
About UCP
This protocol offers a common language for AI agents and commerce systems, greatly simplifying the need for custom integrations across different platforms.
UCP is compatible with existing standards like Agent2Agent and the Model Context Protocol.
The protocol was co-developed with prominent partners such as Shopify, Etsy, Wayfair, and Target.
It’s already endorsed by over 20 additional companies in the retail and payments sectors.
What’s Changing
The UCP is set to enhance the checkout experience for Google product listings via AI Mode in Search and the Gemini app. Shoppers can make purchases through Google Pay, with options to use saved payment and shipping details. Integration with PayPal is also on the horizon.
Google aims to lower cart abandonment and provide retailers with tailored integration options suited to their needs.
Upcoming features include loyalty rewards and personalized shopping experiences.
Business Agent
In tandem with UCP, Google is unveiling the Business Agent, a branded AI assistant that provides shoppers with direct interaction opportunities on Search. Think of it as a virtual sales associate offering real-time responses in your brand’s own tone.
Major retailers like Lowe’s, Michael’s, Poshmark, and Reebok are already on board. Future capabilities may include deeper customization, data training, and a seamless agent-led checkout.
Direct Offer
Google is also testing Direct Offers, a fresh initiative within Google Ads tailored for AI adoption. When AI senses that a shopper is likely to make a purchase, a special discount can be presented.
This pilot will soon expand to incorporate offers such as product bundles, complimentary shipping, and more enticing incentives.
Why It Matters
The rise of agent-led shopping reshapes where and how buying choices are made. Google’s new AI tools and protocols are taking the lead, allowing advertisers to influence these pivotal moments during an AI-driven shopping journey.
Tools like Direct Offers and branded agents create new pathways for advertisers to finalize sales efficiently, all while safeguarding profit margins. The balance between conversion improvements and losses in direct site traffic remains an open discussion.
Bottom Line
According to Google, agentic shopping is unstoppable. With innovations like UCP and its complementary retail tools, Google ensures that AI-driven commerce remains inclusive and accessible, keeping retailers engaged as agents transform the buying landscape.
AI is changing search visibility, but I’m ready to adapt and thrive by unlocking the potential of my most underappreciated channel: email.
With AI reshaping the landscape of search, I’m learning how to reclaim my reach by tapping into owned audiences and transforming email into a growth engine that scales.
The rules of search have changed, and I can feel the impact on my marketing funnel. Despite pouring countless hours into creating compelling content and refining workflows, it’s frustrating to see my efforts wasted when my audience misses my work.
SEO is seeing diminishing returns, while AI-generated summaries are sidelining my branded content. Metrics reveal a reality I didn’t want to face: it looks as if my marketing team doesn’t exist at all.
Even with constant iterations and innovative ideas, the chances of my audience viewing my efforts seem to dwindle.
The new reality is that organic website traffic isn’t the steady stream it once was. With projections expecting a drop of 25% in search engine traffic due to AI, I must find alternative routes to reach my audience.
B2B SaaS companies, marketing platforms, and content-rich businesses are facing a structural shift, and so am I. My owned audience, like my email list, remains untouched by algorithmic changes and provides a reliable base for reaching customers.
Leveraging my undervalued channel means I have the power to control distribution, timing, and messaging, making email an essential component of my marketing strategy.
Email isn’t just a broadcast channel; it’s a precision tool. I need a disciplined approach to realize its full potential: targeted segmentation, optimized send frequencies, and clear performance benchmarks will guide my success.
To harness the power of email, solutions like Campaign Monitor offer AI-driven capabilities that treat email as the strategic asset it really is. I’m ready to utilize tools like Marketing Monitor to make smarter decisions, track real-time results, and consistently improve my campaigns.
The bottom line? Losing traffic to AI doesn’t just impact me momentarily—it threatens long-term competitiveness. I have two options: absorb the loss or pivot to a diversified strategy. Strengthening my owned audience and modernizing my email approach ensures I’m set to not only stabilize but grow.
I recently explored why my competitors often feature in Google’s AI Overviews while my content doesn’t, and I’ve discovered some strategies to change that.
Understanding the mechanics behind Google’s AI Overviews can give your content a much-needed edge. These overviews are complex algorithms that prioritize well-structured and relevant information.
To improve my content’s visibility, I need to focus on optimizing for AI search by ensuring my content is thoroughly cited and indexed. This requires a strategic blend of content optimization and SEO best practices tailored to AI.
By proactively adopting these strategies and tools, my goal is to enhance my content’s AI visibility, ensuring it gets the attention it deserves in AI-driven search environments.
As I type my search query in Google, I’ve noticed an interesting change. The usual AI Mode button is sometimes replaced by a striking blue ‘Send’ button right in the search box.
Google is currently testing this new feature. Traditionally, the AI Mode button appears on the right side of the search box, but it seems this might be changing. As soon as I start typing, the ‘Send’ button takes its place.
What it looks like. Recently, I came across a post by Shameem Adhikarath, who shared a video of this new feature on X.
From the video, it’s clear that when I start typing my query, the AI Mode, Lens, and Microphone buttons vanish, leaving behind this new blue ‘Send’ button.
Interestingly, the familiar plus sign remains unaffected, sticking around as always.
Why this matters. While this is currently just a test, it could have significant implications. If implemented, it might mean fewer users are directed to Google’s AI Mode, prompting more straightforward searches.
For those of us who rely on AI Mode, this change could make accessing it a bit more challenging, urging us to adjust how we initiate searches.
In a world where Google’s AI Overviews address more queries instantly, I’ve found that vibe coding allows us to craft interactive experiences that AI simply can’t replace.
I’ve noticed that search marketers are now shifting their roles from merely optimizing to actually building. Tools like vibe coding, coupled with AI-powered development technologies, have significantly reduced the time from idea conception to execution—from weeks to just a few hours.
These tools don’t make developers obsolete, but they empower search teams to test and create interactive content on their own timelines. This is crucial, as Google’s AI Overviews increasingly pull answers directly into the SERP, reducing clicks to our brand websites.
For marketers, building unique, conversion-focused tools is becoming an indispensable tactic in this zero-click environment.
What is vibe coding?
Vibe coding is about creating software by guiding AI with natural language instead of traditional coding methods. This means focusing on the tool’s purpose, appearance, and response, while AI takes care of implementation.
This term gained popularity in early 2025, thanks to OpenAI co-founder Andrej Karpathy, who described it as a loose, exploratory building style. The appeal? Speed. The risk? Potential shortcuts that could lead to fragile systems.
Today, AI-powered development platforms extend this approach to non-engineering teams, with tools like Replit and Lovable, allowing everyone to build and iterate quickly.
Vibe coding vs. vibe marketing
It’s important to distinguish vibe coding from vibe marketing. Vibe coding involves AI tools designed to create applications and interactive experiences, whereas vibe marketing uses automation platforms to connect existing tools and systems.
Together, these approaches empower search teams to build and operationalize their creations efficiently.
Why vibe coding matters for search marketing
I believe that soon, AI-powered coding will be an essential part of any marketer’s toolkit. It allows us to create sophisticated interactive tools that Google’s AI can hardly mimic, enhancing our SEO and PPC strategies.
With vibe coding, my team can rapidly develop tools that boost conversion, like interactive content aimed to improve user engagement—a factor crucial for both SEO and PPC efforts.
Through vibe coding, I’ve created custom systems that help manage our operational needs efficiently, saving time and costs. For instance, a project quoted at $55,000 was completed in under a week using Replit for just $20 a month.
The opportunity to teach these skills to clients also adds significant value, emphasizing the transition from “we’ll do it for you” to “we’ll build it with you.”
Vibe coding offers a competitive edge, allowing us to navigate zero-click search environments while fortifying long-term relationships with our clients.
Top vibe coding platforms for search marketers
Several leading vibe coding platforms are making waves. My personal preference is Replit for its flexibility, though Figma Make is a great choice too, particularly as it integrates well with our existing workflows.
Testing different platforms will help find the best fit. Whether it’s Lovable for beginners or Cursor for advanced users, there’s a solution tailored to your needs.
Practical SEO and PPC applications: What you can build today
Vibe coding can create a variety of tools, from lead generation calculators to interactive content that increases website engagement. The key is to build tools that fill existing gaps, providing unique and useful solutions.
For instance, I developed an AI-powered accounting ROI calculator, a tool that couldn’t be easily replaced by Google’s direct answers. This not only helps the target audience but also boosts SEO efforts by encouraging repeat visits.
A 7-step vibe coding process for search marketers
I’ve found that following a structured workflow is crucial when using vibe coding. This includes thorough research, creating a content spec document, and iterating designs before functionality.
These steps ensure a comprehensive approach, allowing for prompt testing and deployment. Updating documentation at each milestone helps in managing future updates or revisions.
The dark side of vibe coding and important watchouts
While powerful, vibe coding tools come with risks. Security and compliance issues, price creep, and technical debt are concerns that require careful attention.
Always ensure security reviews and keep track of costs as projects evolve. Monitoring these risks can make vibe coding a reliable tool rather than a complicated headache.
Vibe coding is your competitive edge
In this evolving landscape, vibe coding gives us the ability to build unique digital experiences. It’s a skill set that empowers us to thrive, helping create meaningful, interactive content that stands out in the crowded search environment.
Embracing vibe coding not only promotes strong client partnerships but also equips us to adapt to new search realities, making it a pivotal skill for future success.
