Search is changing fast. AI answers now pull insights from your content and deliver them directly to users without sending traffic to your site. Your brand may gain visibility while your clicks stay flat. Influence shows up, but attribution does not.

Marketers now need a new way to measure influence. The real task is creating attribution for AI answers that captures visibility and impact before the click.

This article introduces a simple framework built on four essentials: visibility, resonance, impact, and feedback.

Author’s Note

Before we get into it: this chapter is part of my ongoing AEO/GEO series on how content discovery and search behavior is changing, and what you need to do to stay visible on search. If you’d like the fuller foundation, here are the key posts referenced throughout this series:

Foundations of AI Search Behavior

• AEO Maturity Model
• How AI Overviews Impact CTR and SEO
• How Generative AI Is Changing Search Behavior
• The Psychology of Conversational Search
• Mapping Content to User Goals & Intent

AI Retrieval, Ranking & Synthesis

• How Generative AI in Search Works
• Structuring Content for AI Extraction
• Authority Signals & Schema Markup for AEO
• Structuring Content for Multi-Turn AI Conversations

Measuring AI Visibility & Performance

• How to Measure AEO Performance
• Building an AEO-Ready Team

When AI Answers Replace Clicks

Traditional analytics were built for a world where users visited your site to engage with your content. AI has changed that. Much of the interaction now happens off-site, inside AI-generated responses, with little to no trace in your reporting tools.

As generative search takes on more of the work, your content can shape decisions without triggering a single measurable action. The real signals are happening elsewhere, and marketers must account for the influence created before a user ever clicks.

Defining Attribution 2.0: From Traffic to Influence

Traditional attribution measures movement like clicks, pageviews, sessions. But today, influence often comes first, which means attribution should be about understanding and tracking momentum. It should be about seeing how ideas spread, how your brand authority grows, and how your content shapes perceptions before any measurable action occurs.

Marketers must then focus on how AI represents and amplifies content. Every summary, recommendation, or synthesized answer powered by AI can extend reach and impact, often without a direct click. 

Understanding how these systems interpret and showcase your content allows marketers to map influence across the broader ecosystem: capturing visibility, authority, and engagement that traditional analytics would otherwise miss.

The Framework: Measuring Influence in the AI Ecosystem

Measuring influence in the AI ecosystem means looking beyond traditional metrics. This framework focuses on four key dimensions: visibility, resonance, impact, and feedback.

Layer 1: Visibility

Visibility in this era is not just about showing up in the search results anymore, rather about how often your brand or content is noticed or referenced within AI-generated outputs. The goal here is simple: see if your ideas are being seen and recognized, even when users don’t click through to your site.

1. Audit your AI presence. Regularly search your brand, products, and key content topics across AI engines like ChatGPT, Gemini, Perplexity, Claude, and Copilot. Record where your content is mentioned, summarized, or notably absent to understand how AI systems are interacting with your content.
2. Track citations. Use LLM visibility trackers, or set up alerts for AI-generated mentions. These tools show when large language models (LLMs) such as ChatGPT, Gemini, Claude, or Perplexity reference your brand, cite your content, or recommend your products. This helps you understand where, how, and how often your brand appears across AI-generated answers. Some of the leading LLM visibility trackers available include:
   1. SE Ranking – combines traditional SEO tools with AI search monitoring. Its AI Search Toolkit tracks brand mentions, positions, and competitors across platforms like ChatGPT and Google AI, giving a clear view of your AI-driven presence.
   2. Ahrefs Brand Radar – shows how AI chatbots represent your brand across platforms like ChatGPT, Google AI, Perplexity, Gemini, and Microsoft Copilot. It helps businesses monitor AI mentions, benchmark against competitors, and uncover opportunities to strengthen their presence in AI-generated search results.
   3. Profound AI – provides advanced insights into how AI interprets content and optimizes product placement, helping companies achieve significant visibility growth in AI-driven search environments.
3. Enhance discoverability. Improve your content’s likelihood of being cited by implementing schema markup, ensuring factual clarity, and optimizing key entities. Clear, structured content helps AI models confidently reference your brand.
4. Benchmark visibility. Develop a monthly “AI Share of Voice” score that tracks the percentage of AI-generated answers where your brand appears for target queries. This provides a measurable way to monitor your growing influence over time.

Visibility is the first step in building influence. If AI systems don’t surface your content, it can’t shape decisions or guide conversations. 

Layer 2: Resonance

Visibility alone is not enough; your content also needs to resonate. Resonance is all about how your brand is understood and remembered. And in the world of AI, that means measuring whether AI systems cite your brand positively, accurately, and frequently, in a way that carries meaning and relevance.

Tracking resonance means looking at how frequently your content is used in AI outputs, whether it’s summarized correctly, and if the core ideas are preserved and represented effectively.

1. Monitor branded search volume. Track increases in searches for your brand or products using tools like Google Trends and Google Search Console. Look for correlations between AI-driven visibility spikes and upticks in search interest to see if AI exposure is influencing awareness.
2. Measure sentiment. Analyze the tone of conversations about your brand using social listening tools or AI-driven sentiment analysis platforms. Monitoring sentiment before and after major AI visibility events helps you understand how your brand is perceived and whether AI references are building positive authority.
3. Survey recall. Conduct periodic audience surveys or polls to measure unaided brand awareness within your category. Understanding how well your brand sticks in users’ minds provides a direct signal of resonance and influence.
4. Create a “Resonance Dashboard.” Combine sentiment, branded search data, and social conversation metrics into a single composite Influence Score. This view will allow marketers to track how effectively AI-driven visibility is translating into brand recognition, perception, and authority over time.

Paying attention to signals like citation frequency, sentiment, and source trust can let marketers start to understand not just if they’re being referenced, but how they’re being referenced. This helps monitor whether the brand is resonating in the AI conversation, building authority in ways that may not show up in clicks or pageviews but are essential to long-term influence.

Layer 3: Impact

Visibility and resonance are powerful on their own, but their true value shows when they translate into meaningful business outcomes. Impact is where AI-driven presence moves beyond awareness and perception, shaping real decisions, behaviors, and conversions. This is the stage where marketers look for proof that being cited, recommended, or surfaced by AI systems is driving tangible value: more qualified traffic, stronger leads, higher engagement, or even direct revenue lifts.

1. Run correlation analysis. Compare periods with high AI visibility against shifts in website traffic, conversions, lead quality, or pipeline growth to identify relationships between AI exposure and business performance.
2. Define proxy conversions. Track secondary indicators of influence such as increases in branded organic searches, direct type-in visits, social engagement, or repeat interactions, to capture the impact that happens before a user ever clicks.
3. Implement attribution modeling. Use regression, media mix models, or Bayesian inference to estimate the indirect contribution of AI-driven exposure, giving you a clearer picture of influence that isn’t captured by last-click metrics.
4. Report “Influence-Weighted ROI.” Layer your traditional ROI or ROAS with an influence multiplier based on inferred impact from AI visibility and resonance, creating a more complete assessment of how AI contributes to revenue and brand growth.

It’s not just about being seen or remembered by AI. It’s about whether that exposure changes what people do. When you tie AI visibility and resonance back to these measurable outcomes, you can clearly see how influence is contributing to your business growth.

Layer 4: Feedback

Influence is not a one-time achievement; it’s a cycle. And feedback is where true influence takes shape. It becomes the engine that keeps your visibility, resonance, and impact evolving. 

As AI systems adapt based on patterns, signals, and relevance, marketers must do the same. Take insights from AI mentions, audience reactions, and performance indicators, then feed them back into the content strategy to strengthen the signals that guide how AI engines interpret your brand. 

1. Map success signals. Identify which types of content (whether they are guides, data-backed studies, FAQs, or definitions) appear most frequently in AI-generated answers. This helps you understand what formats and topics AI engines perceive as most authoritative.
2. Strengthen high-performing entities. Identify the people, products, locations, or concepts that AI already associates with your brand. Expand these pages, improve internal linking, and reinforce supporting content so AI models develop an even stronger, more consistent understanding of these entities.
3. Improve factual density. Refine your top-performing content to be clearer, more concise, and richer in well-structured information. AI models favor content that’s easy to parse and confidently cite, so improving clarity and accuracy increases your chances of repeated inclusion.
4. Close the loop with regular audits. Refine your top-performing content to be clearer, more concise, and richer in well-structured information. AI models favor content that’s easy to parse and confidently cite, so improving clarity and accuracy increases your chances of repeated inclusion.

Influence is supported through repetition, clarity, and constant improvement. And feedback is the mechanism that keeps your authority alive, relevant, and growing.

Operationalizing the Framework

Putting the framework of measuring influence in AI into action simply means integrating each layer into what you already do. Visibility, resonance, impact, and feedback can be layered directly onto the processes you already use, transforming traditional analytics into a more adaptive, AI-aware discipline.

1. Create a unified “AI Attribution Dashboard” that combines key metrics from all four layers (visibility, resonance, impact, and feedback) into a single dashboard. Include AI mentions, sentiment analysis, and conversion or proxy data to create a holistic view of how your content is performing in AI-driven environments.
2. Set quarterly KPIs. These benchmarks provide clear targets and allow your team to gauge the effectiveness of their efforts. Define measurable goals to track progress over time such as:
   1. Increasing your “AI Share of Voice” by 20%
   2. Improving your overall Influence Score by 15%; or
   3. Achieving a 10% lift in traffic correlated with AI visibility. 
3. Align cross-functionality. Bring together SEO, content, brand, analytics, and communications teams to agree on influence metrics, share insights, and coordinate actions. Cross-functional collaboration ensures that AI attribution becomes a shared responsibility.
4. Document assumptions. Treat your AI attribution model as iterative. Clearly note any assumptions, such as how AI visibility or resonance is weighted, and refine these metrics as transparency and data from AI platforms improve. This approach keeps your model accurate and adaptable.
5. Educate stakeholders with influenced-based storytelling. Shift the narrative from traditional traffic- or click-focused reporting to one that emphasizes influence. Explain how AI visibility and resonance drive authority, shape perception, and contribute to measurable outcomes, helping them understand the full value of your AI-optimized content.

Integrating these steps into your regular workflow lets businesses create a system that consistently measures how AI represents a brand—and continuously improves the presence in AI-generated answers. This approach keeps your strategy adaptive, measurable, and aligned with how people now discover information.

Key Takeaway

The marketing landscape is shifting dramatically—from clicks to credibility, and from sessions to significance. Traditional metrics can no longer capture the full story of influence in an AI-driven world. Visibility, resonance, impact, and feedback provide a modern framework for understanding how your content shapes perception, builds authority, and drives results even when users never click.

In the age of AI answers, the brands that win are those that are recognized, referenced, and trusted. Influence now extends beyond what is seen on the page; it exists in the moments AI surfaces your expertise and shapes decisions.

The challenge for marketers is clear: measure the unseen, track the indirect, and embrace a new standard of attribution that values influence as much as traffic. Those who do will lead the way in defining success for the AI era.

The post Attribution in the Age of AI Answers appeared first on SEO Services Agency in Manila, Philippines.

As search engines evolve into AI-driven search ecosystems, the old ways of measuring performance are starting to fall short. Metrics like clicks and impressions only show part of the story. They don’t reveal how your content actually shows up, educates, or engages within AI-generated results.

That’s where Answer Engine Optimization (AEO) comes in. AEO shifts the focus from surface-level stats to a deeper understanding of how your brand appears and is referenced in AI summaries, chat-based answers, and contextual responses. It’s a new way to evaluate visibility and influence in a world where generative search is rewriting the rules.

The real question today isn’t “Do I rank?” — it’s “am I seen and cited by AI” This layer of search is fluid and unpredictable; mentions can appear or vanish depending on small changes in user intent, phrasing, or the model’s retrieval logic. Mastering AEO means learning to navigate that shifting terrain and ensuring your brand stays visible within it.

Author’s Note:

This article is the eighth entry in my AEO/GEO series, which explores how websites can keep up with new search ecosystems. If you’re new to the series, I recommend starting with the earlier pieces to understand how AI-driven retrieval, synthesis, and citation are reshaping the fundamentals of SEO.

Catch up on the series:

• How AI Overviews Impact CTR and SEO – How Google’s AI-generated results are changing click behavior and rankings.

• How Generative AI Is Changing Search Behavior – Why people search differently in the age of AI and what it means for your strategy.

• Mapping Content to User Goals – How to align structure and messaging with user intent to improve engagement.

• How Generative AI in Search Works – A breakdown of how large language models (LLMs) retrieve, rank, and synthesize information.

• Structuring Content for AI Extraction – A practical guide on formatting content so AI systems can easily parse and reuse it.

• Using Authority Signals and Schema Markup for AEO Success – How structured data and expert attributions help AI trust and cite your content.

• How to Structure Content for Multi-Turn Conversations in AI Search – How to design and organize your content so it remains relevant and referenced across multi-turn AI interactions.

Moving Beyond Traditional SEO Metrics

Search is no longer just about ranking on page one. It is now about being part of the answer. Answer Engine Optimization, or AEO, takes optimization a step further by making sure that your content is not just for improving search engine visibility, but for inclusion in AI-generated answers that directly respond to user queries as well. 

Also, with AI-driven search experiences now, the search journey has transformed: users are no longer just searching, they are conversing. These platforms then curate and deliver quick, summarized, and context-rich responses directly within the results without always requiring a click to visit a website. 

Visibility now means more than appearing in search listings. It’s about being cited and recognized by the very AI models shaping what users see and trust, and these have become just as valuable as traditional organic rankings, signaling a shift in how we define engagement and discoverability.

As search becomes more intelligent, success now is not measured by clicks alone. A website may experience fewer visits, yet achieve greater reach and influence by being referenced or featured within AI answers. 

To understand how to measure AEO success, we need to recognize the limitations of current analytics, define the right metrics, and track how our content appears, contributes, and delivers value across the AI-powered search ecosystem.

The Limitations of Click-Based Metrics

Generative search experiences are is reshaping how people look for and receive information. Users now receive AI-generated answers instantly, often without visiting a website. As a result, traditional organic funnels are showing fewer clicks, even when overall visibility and influence may be increasing.

A decline in traffic doesn’t necessarily mean a decline in reach. Content that is cited, summarized, or referenced within AI-generated responses still reaches a wide audience. These mentions strengthen brand authority and awareness, even among users who never leave the search results.

Current analytics platforms are not yet equipped to measure this new layer of visibility. Google Analytics can track traffic from search, but it cannot distinguish between a visit from a traditional link and one originating from an AI Overview. Google Search Console provides impressions and clicks but offers no insight into whether your content was used to inform a generative summary.

This presents two key challenges. First, the generative answer layer remains invisible to most analytics tools. Second, even when visibility can be detected, it is often unstable — a query that cites your content today may produce different results tomorrow, even without changes to your site.

For SEO and AEO professionals, the next step is to develop new measurement frameworks that uncover this hidden layer, track performance over time, and connect these appearances to meaningful business outcomes such as engagement, brand recognition, and trust.

AEO Performance Indicators

Measuring AEO success requires a wider lens than traditional SEO metrics can provide. Clicks and impressions alone no longer capture the full story of visibility in AI-driven search. To understand how to measure AEO performance, brands need to track new indicators that reveal how content performs beyond the click.

AI Impressions

AI impressions reflect how often your content or brand appears within AI-generated summaries or conversational responses, even when it isn’t directly linked or quoted. They are similar to traditional SEO impressions, but with a crucial difference: they measure how frequently your content becomes part of the AI-generated answer itself.

This metric highlights when your content is recognized and surfaced by AI systems, boosting brand exposure even without a click. Each mention within an AI Overview or generative search result signals that your content is being treated as a reliable and contextually relevant source, trusted by both users and the AI models delivering the results.

Tracking AI impressions is still an emerging practice as generative search technology continues to evolve. 

However, there are a few practical ways to start gathering insights: 

• Monitor visibility within AI overviews through early access tools or beta reports, such as Google Search Console’s SGE experiments (when available).
• Use third-party SEO platforms that are beginning to introduce generative search tracking, detecting when your content appears in AI summaries or overviews.
• Set up brand and content mention monitoring to identify instances where AI systems reference or summarize your content across different platforms.

Understanding where your content surfaces requires a closer look at how AI search interfaces work. AI Overviews usually appear as embedded panels within a standard search results page, triggered for queries where Google determines a synthesized answer would be useful.

Within it, you can search for anchor tags pointing to your domain or textual overlaps with your content. However, because these panels change dynamically with user context, model updates, and testing conditions, a single spot-check provides only a snapshot. Long-term tracking is necessary to build an accurate picture of your visibility trends.

Meanwhile, AI Mode introduces a more conversational environment. Unlike static summaries, it generates multi-turn responses designed to engage users in dialogue. As a result, the retrieval patterns are broader and more reasoning-driven, often drawing from different sources than AI Overviews. 

Measuring your presence here requires capturing the entire conversational output and identifying every linked or referenced source. Comparing results between AI Overviews and AI Mode can reveal content biases, preferred sources, and topic coverage gaps that influence how often your content is selected.

A practical way to quantify your visibility is through AI share of voice. For instance, if you track 100 keywords, and find that AI Overviews appear in 25 of them, and your content is featured in 10, your AI share of voice is 10%. 

This metric establishes a baseline for understanding how frequently you appear across generative search experiences. Over time, tracking this percentage helps measure the impact of your optimization efforts and identify opportunities to strengthen your presence within the evolving AI-driven search ecosystem.

Summary Inclusions

Summary inclusions highlight how often your brand or content is directly cited within AI-generated answers, whether in Google’s AI Overviews or other generative platforms. It serves as a measure of authority, relevance, and credibility, showing that AI not only recognizes your content but also trusts it enough to include it in its response. 

The more frequently your brand is referenced in these summaries, the stronger your visibility and trust become in the eyes of both algorithms and users. 

Monitoring summary inclusions provides valuable insight into how effectively your content aligns with what AI deems useful and reliable. 

However, tracking for AI overviews and on AI mode is primarily manual for now, as most analytics platforms are still adapting to AI-driven search reporting. Some practical ways to monitor when your content is being cited or referenced in AI-generated summaries include:

• Manually monitor AI-generated results for your target keywords using tools like Google’s SGE or Bing Copilot to see if your content is cited or linked in summaries.
• Use third-party tracking tools that are beginning to offer generative search visibility features, which detect brand mentions or links in AI overviews.
• Set up brand and URL mention alerts through platforms like Google Alerts or Mention to capture instances where AI-generated content references your site. Though these tools don’t yet directly track AI results, they can still monitor where and how your brand or content is being referenced online, which can indirectly indicate when AI systems are pulling information from your site.
• Document and compare appearances over time to identify trends in how frequently and where your content is being featured in AI answers.

Conversational Engagement

Conversational engagement is another AI performance indicator that reflects how actively users interact with your brand within AI-powered chat experiences. 

Rather than simply appearing in an AI-generated summary, this metric measures the depth of interaction: how often users mention your brand, ask follow-up questions, or continue queries related to your offerings. 

And in tracking metrics for conversational engagement, here are a few effective ways to monitor how users interact with your brand within AI chat environments:

• Track branded follow-up prompts. Observe how often users continue the conversation with additional questions or prompts that mention your brand. This is done by manually testing AI chat interfaces (like Google’s SGE or ChatGPT) using your key topics or brand-related queries, then noting if the AI generates follow-up suggestions or if your brand reappears in subsequent dialogue threads.
• Monitor repeated mentions in AI chat threads. Identify instances where your brand or content is referenced multiple times throughout a single AI interaction. You may test queries around your target keywords and observe whether the AI continues to cite or mention your brand across follow-up responses. Consistent repetition indicates stronger brand association and relevance within conversational contexts.
• Analyze rephrased or expanded branded queries. Look for users who refine or restate their questions involving your brand, showing deeper curiosity or intent. Experiment with variations of branded queries in AI chat interfaces and note if the system continues to associate your brand with related topics or reintroduces it in expanded answers.

Take this exchange I had with ChatGPT as an example:

SEO Hacker was mentioned in both the first and second answer, which means that we are possibly getting multiple brand mentions even throughout follow-up prompts from users. 

Dwell Time and Content Interaction

Dwell Time and content interaction measure what happens after visibility: how long users stay and engage once they reach your content through AI-driven results. Even in an AI-first search environment, time spent reading or interacting with your page remains a powerful indicator of relevance and satisfaction.

In hybrid search experiences where users discover information through both SERPs and AI overviews, higher dwell time signals that your content not only earned visibility but also fulfilled user intent — proving its depth, usefulness, and credibility in the moments that matter most.

While AI platforms don’t yet provide direct analytics, there are ways to measure these AI performance indicators:

• Use Google Analytics or GA4. Monitor average engagement time and scroll depth for pages frequently surfaced in AI results.
• Track referral sources. Identify sessions that originate from AI-driven search experiences (like Google’s SGE or Bing Copilot) if labeled in traffic sources.
• Analyze session duration trends. Look for increases in on-page time or interactions (clicks, video plays, form fills) on content recently appearing in AI overviews.
• Observe behavioral flow reports. See whether users explore additional pages after landing on your site, which may indicate that AI-driven visitors find the content relevant and worth exploring.

These insights help you gauge whether your content is simply being seen, or genuinely engaging users who arrive through AI-enhanced search experiences.

AI Bot Activity

One of the most overlooked signals of visibility is bot activity. Tracking how often AI-related crawlers visit your site can help you understand how frequently your content is being indexed, retrieved, or evaluated for use in generative search results.

Bots such as ChatGPT-User, ClaudeBot, or PerplexityBot regularly scan or request web pages to collect information or serve user queries. A consistent crawl rate typically indicates healthy visibility, while a sudden decline could mean your site has been deprioritized or excluded from certain retrieval pipelines. 

By reviewing server logs or bot analytics, you can spot potential issues before they show up in your downstream performance metrics.

Common AI Bots to Track

Below is a summary of major AI crawlers, what they do, and how to manage their access:

How to Measure AEO Performance 

Understanding AEO performance indicators is only the first step. The real impact comes from turning insights into measurable action, which requires a structured approach.

Tracking key metrics such as AI impressions, summary inclusions, conversational engagement, and dwell time involves creating dashboards that will give you a clear picture of how your content performs in AI-driven search environments. 

Identify Key AEO Metrics

Start by determining which performance indicators matter most for your goals. Focus on metrics such as AI impressions, summary inclusions, conversational engagement, and dwell time. These metrics capture your overall AI-driven search presence.

Combine Active and Passive Tracking Methods

Measuring performance in Answer Engine Optimization (AEO) requires using both active and passive tracking approaches. Together, they help capture the full spectrum of visibility, engagement, and authority signals that reflect how your content performs within AI-driven search environments.

Active tracking involves hands-on observation of where and how your content appears within generative search results. 

This can include running your target keywords in tools such as Google’s Search Generative Experience (SGE), documenting when your brand or pages are mentioned, and testing branded variations of your queries to identify follow-up prompts and conversational references. 

Regular testing helps uncover new opportunities and spot shifts in AI-driven ranking behavior.

Passive tracking, by contrast, collects data automatically through system logs and analytics platforms. 

This approach reveals how users and AI systems interact with your content behind the scenes. By analyzing server logs, you can see when AI crawlers fetch your pages, how frequently they return, and whether those visits change over time. 

Combined with analytics data—such as dwell time, engagement rates, and interaction patterns—passive tracking gives you a deeper view of how your content performs once it’s surfaced by AI systems.

Modern SEO and analytics tools are beginning to offer specialized features for AEO tracking. Platforms like SE Ranking’s AI Search Toolkit can help you:

1. Monitor when and where AI tools mention your brand or link to your pages.
2. Identify visibility gaps and opportunities across multiple AI search engines.
3. Compare your domain’s inclusion rate and brand mentions against competitors.
4. Review how AI-generated answers reference your content for specific prompts.
5. Evaluate and benchmark overall AI search visibility across multiple domains.

Build the Dashboard Framework

Organize your collected data into a dashboard that brings together all key AEO metrics such as AI impressions, summary inclusions, conversational engagement, and dwell time. This framework makes it easier to identify patterns, track trends, and compare performance across different indicators. 

A well-structured dashboard turns raw data into actionable insights, helping you make informed decisions to optimize your content for AI-driven search.

To enrich your dashboard with deeper insight, consider integrating additional data sources and monitoring methods:

• Clickstream data from trusted third-party providers can help approximate visibility by observing user behavior across the broader web. Monitoring AEO-affected queries in this way allows you to estimate click-through rates (CTR) and identify where your content is likely being cited or surfaced in AI responses.
• Server log analysis offers visibility into how AI bots interact with your site. By filtering logs for known AI user agents, you can measure crawl frequency and detect any drops or spikes that may signal changes in retrieval or ranking behavior.
• Direct monitoring provides the most accurate view of your presence in generative search. Using browser automation frameworks can automate your target queries, capture full generative outputs, and extract citations from AI-generated responses. Repeating this process regularly creates a longitudinal dataset that tracks how your inclusion in AI results evolves over time.

Creating an integrated dashboard helps you connect technical data with real performance results. Over time, it becomes your main hub for tracking AEO, making it easier to measure impact, spot changes in AI behavior, and keep improving your optimization strategy.

Visualize and Analyze Data

Use charts, tables, and trend lines to interpret your AEO metrics clearly and effectively. Visualizing relationships will help you which content truly resonates with users. 

Analyzing these patterns allows you to identify high-performing content, spot opportunities for improvement, and make data-driven decisions that enhance visibility, authority, and engagement within AI-powered search environments.

Optimize Based on Insights

Finally, use your dashboard to refine strategies. Identify content gaps, enhance authority, and adjust messaging to improve visibility and engagement across AI-driven platforms. This approach bridges the gap between theory and practice, transforming abstract AEO concepts into measurable actions that strengthen your brand’s presence in the AI-driven search landscape.

Repeated Tracking

Tracking share of voice in AEO  is more complex than it is in traditional search because there’s no fixed results page to measure. In classic SEO, rankings were stable enough to scrape and compare over time. You could identify changes tied to updates or competitors with relative confidence.

In generative search, however, results are dynamic. The same query can return different answers from one test to the next, even under identical conditions. The AI’s retrieval and synthesis processes constantly shift what’s displayed based on random sampling, evolving index data, and personalization signals.

Because of this, share of voice can no longer be viewed as a static percentage of rankings held—it’s better understood as a probability distribution of visibility over multiple observations. Measuring it effectively means running repeated tests, aggregating the results, and looking for patterns in how often and where your brand appears.

Repeated tracking also helps validate and strengthen other AEO metrics. For example:

• It provides context for AI impressions, showing how often your content is surfaced over time rather than in a single instance.
• It clarifies fluctuations in AI citations or mentions, revealing whether they are temporary or part of a longer trend.
• It supports dashboard-level insights, connecting short-term volatility with long-term performance averages.

By combining repeated tracking with your dashboard metrics—such as impressions, inclusion rates, conversational engagement, and crawl frequency—you can develop a more accurate picture of your brand’s true presence within generative search. This ongoing, iterative approach ensures you’re measuring visibility as a living system rather than a single static result.

Interpreting Answer Engine Analytics

The data you track in your AEO dashboard provides a framework for understanding how to measure AEO performance beyond traditional metrics. When your brand appears in AI-generated summaries or when dwell time on linked pages increases, it signals that your content is both relevant and trusted by AI systems.

AI favors authoritative, well-structured, and semantically rich content, so tracking which pages are cited or surfaced helps reveal what performs best. These insights can guide improvements in content structure, topic depth, and schema optimization, ensuring your brand earns not only visibility but also authority and engagement.

Connecting AI visibility to outcomes like traffic, conversions, and revenue brings the full picture into focus. In Google Analytics, start by segmenting landing pages tied to queries that trigger AI panels. If traffic declines while conversions hold steady, your content may be capturing only the most intent-driven users.

Even without clicks, AI citations still drive value. Mentions in authoritative answers can increase branded search and direct visits over time. Tracking these assist signals helps quantify how generative visibility contributes to broader brand lift and long-term growth.

Key Takeaway

Success in AEO goes beyond clicks and rankings. It’s about being seen, cited, and trusted within the AI layer of search, where users engage directly with generative results. True performance is measured not just by traffic, but by visibility, authority, and meaningful engagement across AI-driven platforms.

To measure AEO performance effectively, focus on AI-native KPIs such as AI impressions, summary inclusions, conversational engagement, and dwell time. These metrics reflect how your content participates in the

The post How to Measure AEO Performance: Key Metrics and Strategies for the AI-Driven Search Era appeared first on SEO Services Agency in Manila, Philippines.

Website traffic is considered one of the main (if not the main) indicators of web success. But there is more to just attracting traffic- website owners and SEO professionals can benefit from doing website traffic data analysis and understanding website statistics and trends. Whether you’re still growing your site or already focusing on acquiring your target market- traffic data analysis can aid in your SEO and marketing strategies. What’s even better is that this can easily be done with free tools such as Google Analytics and Google Search Console.

What are Google Analytics and Google Search Console?

Google Analytics (GA) and Google Search Console (GSC) are two of Google’s own free tools that provide webmasters the ability to track website traffic attribution, search terms, and behavior data. Although there are a ton of options for more “feature-packed” tools that can help marketers to track these things plus other SEO factors of your website, these two already provide everything you need in understanding your website’s progress- both on the big picture and on an intricate standpoint. My team at SEO Hacker also trusts these two free tools from Google providing the necessary information for analyzing a website’s data on traffic and overall SEO performance.

Google Analytics

Google Analytics can be considered your main tool for knowing the entire story behind your website and being able to piece it together so you have a clear understanding of everything that’s going on on your website. It’s focused on providing information that is specific to what your website receives and how a user interacts with it.

Google Search Console

On the other hand, Google Search Console provides information about your website specifically in the aspect of how it is performing from Google’s search results. Here, you can find information about your website with respect to the following:

• Search Performance
• Google Indexing
• Google Page Experience
• Enhancements and security issues

To put it simply, it presents data that allows you to see your website from Google’s perspective.

Google Analytics Vs Google Search Console

When it comes to analyzing your website’s data, these two free tools offered by Google provide different sets of information for us SEO professionals and marketers to utilize. The only similarity they have based on the data sets found in their respective dashboards can be stemmed from; Google Analytics providing user traffic data that can provide you an idea of your website’s authority in Google Search, and Google Search Console provides search data that can translate to traffic coming into your website.

It is very important to acknowledge that these tools track traffic differently. There will always be certain discrepancies in data but you’ll notice that the numbers presented are still very close to each other. What’s important to take note of is that these tools can give you what you need to know about a website’s growth and how it’s keeping up with certain trends.

To learn how to set up Google Analytics, click here. To learn how to set up Google Search Console, click here.

How To Approach Website Traffic Data Analysis

Whether you’re providing website traffic data analysis for a newly SEO-optimized site or a well-seasoned website with multiple SEO strategies implemented; growth should always be your priority. Information is king. And with the information that Google Analytics and Google Search Console provide, it’s all about how well you understand that information and what you can do with it.

How To Do Initial Website Audits with Google Search Console

Let’s assume that you’ve already laid out the SEO foundation of your website prior to development. Before your website traffic data analysis, the first tool that you should be closely monitoring must be Google Search Console. Starting with the Index Coverage report.

Review Coverage Section

The Index Coverage report is where you can find how much of your web page is being crawled and indexed by Google. The term “indexed” describes web pages that are stored in Google Search’s database, which allows them to be retrieved when a search query is punched in by a person using Google. There are also instances wherein Google crawled your web page, but decided to exclude it from its database. The report marks these pages as “Excluded”.

There will always be certain instances wherein an important web page that’s essential in your strategy is marked as Excluded. These are the pages that Google decided to be excluded from the list of pages that can be searched by users. As an SEO professional, this provides you with information for your next action. What should you optimize more? Should you add content to the page? Build better topical authority? Whatever the reason may be, this is a good signal for you to know what to change and improve for your website’s SEO.

The Index Coverage report also provides information for pages with SEO-related errors within them. Web pages marked with Error are more penalizing for SEO than a page marked as Excluded. Errors such as your website’s broken pages (404), pages that are set as no-index, and all other errors affecting Google’s capability in indexing your pages are listed here.

I highly recommend immediately taking action when receiving this information and then looking for ways to prevent it from happening. Learn more about the common GSC errors and how to fix them by clicking here!

Additionally, although the data found here are not directly considered “traffic”, they still play an important role in your website traffic data analysis. Web pages that Google Search Console identifies as having issues will not be indexed. Having non-indexed pages on your website will result in not being searched by users. Which will ultimately lead to less organic traffic coming into your website.

Review Performance Section

The last section that you should focus on is the Performance section of Google Search Console. This section provides you with an overview of how often users interact with your website on the  Google engine results pages (SERPs).

Impressions represent how many users are able to see your website within the search results pages, while Clicks provide how many click-throughs it received from those users. The main point of analyzing this data is to provide you with a basic idea of how well your website is performing in Google’s Search Results Pages. When compared to Google Analytics website traffic data, the information is almost proportional to each other. This is mainly because whenever a website receives a high number of impressions and clicks, this is also an indication of website traffic increase.

How To Do Search Traffic Analysis with Google Analytics

Now that you’ve taken the necessary steps in optimizing your website based on Google Search Console, it’s time to further go into website traffic data analysis by understanding how it can affect performance and growth. This can be done by analyzing the user traffic data presented in Google Analytics. To start, the majority of the search traffic data that we need can be found in the Reports section of the tool. From there, proceed to navigate into Traffic Acquisition.

From there, proceed to navigate into Traffic Acquisition. The first thing you’ll notice with the tool is that traffic data is categorized into different types. Since our main focus for website traffic data analysis is SEO, we’ll only tackle Organic Search traffic for this article. 

The main indicator in understanding website growth using Google Analytics is how much organic search traffic is coming into the website. This will tell you the specific number of people going into your website coming from Google search results- very similar to Google Search Console’s method of acquiring data. The only difference is that you can actually check which of your web pages people are landing on. This information can easily be taken by doing the following:

1. Add filters to the tabulated data by interacting with the “+” icon, then clicking Landing Page to display what pages the users are clicking within Google Search results
   
   
   
2. Then input “organic search” in the top left-most search bar of the data to allow the table to only display organic search traffic
   

After having successfully accomplished these instructions, the data presented in the table should appear similar to this,

The data appearing within the table is now comprised of the list of web pages that are garnering organic search traffic. Since the data is sorted from highest organic traffic to lowest, website traffic data analysis suggests that these web pages are considered the most visible in Google search results. But what’s most important is that through this organized information, you can also acknowledge which of your web pages are the least visible within Google search results. 

Only by acknowledging these pages can you employ a strategy focused on improving the SEO of your weakest pages. Maybe consider doing a content gap analysis for these pages and see what you can improve. Learn about it here in our Content Gap Analysis guide! 

As SEO Professionals, it should always be recognized that SEO is holistic by nature. Having the majority of your pages visible online equates to an overall improvement of website SEO authority. The information that Google Analytics present, provides everything you need in optimizing and restrategizing for website growth. So how can I further improve my analysis with both Google Analytics and Google Search Console?

Analyzing Website Traffic with Google Analytics and Google Search Console

One of the most volatile types of data in the world of digital marketing is organic search traffic. A lot of factors can affect the search traffic coming into your website. Some of the main factors of volatility in traffic include search algorithms, seasonal trends, an unexpected and unchecked bug in your website, and website server volatility. And all of these can be quickly figured out upon checking the GA and GSC tools. To further expound on the importance of website traffic data analysis, consider the following example.

One of our informational websites is receiving a decline in organic search traffic in comparison to the previous period. It lost an estimated 800 users in 1 month. To every website owner or SEO professional, this is considered an alarming loss in website traffic. Since the issue at hand mainly involves organic search traffic, the best tool to utilize next would be Google Search Console

Based on the data presented, it appears that it is only expected to experience website traffic since there is a particular loss in impressions for the website. And since there is a visible loss in impressions, this would also affect the number of clicks the website is receiving within Google search results. What does this mean for our website traffic data analysis?

Since there are fewer impressions coming to the website, your web pages are appearing less in Google search engine results pages. Luckily, Google Search Console also provides data on the search queries that users typed to discover your website. 

Based on the keywords shown, it is quite noticeable how particular keywords received a major drop in impressions. This means that the website is either not ranking for the keyword or that the search query is lower for that particular period. And based on manually testing all these keywords by searching them on Google, I was able to discover that the website is ranking on the first page on all of them. And a website that ranks on the first page of Google is guaranteed impression data.

Based on all the data that I’ve gathered, we can only conclude that the website is undergoing a particular season wherein its keywords are being searched less by users. Rankings are going well, but there’s less traffic coming into the website. These are the kinds of conclusions that are only possible to hypothesize on when you employ tools like GA and GSC to provide the necessary information for website traffic data analysis.

Key Takeaway

It is very easy to be overwhelmed with data and information. But at the same time, as SEO professionals, we should also be grateful that we can easily acquire them through Google Analytics and Google Search Console. There would absolutely be no point in strategizing and executing optimizations if we have no information to prove our efforts. 

It’s only a matter of acknowledging the issue at hand, identifying relevant data to collect, and properly translating that data for you to develop the planned course of action for your website. This exactly represents the importance of knowing how to do even the basic website traffic data analysis.

Interested in an in-depth guide for GA and GSC? Check out our Google Analytics Tutorial for Beginners and Google Search Console Guide!

The post Website Traffic Data Analysis with Google Analytics and Google Search Console appeared first on SEO Services Agency in Manila, Philippines.

The introduction of Google Analytics 4 last year brought about a number of changes. One of which is the shift from Goals to Conversions. If you utilize GA goals, then you understand the importance of tracking activities that can lead to your business’ success. Today I’ll be teaching you how to optimize your Google Analytics 4 Conversions.

The Difference Between GA Events Vs. Goals

First, you should understand the difference between Google Analytics events and goals. For one, goals were used to track actions that could affect your business. This could refer to subscriptions to newsletters or contact form submissions. On the other hand, events were used to track other actions that did not necessarily lead to your success. This could refer to online form downloads or button clicks.

With Google Analytics 4, goals no longer exist. They are now called conversions and they require events to be set up.

Set Up Events

The first step to optimizing your Google Analytics 4 Conversions is to set up your events. Think about what your goals are and choose the appropriate event to set up. You can take a look through Google’s automatic and recommended events to get an idea of what to choose.

Then head to GA4 and click on the Events category. You will notice that there are already some automatic events such as “page_view” and “first_visit”. If you want to make your own, click “Create event”.

This pop up should appear, which will show you a list of your custom events. In this case, I’ve already created an event called “contact_form_to_thank_you”. To create your own, click Create.

Once you’ve done that, it will take you to a Configuration page where you will have to fill up your conditions. Here’s the configuration of the event I previously mentioned.

I set the parameter as “page_location”, the operator as “equals”, and the value as the URL of the site’s thank you page. I chose to copy the parameters from the source event and then hit “Create” on the upper right side of the screen.

Now I can track how many people are filling out the contact form. How? I set my contact form up so that after someone has sent in an inquiry, they will automatically be redirected to the Thank You page. And that’s basically it.

Now that you’ve created your event, let’s talk about how to turn it into a conversion.

Turn Events Into Conversions

There are two ways to turn events into conversions. One is through the Events category and the other is through the Conversions category.

For the events category, all you need to do to mark it as a conversion is to click the button and you’re done.

For the Conversions category, click “New conversion event”.

Then, put in your event name and hit save.

Once you’ve done this, wait a few days before testing it out. Then you should start seeing results.

Key Takeaway

Now you know how to optimize your Google Analytics 4 Conversions. Use this knowledge to track movements on your website that can help lead to its success. Make sure you set up the right events to turn into conversions to see how your website is faring. Keep a close eye on these goals to be able to develop strategies on how you can improve your site’s engagements.

If you have any other strategies for GA4 conversions, I would love to hear about them in the comments section below.

The post How to Create New Conversion Events in Google Analytics 4 appeared first on SEO Services Agency in Manila, Philippines.

Google Analytics is one of the best tools you can freely use to measure and improve your website. It deals with your visitors, user activity, dwell time metrics, incoming search terms, and what have you.

Thus far, we have compiled a series of tutorials for you to jump-start your use of Google Analytics:

• Google Analytics Tutorial

A tutorial about how to install the Google Analytics Tracking code and how to understand the Dashboard data. Here we defined Visits, Unique Visitors, Pageviews, Pages / Visit,  Average Visit Duration, Bounce Rate and Percent of New Visits. This is critical to someone who is trying his hand with Google Analytics for the first time.

• Google Analytics Tutorial: Goal Tracking

A tutorial on how to start with Goal Tracking in Google Analytics. Goals are important – your website has purposes that you want it to achieve – whether it’s for a user to contact you, or to subscribe to your email list, or to make a sale. Tracking these Goals are important. Knowing where users that achieved these Goals came from, is important. We explained how to set-up and understand Goals in Google Analytics. We also discussed about Exact Match, Head Match and Regular Expression Match and how you can utilize them for your website.

• Google Analytics Tutorial: Events Tracking

Events are important. When someone clicks your ‘contact-us’ page, when someone subscribes to your email list, or even when a person  clicks on a ‘play’ button in your video – those things are events that are executed by your users. Those things are important – they tell you whether your email newsletter form is better off on the sidebar or in-content. It tells you which of your articles or social profiles are getting more attention. Know how to set-up Events Tracking with Google Analytics in this tutorial.

• How to Track Outbound Links using Google Analytics

Outbound links are a natural part of each and every website. A website cannot be a lone ranger. No website is an island. Your website has to have other partner sites, or at least other sources where it gets it’s information from. It makes your website more reputable, friendly (to other webmasters) and trustworthy. In this tutorial, we’ll teach you how to track your outbound links using Google Analytics and how it should appear in your Google Analytics Dashboard.

• How to Track your Engaging Posts in Google Analytics

Sometimes the simplest things are overlooked. All websites are capable of engaging its target audience. How do you know if your website is doing well in its user engagement? Time. In this Google Analytics Tutorial, we’ll discuss how you can set-up Goals that will help you track how many users are really engaged by your stuff, as they spend different amounts of their precious time going through it.

And it doesn’t stop there. There’s a whole new world to discover with Google Analytics and we will continue to add up to this list of tutorials as we go along.

The post Google Analytics Tutorial for Beginners appeared first on SEO Services Agency in Manila, Philippines.

I’m pretty sure that you’re getting a good number of users pouring in to your website. The real question is, how many people really do read your stuff? How many of your users actually go through your webpages and take time to understand what you’re talking about? How do you track that with Google Analytics?

(Note: If you missed it, here’s the last tutorial about Tracking Outbound Links using Google Analytics)

A Matter of Time

There is a very simple way to measure out your engaged users. Time. The more time they spend on your pages, the more likely they are engaged with your content. For this entry, this is how we are going to measure out your engaged users – for whatever reason they are spending their precious time with in your website.

Some helpful website facts for you in determining your Visit Duration goal:

Average time on site: 190.4 seconds (Around 3 minutes)
Average pageviews: 4.6
Bounce Rate: 40.5%
New Visits: 62.9%

Average Bounce Rate of Website per category:

Retail / Ecommerece Sites: 20-40% Bounce
Landing Pages: 70-90% Bounce Rate
Portals (MSN, Yahoo, etc): 10-30%
Services or FAQ sites: 10-30%
Content Websites: 40-60%
Blogs: 60-80%
Lead Generation: 30-50%

Step 1: Login to your Google Analytics Account

Step 2: Click on the Admin button on the upper-right section of your account

Step 3: Click on the Website Profile you want to track engaged users with

Step 4: Click on Goals

Step 5: Name your Goal. I recommend naming it something like ‘Engaged Users’

Step 6: On the Goals page, click on the Visit Duration radio button

Step 7: Put in the number of minutes that would define an Engaged User for your website. For this example, I put in 3 minutes.

And it’s all set-up! Here’s how to check your first data:

Step 1: Go to your Google Analytic’s Reporting section

Step 2: Click on Goals -> Overview on the left-hand sidebar.

Step 3: On the Goals Overview page, click on the ‘All Goals’ drop-down button and select the Engaged Users Goal.

In my case, I have 4 categories of Engaged Users:

Initially Engaged Users (1 Minute)
Engaged Users (2 Minutes)
Really Engaged Users (3 Minutes)
Fans (4 Minutes)

Step 4: Voila! You can check out which of your pages are engaging users! I usually set this to a daily check so that I can view the data in micro-perspective.

Determining the Ratio

The great thing about getting this data is you can compare it with the total number of visits that you got that day. This will give you a good look of the percentage of your readers that are really engaged with your stuff!

For example: If I have a data 300 of initially engaged users (1 minute Visit Duration) and I compare it with the 3,000 total visitors I got in that same time-span, I have a ratio of 10% initially engaged users. Increasing this ratio on a monthly basis should be a webmaster’s goal.

How do you Improve User Engagement?

The real question is, where to begin? There are SO MANY THINGS you can do to improve your user’s Visit Duration:

Design

Try going in some of these sites to check out their design:

Soupagency.it

Wearemovingthings

Eastworksleather

Mailchimp

Now imagine having your users spend that much time with your website JUST FOR YOUR DESIGN. But you’re much more than just design, aren’t you?

Content

Content is an excellent way to engage your users.  Having the right content that people are looking for should already spell out ‘engagement’. People spend time reading or watching information they want. It doesn’t have to be an extensive piece of content such as this Youtube SEO post. It can come in the form of a compilation – some short, bite-sized posts like our Content Strategy Tutorial series.

Functionality

Sometimes people are looking for something interactive or perhaps for a tool to help them out. Having any of these in your website can increase user engagement. Imagine how much time people burn in playing online games – whether it’s in Facebook or it’s in a website like Newgrounds.com

Call to Action

After every post, give your users a suggestive action – something that would benefit them. It could be giving them a free e-book, webinar, or other sources of information in your website. Sometimes if you don’t suggest, people simply get up and leave. You have to take the lead. Guide your users into what you want them to do.

Tips for Keeps: Set-up your User Engagement metric. It’s easy, simple and it gives you a good idea in how well your website is retaining its users.

The post How to Track User Engagement and Interest with Google Analytics appeared first on SEO Services Agency in Manila, Philippines.

How do I track outbound links in Google Analytics 4?

Quick Answer: In the latest version of Google Analytics (GA4), outbound clicks are automatically tracked. To view this data, click on the “Real Time” section of your Google Analytics dashboard. Then, choose “Events,” then “Overview.” Next, click “outbound-link,” and set the secondary dimension to “Source.” This will show you all the sources of outbound link traffic.

Author’s Note: The process outlined below is not applicable to the current Google Analytics anymore. To know the latest process on tracking outbound links clicks, read How to Track Outbound Link Clicks with Google Tag Manager.

Overview

For sure you have some outbound links in your website going to other websites for various reasons. We sometimes cite other websites as sources of fun, information, or attribution, etc. You can track which outbound links are clicked by your users by adding a short, simple code in your Google Analytics Tracking code.

Where are you Going?

For sure you’d like to see where your visitors are headed to after they’ve been through your website. Tracking where all your outbound traffic is headed can tell you which outbound links are doing well in your website and which are not. Here’s the code to track all outbound links in your website:

<script type=”text/javascript“>

var a = document.getElementsByTagName(‘a’);
for(i = 0; i < a.length; i++){
if (a[i].href.indexOf(location.host) == -1 && a[i].href.match(/^https:///i)){
a[i].onclick = function(){
_gaq.push([‘_trackEvent’, ‘outgoing_links’, this.href.replace(/^https:///i, ”)]);
}
}
}

</script>

What this code does is it gets all your <a> tags (which is what your links are made out of) and appends an onClick function to it. The onClick function will create an Event Category which will be outgoing_links, and the event action will be the URL.

Put this below your Google Analytics Tracking code like this (highlighted in blue):

<!–THIS IS YOUR GOOGLE ANALYTICS TRACKING CODE–>

<script type=”text/javascript”>

var _gaq = _gaq || [];
_gaq.push([‘_setAccount’, ‘UA-xxxxxxxx-x’]);
_gaq.push([‘_trackPageview’]);

(function() {
var ga = document.createElement(‘script’); ga.type = ‘text/javascript’; ga.async = true;
ga.src = (‘https:’ == document.location.protocol ? ‘https://ssl’ : ‘https://www’) + ‘.google-analytics.com/ga.js’;
var s = document.getElementsByTagName(‘script’)[0]; s.parentNode.insertBefore(ga, s);
})();
var a = document.getElementsByTagName(‘a’);
for(i = 0; i < a.length; i++){
if (a[i].href.indexOf(location.host) == -1 && a[i].href.match(/^https:///i)){
a[i].onclick = function(){
_gaq.push([‘_trackEvent’, ‘outgoing_links’, this.href.replace(/^https:///i, ”)]);
}
}
}
</script>

<!–END RECORD OUTBOUND LINKS CODE–>

This should track all your outbound links. You can check this at the Content -> Events section when you go to your Google Analytics account.

You will be able to see something like this:

(Click the Image to Enlarge)

Event Category is the name of the event. In this example, it is the name of my outbound links – if you noticed, I customized my Events Categories giving them names like ‘SEO Services SB’, ‘SEO School SB’, ‘Facebook Group SB’, etc. You can also customize your Event Categories by using the onClick function for Google Analytics Events tracking here.

Total Events is the times the Event occurred – in this case, it’s the number of times my outbound link was clicked by a user.

Unique Events is the times the Event occurred for a Unique IP address – in this case, it’s the number of times my outbound link was clicked by a Unique user.

Event Value and Avg Value can be set on Goals Settings. As of now, we will not use these.

Where are You Going?

If you check out my Event Categories, I name my links to my understanding. For example, I append an ‘SB’ label to my sidebar links to see if they are clicked more often than their in-content or image counterparts. For this timeframe, it strongly suggests that my sidebar links are the most clicked links – particularly my SEO Services link and SEO School link.

If you want to check your outbound links without the categories simply click the ‘outbound-article’ Event Category and it should take you to the raw URLs of your outbound links.

The results should look like this:

One More Trick

When you’re tracking site-wide outbound links, you can check which pages prove most effective in compelling your users to click-through. Simply add a secondary dimension like this:

Then filter the results such that it won’t show you anything but your site-wide links (you should manually put a customized onClick Events Tracking code in your Site-wide links to effectively track them.) First, click on the Advanced Filter link:

Then Exclude all non site-wide links (Event Category) in my case it is labeled as an ‘outbound-article’ and an ‘outbound-menu’ :

Your Google Analytics should show you data that looks like this:

This data tells me on which landing page has any of my site-wide links have been clicked. This is especially helpful if you are testing sidebar ads, banners, links or email signup forms.

Tips for Keeps: Implementing this Google Analytics Outbound Links Tracking code is a piece of cake – paste the code beside your Google Analytics Tracking code to start gathering your outbound user activity data.

The post How to Track Outbound Links using Google Analytics appeared first on SEO Services Agency in Manila, Philippines.

Lots of things can happen in a website today. You can play a video, subscribe to a newsletter, even play flash games! Would you be able to track if your users are engaging in these activities in your website with Google Analytics? With the usual tracking code, you can’t. So let’s make some tweaks and make sure you’re tracking these valuable interactions shall we?

Pinpointing each Activity

People go in your website to do a certain activity. Either it’s to read the information in your page, watch a video, play a game, or simply send you an email using your contact form. Whatever it is, you can track it and collect the data as a Goal (See our Google Analytics Goal Tracking Tutorial here) or as an event or even both. This data can be used to further improve your website – such as whether to put the email subscription form in the sidebar or as a pop-up or which of your advertisements are getting the most attention / clicks.

Hands in the Mud

So let’s get our hands dirty. Before we start, make sure you have your Google Analytics Tracking code installed in your website.

The code is something as simple as:

onClick=”_gaq.push([‘_trackEvent’, ‘Event Category’, ‘Event Action’, ‘Event Label’]);”

Attach this code to a link or a button in your website. Here’s an example:

<a href=”http://yourURLhere.com” onClick=”_gaq.push([‘_trackEvent’, ‘Event Category’, ‘Event Action’, ‘Event Label’]);”>Your Anchor Text</a>

What this code does is it tells your Google Analytics Tracking code to track an event happening in your website. And whenever someone clicks this link where the code is attached to, it will record the event.

Let’s take a real example that I use here in the SEO Hacker website. See this sidebar?

If you check out the code behind this sidebar, I applied the onClick Events Tracking Code to all of ’em. The code looks like this:

<a onclick=”_gaq.push([‘_trackEvent’, ‘Google Plus SH Page Sidebar’, ‘SEO Hacker G Page’, ‘Visited our Google Plus Page’]);” rel=”publisher” target=”_blank” href=”https://plus.google.com/102703521231315022013/”>Follow us on Google+</a>

It means that when someone clicks on one of these links, it will automatically tell Google Analytics that someone clicked it. It will specify which of the links the user clicked and where the user went. The sample code tells me that the user went to my Google Plus page through this sidebar link.

Inserting the code is a piece of cake – unless you have a TON of things you want to track in your website. So don’t track each and everything a user does – only that which is important. Besides, you wouldn’t want to dilute the important events in your website with the unimportant and ‘common’ ones.

Tracking Events through Forms

Usually a form has some sort of button such as my Email Subscription form on the right sidebar:

You can put the onClick code in the ‘input’ part of the code like this:

<input onClick=”_gaq.push([‘_trackEvent’, ‘Sidebar Email Form’, ‘Email Subscribed’, ‘SEO Hacker RSS Subscribed’]);“ name=”submit” id=”af-submit-image-1013632171” type=”image” class=”image” style=”background: none;” alt=”Submit Form” src=”http://www.aweber.com/images/forms/modern/red/button.png” tabindex=”502“/>

It’s fairly simple – now Google Analytics gets to track each time someone subscribes to our Email RSS feed using this form. Right now I have no other email forms in my website but if I do, I can put another events tracking code in it so it would track which is the better, more effective form in gathering leads.

How it Looks Like

On your Google Analytics Sidebar, go to Content -> Events -> Top Events.

This is how your events would look like in the Top Events section in your Google Analytics. As you can see, most of my events come from outbound links. Tracking outbound links comes with a different code which we will tackle in our Google Analytics Tutorial series.

You can also check out on which pages most of your events happened. Of course, you could always combine the data using Segments if you want to see exactly which Event happened on which Page.

Events tracking is simple and easy. Events Tracking is also highly overlooked. Don’t waste any time. The earlier you apply this in your website, the more valuable data you can look back to. That data can be your basis for A/B testing of forms, buttons, links, videos, etc.

Learn from your user activity, apply that data to your website, test. That’s what Google Analytics is about.

The post Google Analytics Tutorial: Events Tracking appeared first on SEO Services Agency in Manila, Philippines.

Google Analytics Goals and Funnels Visualization are the perfect tools to identify how your goals are performing and how you can improve your website’s strategy.

Websites have goals. It could be an online store or a subscription site, whatever it may be, it’s important to have good goals in a website. But knowing the progress in your goals is totally different.

Webmaster’s Note: This is an entry by Khris Torres – you’ll be seeing more of him here and in SEO School as he partners with me in creating tutorials and guides for you guys.

The most common goal that a person can think of would be selling something online. This is known as an e-commerce goal. By the way, Google Analytics has an Ecommerce module, which I plan to make another article for someday. But for now, we will discuss about other kinds of goals.

Other goals for example can be a Lead Generation goal. This is when you want a user to enter their contact information so that they can be contacted about their product inquiry. An Information goal is when you want a user to download your stuff or view your resource page. A Mailing List goal is when you want a user to join a newsletter or an email feed. In other words, you can have any type of goals in your website that you can track in Google Analytics.

Start making goals

You would need the URL of your goal page, the name of the goal, the goal value and funnel. Make sure your website is integrated with Google Analytics. If you skip that step, you won’t be getting any data from your website. So if I were you, I’d learn Google Analytics Integration now.

Step 1: Login to Google Analytics

Step 2: Click on the Admin tab, which can be found in the upper right side of the page. Click on “Goals”, which is beside “Users” and “Filters”.

As you see, in the “Goals” tab that you can have only 4 goals that you can set. If you want to make more goals, just simply create a new profile.

Step 3: Click on a Goal that’s empty, assume its set 1.

Step 4: Fill up the form.

Write your goal name and select Active so that you can start tracking. For now, we will be teaching you URL Destination.

The goal URL is where you want your visitors to go to in your website. You don’t need to enter the complete address of the page. Instead of starting with www.absmywebsite.com/thankyou.html, you type in /thankyou.html and Google will automatically detect that page.

For a side track, I’ll be explaining the Different Match type options.

Exact match requires that your website goal URL is the exact same URL that you placed in the setup of Google Analytics. This means that there should be no dynamic session’s parameters or identifiers in your URL.

Head match can be used if your website goal page uses dynamically generated content. Head match captures data from the URL parent. Here’s a sample for you to understand better:

http://www.abcmywebsite.com/quote.cgi?page=1&id=1234

For this sample, you will not include the ID part of the URL. Any page that may have a different ID will still be tracked.

Regular Expression Match is a pattern used to match text. They can contain characters and metacharacters and they are used in Google Analytics to capture portions of data field. Within Google Analytics, regular expressions are most useful in filters and tracking goals. You can use it to exclude a range of IP addresses so that they will be tracked by Google Analytics. You can learn more about metacharacters in the help module of Google Analytics.

You can select the Case sensitive option if your website’s URL are case sensitive.

Goal values can be used to monitor sales or expenses. Just place a value of the goal URL. An example can be an email campaign if you’re studying about Email marketing. The goal URL would be the Thank you page whenever someone signs up for an email list. The value of the subscription is $5. By putting 5 on the Goal value, you can identify how much people are subscribing to your email list.

Goal Funnel is an optional feature of Google Analytics, but it can help you identify and visualized your goals in a form of a funnel.

When you select to use goal funnel, an extended part of the form will appear. This is where you can track where your visitors are coming from and where they are going. This depends on your goal type and the structure of your website. It’s best to identify where your visitors are coming from and where should they go to get to your goal URL.

As soon as you save the goal, you are done! Let’s wait and see how your goals progress.

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