Google Analytics

Imagine running a physical shop where you cannot see your customers. You do not know how many people walk in, which products they look at, how long they stay, or why they leave without buying. That is exactly what running a website without analytics is like - you are flying blind. Google Analytics 4 (GA4) is a free tool from Google that tracks and reports on your website traffic. It tells you who visits your site, where they come from, what they do while they are there, and whether they take the actions you care about - like filling out a contact form, making a purchase, or signing up for a newsletter. GA4 is the current version of Google Analytics. It replaced the previous version called Universal Analytics (UA), which stopped processing new data on 1 July 2023. If you were using Universal Analytics before, your old data is no longer being updated. All new tracking must use GA4. The biggest change between UA and GA4 is how they collect data. Universal Analytics used a session-based model - it focused on grouping user actions into sessions (visits). GA4 uses an event-based model - every interaction a user has with your site is recorded as an event. A page view is an event. A scroll is an event. A button click is an event. This gives you much more detailed and flexible data about how people actually use your website. GA4 is completely free for most businesses. Google also offers Google Analytics 360, a paid enterprise version with higher data limits, advanced features, and dedicated support. For small and medium businesses, the free version is more than sufficient. The bottom line is simple: if you have a website and you are not using Google Analytics, you are making decisions based on guesswork instead of data. GA4 gives you the facts you need to understand what is working, what is not, and where to focus your effort.

Setting up Google Analytics 4 involves three layers that work together: an account, a property, and a data stream. Think of it like a filing cabinet. The account is the cabinet itself. The property is a drawer inside it (one for each website or app you want to track). The data stream is where the data actually flows in from your website or app. Here is how to set everything up from scratch: Step 1: Create a Google Analytics Account Go to analytics.google.com and sign in with your Google account. Click "Start measuring" and enter your account name. This is usually your business name. Under "Account Data Sharing Settings," review the options. Most businesses can leave the defaults on - they allow Google to benchmark your data anonymously against industry averages, which can be useful later. Step 2: Create a Property Next, create a property. Enter your property name (usually your website name), select your reporting time zone and currency. Getting these right is important because GA4 uses them to calculate daily metrics and revenue data. If your business operates in Malaysia, select "(GMT+08:00) Kuala Lumpur" and "Malaysian Ringgit (MYR)." You will also be asked about your business industry category and business size - these help Google tailor the interface for you. Step 3: Set Up a Web Data Stream After creating the property, choose "Web" as your platform. Enter your website URL and give the stream a name (for example, "Main Website"). Once created, GA4 gives you a Measurement ID - a code that starts with "G-" followed by a string of characters (for example, G-ABC123XYZ). This ID is what connects your website to your GA4 property. Keep it handy - you will need it in the next section when you install the tracking code. Step 4: Enable Enhanced Measurement Before leaving the data stream settings, make sure Enhanced Measurement is turned on. This is one of GA4's best features - it automatically tracks common user interactions without any extra setup. With enhanced measurement enabled, GA4 will automatically track: • Page views - every page a visitor loads • Scrolls - when a visitor scrolls to the bottom of a page (90% depth) • Outbound clicks - when someone clicks a link that takes them to another website • Site search - when someone uses your website's search bar • Video engagement - when embedded YouTube videos are started, progressed, or completed • File downloads - when someone downloads a PDF, spreadsheet, or other document GA4 also offers a seventh enhanced measurement event - form interactions (tracking when users start and submit forms). However, this feature is known to be unreliable in many setups, so many professionals disable it and use Google Tag Manager to track forms more accurately instead. You can toggle each of these events on or off individually. For most businesses, keeping all of them on is the right choice. This means that from the moment you install GA4, you are already tracking meaningful user behaviour without writing a single line of extra code.

You have your GA4 account, property, and Measurement ID ready. Now you need to install the tracking code on your website so GA4 can start collecting data. There are three main ways to do this, and the right choice depends on your technical setup. Method 1: Direct Installation (gtag.js) This is the simplest method. GA4 gives you a small JavaScript code snippet that you paste into the <head> section of every page on your website. The code looks like this: a script tag that loads Google's tracking library, followed by a few lines that configure your Measurement ID. If you have a simple HTML website and are comfortable editing code, this works well. The downside is that any future changes to your tracking require editing your website code directly. Method 2: Google Tag Manager (Recommended) Google Tag Manager (GTM) is a free tool that acts as a container for all your tracking codes. Instead of pasting the GA4 code directly into your website, you install one GTM snippet on your site and then manage all your tags (GA4, Facebook Pixel, LinkedIn Insight, and more) from the GTM dashboard. The advantage is that you can add, edit, or remove tracking codes without touching your website code. For businesses that plan to use multiple tracking tools or want flexibility, GTM is the recommended approach. Inside GTM, you create a "Google Analytics: GA4 Configuration" tag, enter your Measurement ID, and set it to fire on "All Pages." Method 3: CMS Plugins If your website is built on a content management system like WordPress, Shopify, or Wix, there are built-in integrations or plugins that make installation even easier. On WordPress, plugins like "Site Kit by Google" let you connect your GA4 property with a few clicks - no code editing required. Shopify has a native Google channel integration. Wix has a built-in Marketing Integrations section. The plugin method is the easiest but gives you the least control over advanced tracking configurations. Verifying Your Installation After installing the tracking code, you need to confirm it is working. Open your website in a browser and navigate to a few pages. Then go to your GA4 property and click Reports > Real-time. You should see at least one active user (that is you). The real-time report updates every few seconds and shows you page views, events, and user locations as they happen. If you do not see any data in real-time reports, check these common issues: • Code placement: The tracking code must be in the <head> section, not the <body> or footer • Measurement ID mismatch: Double-check that the ID in your code matches the one in your GA4 data stream settings • Ad blockers: Browser extensions like uBlock Origin can block GA4 tracking. Try in an incognito window with extensions disabled • Caching: If your website uses caching, clear the cache after installing the code so the latest version loads For a more thorough check, use the Google Tag Assistant Chrome extension (now called "Tag Assistant Companion"). It shows you exactly which tags are firing on any page, whether they are sending data correctly, and flags any errors.

When you open Google Analytics 4, the first thing you see is the Home page. Think of it as your daily dashboard - a quick snapshot of how your website is doing right now and over the past few days. The Home page is made up of several snapshot cards that give you a quick overview without clicking into any reports. You will typically see: • Users in last 30 minutes - a real-time count of active visitors, with a bar chart showing activity by minute • Users and new users - how many people visited over the last 7 or 28 days, with a trend line showing whether traffic is going up or down • Key events - how many valuable actions (like form submissions or purchases) users completed • Recently accessed - shortcuts to reports you have opened recently, so you can jump back quickly Below the snapshot cards, you will also see AI-generated insight cards. These are powered by Google's AI and highlight things that are unusual or noteworthy - for example, "Users from Instagram increased 45% compared to last week" or "Your page 'Contact Us' had an unusually high bounce rate yesterday." You do not need to go looking for these patterns; GA4 surfaces them automatically. Now let us look at the Real-Time report. Click "Reports" in the left sidebar, then "Real-time." This report shows you what is happening on your website right now, updated every few seconds. You will see: • Active users - how many people are on your site at this exact moment • Pages being viewed - which specific pages people are looking at right now • Events firing - what actions users are taking (clicks, scrolls, form starts) • Traffic sources - where current visitors came from (Google search, social media, direct) • User locations - a world map showing where your current visitors are located Real-time data is most useful in three situations. First, campaign launches - when you send out an email newsletter or launch a social media ad, you can watch in real-time as people start arriving on your site. Second, debugging - if you just installed a new tracking code or made changes to your website, the real-time report lets you verify immediately that events are firing correctly. Third, live events - if you are hosting a webinar or flash sale, you can monitor traffic spikes as they happen. One important thing to understand: the Home page and real-time data are great for a quick pulse check, but they are not where you do deep analysis. For that, you need the standard reports and explorations, which we will cover next.

The Life Cycle reports are where you spend most of your time in GA4. They are organised into four categories that follow the user journey from first arrival to long-term loyalty: Acquisition, Engagement, Monetisation, and Retention. Acquisition: Where Do Your Users Come From? The Acquisition reports answer the fundamental question: how are people finding your website? There are two main reports here: • User Acquisition - shows how new users found your site for the first time. If someone first discovered you through Google search, that channel gets the credit, even if they return later through a different source • Traffic Acquisition - shows how sessions (visits) arrive at your site. This includes both new and returning visitors. If a user first came from Google but returned the next day by clicking a link on Facebook, the Facebook visit shows up here GA4 groups traffic into default channel groups: Organic Search (people who found you on Google or other search engines), Direct (typed your URL or used a bookmark), Organic Social (Facebook, Instagram, LinkedIn, X), Referral (links from other websites), Paid Search (Google Ads), Email, and more. Engagement: What Do Users Do on Your Site? Once people arrive, you need to know what they actually do. The Engagement reports show: • Pages and screens - which pages get the most views, which keep people engaged longest • Events - a list of all events being tracked (page views, scrolls, clicks, custom events), with counts for each • Key events - the specific actions you have marked as important for your business (we will cover these in Module 3) The two most important engagement metrics are engagement rate (the percentage of sessions where the user interacted meaningfully - stayed longer than 10 seconds, viewed 2+ pages, or triggered a key event) and average engagement time (how long users actively engaged with your content). Monetisation: Are Users Spending Money? If you sell products or services online, the Monetisation reports show revenue data: total revenue, purchases, items viewed, items added to cart, and revenue by product. For businesses that do not sell online, this section may show limited data, but it becomes important if you ever add e-commerce tracking. Retention: Do Users Come Back? The Retention report shows how often users return to your site after their first visit. It displays a cohort chart - a grid that shows what percentage of users who visited in Week 1 came back in Week 2, Week 3, and so on. For most content websites, a returning user rate of 20-30% is healthy. For e-commerce sites, higher retention usually means stronger customer loyalty.

Knowing what people do on your website is important, but knowing who they are is equally valuable. The User Attributes and Tech reports help you understand your audience so you can make better decisions about content, design, and marketing. User Attributes: Demographics The Demographics report shows you the characteristics of your visitors: • Country and city - where your visitors are located geographically. This is especially useful if you serve a specific region. You might discover visitors from countries you never expected • Age - the age brackets of your visitors (18-24, 25-34, 35-44, and so on) • Gender - the gender split of your audience • Interests - what topics your visitors are interested in based on their broader browsing behaviour (Technology, Business, Sports, and so on) A word of caution about demographics data: GA4 can only collect age, gender, and interests data when Google Signals is enabled in your property settings (Admin → Data Settings → Data Collection). Google Signals uses data from users who are signed into their Google accounts and have personalised advertising turned on. This means demographics data is based on a sample of your users, not all of them. You may also see "(not set)" for a significant portion of your audience - these are users GA4 cannot identify. Additionally, GA4 applies data thresholds - if your audience is too small, some demographic data is hidden to protect individual privacy. You might see a message like "Data thresholds have been applied" when viewing these reports. This is normal and more common for websites with lower traffic. Tech Reports: Devices and Browsers The Tech reports tell you how people access your website: • Device category - the split between desktop, mobile, and tablet users. For most websites today, mobile traffic is 60-70% of total traffic • Browser - which browsers people use (Chrome, Safari, Edge, Firefox). If a large portion of your audience uses Safari, for example, you need to make sure your site works well on it • Operating system - Windows, macOS, Android, iOS, Linux, and others • Screen resolution - the display sizes your visitors use, which matters for responsive design These reports are not just interesting trivia - they directly inform business decisions. If 65% of your visitors are on mobile phones but your website looks broken on small screens, you know exactly what to fix first. If most of your audience is in a specific country, you might consider localising your content for that market. Customising Your Report Navigation By default, GA4 shows a standard set of reports in the left sidebar. But you might not need all of them, and you might want quick access to reports you use frequently. The Report Library lets you customise which reports appear in your navigation. To access it, go to Reports and click the pencil icon (or "Library" at the bottom of the report navigation). From here, you can: • Pin your most-used reports - add shortcuts to reports you check daily • Remove reports you never use - declutter your navigation • Create custom report collections - group reports by topic (for example, a "Weekly Review" collection) Customising the report library is optional but recommended once you have been using GA4 for a few weeks and know which reports matter most to your business.

In Module 1, we mentioned that GA4 uses an event-based data model where every user interaction is recorded as an event. Now let us dig deeper into what that actually means and why it matters for your business. In GA4, everything is an event. When someone loads a page, that is a page_view event. When they scroll down, that is a scroll event. When they click a link to another website, that is a click event. When they download a PDF, that is a file_download event. Every single interaction gets its own entry in your data. GA4 organises events into four categories, and understanding these categories is key to getting the most out of your tracking: 1. Auto-Collected Events (Always On) These events are tracked automatically the moment GA4 is installed on your site. You cannot turn them off and you do not need to configure anything. They include: • first_visit - when a user visits your site for the first time ever • session_start - when a new session (visit) begins • page_view - when a page loads in the browser • user_engagement - when the user has been actively engaged for at least one second 2. Enhanced Measurement Events (Toggle On/Off) We covered these in Module 1. They are extra events that GA4 can track automatically, but you can toggle each one on or off in your data stream settings: • scroll - user scrolls to 90% of the page depth • click - user clicks a link to an external website (outbound click) • view_search_results - user performs a search on your site • video_start, video_progress, video_complete - engagement with embedded YouTube videos • file_download - user downloads a document (PDF, XLSX, DOCX, etc.) • form_start, form_submit - user interacts with a form (though this one can be unreliable) 3. Recommended Events (Google-Suggested Names) These are events that Google recommends you set up using their predefined names. Using Google's recommended names means GA4 can generate special reports and features for these events. Examples include: • login - user logs into an account • sign_up - user creates a new account • purchase - user completes a transaction • add_to_cart - user adds an item to their shopping cart • generate_lead - user submits a contact or enquiry form 4. Custom Events (Your Own) These are events you create with your own names for interactions specific to your business that do not fit into any of the above categories. For example, you might create a whatsapp_click event when someone taps your WhatsApp button, or a brochure_request event when someone fills out a brochure request form. Each event can also carry event parameters - extra pieces of information that add context. For example, a page_view event includes parameters like page_location (the URL), page_title (the page name), and page_referrer (where the user came from). When you create custom events, you can attach your own parameters to capture any detail you need.

Now that you understand the different types of events, let us talk about key events - the most important concept in GA4 for measuring business success. A key event is simply any event that you mark as particularly important for your business. It tells GA4: "This action matters - I want to track it as a business outcome." Before March 2024, key events were called "conversions." Google renamed them to "key events" to avoid confusion with Google Ads conversions, which are a separate concept. The functionality is the same - only the name changed. Why Key Events Matter Without key events, GA4 treats all events equally. A page view gets the same importance as a purchase. By marking certain events as key events, you tell GA4 which actions represent real business value. This affects several things: • Key events appear prominently in your reports and the Home page overview • GA4's AI (Analytics Advisor) focuses on key events when analysing your site's performance • Key events power the "engaged session" metric - any session that triggers a key event is considered engaged • If you link Google Ads, key events can be imported as Google Ads conversions for Smart Bidding How to Mark an Event as a Key Event Go to Admin → Events (under your property's Data Display section). You will see a list of all events GA4 has recorded. Next to each event name, there is a toggle in the "Mark as key event" column. Simply flip the toggle for any event you want to mark as a key event. You can have up to 30 key events per property. For most small businesses, 5-10 key events is the sweet spot. Having too many dilutes the meaning - if everything is a key event, nothing is. Common Key Events for Different Businesses Here are the key events that matter most depending on your business type: • Service businesses (consultants, coaches, agencies): generate_lead (contact form submissions), whatsapp_click, phone_click • E-commerce (online stores): purchase, add_to_cart, begin_checkout • Content/media sites (blogs, news): sign_up (newsletter subscription), file_download, scroll on key articles • SaaS/apps: sign_up, login, feature activation events Creating New Events from Existing Ones Sometimes the event you want to track as a key event does not exist yet. GA4 lets you create new events based on conditions applied to existing events - without writing any code. Go to Admin → Events → Create Event. For example: • You want to track when someone views your "Thank You" page (which appears after a form submission). Create a new event called form_complete that fires when page_view happens AND the page_location contains "/thank-you" • You want to track when someone views your pricing page. Create a new event called pricing_view that fires when page_view happens AND the page_location contains "/pricing" After creating the event, go back to the Events list and mark your new event as a key event. Verifying Key Events After setting up key events, verify they are working. Trigger the action on your website (submit the form, click the button), then check two places: • Real-time report - the event should appear within seconds under "Event count by Event name." Key events are highlighted with a star icon • Reports → Engagement → Key events - this report shows all your key events with counts over time. It may take 24-48 hours for data to appear here

You now know how to track what people do on your website. But there is another critical piece: knowing exactly where they came from. While GA4 automatically identifies broad traffic channels (Organic Search, Social, Direct), it cannot tell the difference between a link you shared on Facebook versus one you sent in an email - unless you tag your links with UTM parameters. What Are UTM Parameters? UTM stands for "Urchin Tracking Module" (a holdover from the pre-Google Analytics era). UTM parameters are short pieces of text you add to the end of a URL to tell GA4 exactly where the click came from. When someone clicks a UTM-tagged link, GA4 reads the parameters and attributes that visit to the specific campaign, source, and medium you defined. There are five UTM parameters: • utm_source (required) - The platform or website sending the traffic. Examples: facebook, newsletter, linkedin, partner_blog • utm_medium (required) - The marketing channel type. Examples: social, email, cpc (cost per click), referral, banner • utm_campaign (required) - The specific campaign name. Examples: spring_sale_2026, weekly_newsletter_apr, product_launch • utm_content (optional) - Differentiates between multiple links in the same campaign. Examples: header_button, footer_link, image_banner • utm_term (optional) - Identifies paid search keywords. Mostly used with Google Ads for manual tracking A tagged URL looks like this: https://yoursite.com/pricing?utm_source=facebook&utm_medium=social&utm_campaign=spring_sale_2026 Building Tagged URLs You do not have to type these parameters manually. Google provides a free tool called the Campaign URL Builder (search for "Google Campaign URL Builder" or go to ga-dev-tools.google). Enter your base URL and the parameter values, and it generates the full tagged URL for you. Naming Conventions: The Rules That Save You The most common mistake with UTM parameters is inconsistent naming. UTM values are case-sensitive, so Facebook, facebook, and FACEBOOK will appear as three separate sources in your reports. Follow these rules: • Use lowercase only - facebook not Facebook • Use underscores instead of spaces - spring_sale not spring sale • Be consistent - always use the same source name for the same platform • Create a naming document - a simple spreadsheet listing your approved source/medium/campaign values so everyone on your team uses the same names Seeing UTM Data in Reports Once people start clicking your tagged links, the UTM data appears in the Acquisition → Traffic Acquisition report. You can see exactly how each campaign performed: how many users it brought, their engagement rate, and whether they triggered any key events. Common UTM Mistakes to Avoid • Using UTMs on internal links - Never add UTM parameters to links within your own website. This resets the session source and makes it look like users came from your own site rather than their original source • Inconsistent naming - fb vs facebook vs Facebook creates three separate entries in reports • Missing parameters - Always include at least source, medium, and campaign. Missing values show as "(not set)" in reports • Not using UTMs at all - Any untagged link from email, social media, or partner sites may show up as "Direct" traffic, making it impossible to measure those channels accurately

Imagine being able to ask your website data a question in plain English - the same way you would ask a colleague - and getting a clear answer with a chart. That is exactly what Analytics Advisor does. Analytics Advisor is a Gemini-powered conversational AI built directly into GA4. It was rolled out in late 2025 and has been expanded significantly in 2026. You do not need a separate subscription or tool - it is part of the standard GA4 interface. Where to Find It You will see Analytics Advisor in two places: • A search bar at the top of the GA4 interface (labelled "Ask Analytics Advisor") - click here to start a conversation • An insight panel that appears alongside reports - sometimes Analytics Advisor offers proactive suggestions as you browse reports Asking Broad Questions The simplest way to start is with a broad question like: • "How is my site doing?" • "Give me an overview of my website's performance this month" • "What should I know about my traffic right now?" Analytics Advisor responds with a tailored business health check. It pulls together key metrics, creates visualisations (charts and tables), and provides links to relevant reports where you can dig deeper. The response is not a generic template - it analyses your actual data and highlights what is noteworthy for your specific website. Asking Specific Questions You can also ask targeted questions about specific metrics, time periods, or segments: • "What have my active users been doing over the last 30 days?" • "Which traffic source brought the most new users last week?" • "How many key events did I get from mobile users this month?" • "Compare my traffic this month to the same month last year" For each question, Analytics Advisor generates a response with the relevant data, often including a chart or table, and suggests related questions you might want to explore next. Language Support Analytics Advisor currently works best in English but supports multiple languages. The quality of responses in non-English languages has been improving steadily since launch. What It Can and Cannot Do Analytics Advisor is excellent for quick answers, spotting trends, and generating hypotheses. However, it has limitations: • It works with the data in your GA4 property only - it cannot access external data or tools • Complex multi-step analyses (like correlating weather data with sales) still require Explorations (covered in Module 5) • Occasionally, it may misinterpret an ambiguous question - rephrasing usually fixes this • It cannot make changes to your GA4 configuration - it is read-only

Getting useful answers from Analytics Advisor depends on asking the right questions. Like any AI tool, the quality of the output matches the quality of the input. Here is how to formulate effective queries. Broad vs Specific Questions Broad questions are great for starting your analysis: • "How is my website performing?" → Gets a general health check • "What are the key trends this month?" → Surfaces notable patterns Specific questions are better for investigating particular areas: • "What is my engagement rate for users from social media in the last 7 days?" → Precise metric for a specific channel and timeframe • "Which pages have the highest exit rate this month?" → Identifies problem pages The best approach is to start broad, then go specific. Let the broad answer point you toward what to investigate next. Time-Bound and Comparison Queries Adding a time frame makes your questions much more useful: • "How did my traffic change between January and February?" • "Compare this week's key events to the same week last month" • "What was my best-performing day in the last 30 days?" Comparison queries are particularly powerful because they highlight changes you might not notice when looking at a single time period. Follow-Up Questions One of Analytics Advisor's most useful features is the ability to ask follow-up questions in the same conversation. After getting an initial answer, you can drill deeper: • Initial: "My traffic increased by 40% last week." • Follow-up: "Which channels drove that increase?" • Follow-up: "What pages did those new users visit?" • Follow-up: "Did any of them trigger key events?" This conversational flow lets you investigate a topic layer by layer without having to navigate through multiple reports. Key Driver Analysis One of the most powerful capabilities is key driver analysis. When you notice something unusual - a spike or a drop - ask Analytics Advisor to explain why: • "Why did my traffic spike on March 15th?" • "What caused the drop in key events last weekend?" • "Why is my engagement rate lower this month compared to last month?" Analytics Advisor uses AI to pinpoint root causes automatically. It identifies which channels, pages, campaigns, or user segments drove the change. This type of analysis would normally take an experienced analyst 30-60 minutes of manual investigation - Analytics Advisor does it in seconds. When to Use Explorations Instead Analytics Advisor is not the right tool for everything. Use Explorations (Module 5) when you need: • Complex multi-dimensional analysis with custom segments • Funnel analysis with specific step sequences • Path analysis to visualise user journeys • Cohort analysis over extended time periods Think of Analytics Advisor as your quick-answer assistant and Explorations as your deep-research workshop.

Beyond the questions you ask, GA4's AI works proactively in the background, surfacing insights you might not have thought to look for and predicting future behaviour. AI-Generated Insight Cards We briefly mentioned insight cards on the Home page in Module 2. Let us look at them more closely. GA4 automatically analyses your data and generates insight cards when it detects: • Anomalies - unusual spikes or drops that deviate from normal patterns. "Sessions from Paid Search increased 120% compared to the previous period" • Emerging trends - patterns that are developing over time. "Traffic from mobile devices has been growing steadily for the past 4 weeks" • Milestone alerts - when metrics reach notable thresholds. "Your website received its 10,000th visitor this month" You do not need to do anything to activate these insights - they appear automatically. You can click on any insight card to see more detail and explore the underlying data. Predictive Metrics GA4 also offers predictive metrics that use machine learning to forecast future user behaviour. There are three predictive metrics: • Purchase probability - the likelihood that a user who was active in the last 28 days will make a purchase in the next 7 days • Churn probability - the likelihood that a user who was active in the last 7 days will NOT be active in the next 7 days • Predicted revenue - the expected revenue from a user over the next 28 days based on their behaviour There is an important catch: predictive metrics require a minimum amount of data to work. Specifically, your property needs at least 1,000 positive samples (users who did purchase or did churn) and 1,000 negative samples (users who did not) over a recent period. This means predictive metrics are mainly available for larger e-commerce sites. For smaller sites, these features will show as unavailable. Building Predictive Audiences If your site meets the data requirements, you can create predictive audiences based on these metrics. For example: • "Likely purchasers" - users with a high purchase probability, whom you can target with remarketing ads • "Likely churners" - users at risk of leaving, whom you can re-engage with special offers or content These audiences can be shared with Google Ads for targeted campaigns. Data-Driven Attribution The last piece of GA4's AI toolkit is data-driven attribution. In the real world, customers rarely convert on their first visit. They might see a social media post, click a Google ad, read a blog article, then finally make a purchase a week later from a direct visit. The question is: which of these touchpoints gets credit for the conversion? GA4 uses machine learning to distribute credit across all touchpoints based on their actual contribution to the conversion. This is called data-driven attribution, and it is the default model in GA4. Unlike older "last-click" models that gave all credit to the final touchpoint, data-driven attribution recognises that earlier interactions (like the social media post that created awareness) also contributed to the conversion. You can explore attribution data in the Advertising workspace (left sidebar → Advertising). Here you will find: • Conversion paths - the sequences of touchpoints that lead to conversions • Model comparison - compare data-driven attribution with other models to see how credit distribution differs

So far, we have been looking at GA4's standard reports - the pre-built dashboards that show Acquisition, Engagement, Monetisation, and Retention data. These reports answer common questions and are great for day-to-day monitoring. But what happens when you need to answer a question that the standard reports do not cover? That is where Explorations come in. Think of the difference like this: • Standard Reports = a pre-designed dashboard that answers the most common questions. Quick to read, but limited in flexibility • Explorations = a blank canvas where you choose exactly what data to display, how to slice it, and what to visualise. More powerful, but requires you to build the analysis yourself To access Explorations, click "Explore" in the left sidebar. You will see a gallery of templates and any explorations you have previously saved. GA4 offers seven exploration templates: • Free Form - the most flexible option. Build custom tables, charts, and visualisations by dragging dimensions and metrics into rows, columns, and values. This is what you will use most often • Funnel - visualise a step-by-step user journey (like "viewed product → added to cart → started checkout → purchased") and see where users drop off at each step • Path - see how users navigate through your site from any starting or ending point. Discover unexpected routes users take • Segment Overlap - Venn diagram showing how user segments overlap (for example, how many users are both "mobile users" and "purchasers") • User Explorer - drill into individual user behaviour, examining the specific sequence of events and sessions for a single user. Useful for troubleshooting or understanding a particular customer journey • Cohort - group users by their first visit date and track their behaviour over time (similar to the Retention report but with much more flexibility) • User Lifetime - analyse long-term user value by looking at total revenue, sessions, and engagement over a user's entire relationship with your site The Exploration Interface Every exploration has two main panels: • Variables panel (left side) - this is your toolbox. It contains three sections: Dimensions (what you want to group by, like "Country" or "Page title"), Metrics (what you want to measure, like "Users" or "Key events"), and Segments (user groups you want to compare, like "Mobile users" or "New users") • Tab settings panel (middle/right) - this is where you build your analysis by dragging variables from the left panel into configuration areas like Rows, Columns, Values, and Filters The result appears as a table or visualisation on the right side of the screen.

The Free Form exploration is the one you will use most often. It lets you create custom tables and charts by combining any dimensions and metrics from your GA4 data. Step-by-Step: Creating a Free Form Exploration 1. Start a new exploration Go to Explore and click "Free form" (or "Blank" to start from scratch). Give your exploration a name - something descriptive like "Mobile vs Desktop Engagement" or "Top Pages by Country." 2. Import dimensions and metrics In the Variables panel on the left, click the "+" button next to Dimensions to add the categories you want to analyse (like "Device category," "Country," "Page title," "Session source/medium"). Then click "+" next to Metrics to add what you want to measure (like "Active users," "Engagement rate," "Key events," "Average engagement time"). 3. Build your analysis Drag dimensions from the Variables panel into the Rows area in the Tab settings panel. This defines the rows of your table. Drag metrics into the Values area. This defines the numbers that appear in each cell. For example, dragging "Device category" into Rows and "Active users" + "Engagement rate" into Values creates a table showing user counts and engagement rates for Desktop, Mobile, and Tablet. 4. Choose a visualisation type The default is a table, but you can switch to other types in the Visualisation dropdown: • Table - rows and columns of data (most common) • Donut chart - shows proportions (good for device split or channel mix) • Line chart - shows trends over time • Scatter plot - shows correlations between two metrics • Bar chart - compares values across categories • Geo map - geographic distribution of users 5. Apply filters Filters narrow your data to specific subsets. Click "Filters" in the Tab settings and define conditions. For example: "Country equals Malaysia" or "Page title contains blog." Multiple filters can be combined to get very specific views. 6. Create and apply segments Segments are predefined groups of users you want to compare. Click "+" next to Segments in the Variables panel to create custom segments: • User segment - groups of users matching certain criteria (e.g., "Users who triggered a purchase event") • Session segment - groups of sessions matching criteria (e.g., "Sessions from mobile devices") • Event segment - groups of events matching criteria (e.g., "Page view events on blog pages") Drag segments into the Segment Comparisons area to see side-by-side data for different user groups. Practical Example: "Which pages do my mobile users visit most?" Here is how to answer this question: 1. Create a session segment: "Device category equals mobile" 2. Drag "Page title" into Rows 3. Drag "Views" and "Average engagement time" into Values 4. Apply the mobile segment 5. Sort by Views (descending) You now see exactly which pages mobile users visit most and how long they spend on each one.

Free Form explorations are great for general analysis, but two specialised exploration types deserve special attention: Funnel and Path explorations. These are specifically designed to understand how users move through your website. Funnel Exploration: Where Do Users Drop Off? A funnel exploration visualises a sequence of steps you expect users to follow and shows you how many users complete each step - and more importantly, where they drop off. Setting up a funnel: 1. Go to Explore and choose the "Funnel exploration" template 2. Define your steps. Each step is an event or page view. For example: • Step 1: page_view on your product page • Step 2: add_to_cart event • Step 3: begin_checkout event • Step 4: purchase event 3. GA4 shows a bar chart with the number of users who completed each step and the drop-off rate between steps Funnel explorations have two modes: • Closed funnel - only counts users who completed the steps in the exact order you defined. A user who skipped Step 2 and went straight from Step 1 to Step 3 is not counted • Open funnel - counts users who completed each step regardless of order. A user can enter the funnel at any step. Open funnels typically show higher completion rates because they are less restrictive You can also create trended funnels that show how completion rates change over time. This is useful for measuring the impact of website changes - for example, did redesigning the checkout page improve the completion rate? Path Exploration: Where Do Users Actually Go? While funnel explorations test a specific hypothesis ("Do users follow this path?"), path explorations are for discovery - finding out where users actually go without any assumptions. Path explorations let you choose either a starting point or an ending point and see the tree of pages or events that users navigate through. Starting point example: • Start with: "Homepage" • See: What pages users visit next (About? Pricing? Blog? Contact?) • Then: What they visit after that, and after that, branching outward Ending point example: • End with: "Purchase event" • See: What pages users visited immediately before purchasing • Then: What they visited before that, tracing the path backward Path explorations often reveal unexpected navigation patterns. You might assume users go Homepage → Products → Product Page → Cart, but the path exploration might show that most purchasers actually go Blog → Product Page → Cart, skipping the Products listing entirely. You can also apply segments to path explorations. Compare how mobile users navigate versus desktop users, or how users from different traffic sources take different paths through your site. Practical Example: "Where do users go after landing on my pricing page?" 1. Open a Path exploration 2. Set the starting point as a page_view event where page_title equals "Pricing" 3. See the branching tree of what users do next - do they contact you? Go to the FAQ? Leave the site entirely? 4. The answer tells you whether your pricing page is effective at moving users toward a decision or whether it is a dead end

Google Search Console (GSC) is a free tool from Google that shows you how Google sees your website. While GA4 tells you what people do on your site, Search Console tells you how people find your site on Google - and whether Google can properly read and index your pages. To get started, go to search.google.com/search-console and add your website. You will need to verify ownership to prove you own the site. There are several methods: • Domain verification (recommended) - add a DNS record through your domain registrar. This covers all subdomains and protocols automatically • HTML tag - add a small meta tag to your homepage’s HTML • Google Analytics method - if GA4 is already installed on your site, Google can verify ownership through your existing tracking code • HTML file upload - upload a verification file to your website’s root folder • Google Tag Manager - if GTM is already installed on your site, Google can verify ownership through your GTM container Once verified, the most important report is the Search Performance report. This shows you four key metrics for your Google search traffic: • Clicks - how many times someone clicked on your site in Google search results • Impressions - how many times your site appeared in search results, even if nobody clicked • Click-Through Rate (CTR) - the percentage of impressions that resulted in clicks. A typical CTR for position 1 is 20-28%, dropping to 2-5% by position 10 • Average Position - your average ranking position for a given query (1 = top result, 10 = bottom of page 1) You can filter this data by query (what people searched), page (which of your pages appeared), country, device (desktop, mobile, tablet), and date range. This filtering is incredibly powerful. For example, you can find all queries where your site appeared in positions 8-15 (bottom of page 1 or top of page 2) - these are your "quick win" opportunities where a small SEO improvement could move you up significantly. Beyond search traffic, GSC also provides: • Index Coverage report - shows which of your pages Google has indexed (can appear in search results), which pages have errors preventing indexing, and which pages Google has discovered but chose not to index • Core Web Vitals - measures your page speed and user experience (Largest Contentful Paint, Interaction to Next Paint, Cumulative Layout Shift). Google uses these as ranking factors • Page Experience - a combined view of HTTPS security, mobile-friendliness, and Core Web Vitals Think of Search Console as your report card from Google. It tells you what Google thinks of your website and where you can improve to get more visitors from search.

Search Console and GA4 are powerful on their own, but they become even more valuable when linked together. Here is why: Search Console shows you what people searched on Google to find your site, while GA4 shows you what people did after they arrived. Linking them gives you the complete picture - from the search query that brought someone to your site, to the pages they viewed, to the actions they took. How to Link Search Console to GA4 The linking process takes just a few minutes: 1. Open GA4 and go to Admin (gear icon at the bottom left) 2. Under your property, find Product Links 3. Click Search Console Links 4. Click the Link button 5. Select your Search Console property from the list (you must be verified as an owner in both GSC and GA4) 6. Choose which GA4 web data stream to link 7. Click Submit Once linked, two new reports appear inside GA4 under Reports → Search Console: • Queries report - shows the search terms people used on Google before clicking through to your site, along with clicks, impressions, CTR, and average position. This is similar to the Search Console Performance report, but now you can see it alongside your GA4 data without switching between tools • Google Organic Search Traffic report - shows which of your pages received organic Google traffic, combined with GA4 engagement metrics like engagement rate and average engagement time. This is uniquely powerful because it answers questions like: "Which landing pages get the most Google search traffic, and do visitors from Google actually engage with the content?" Practical Use: Finding High-Value SEO Opportunities The real magic happens when you combine Search Console data with GA4 behaviour data. Here is a practical workflow: 1. Find high-impression, low-CTR queries - In the Queries report, sort by impressions (highest first) and look for queries with low CTR (below 3-5%). These are pages that appear in search results frequently but fail to attract clicks. Improving the page title and meta description can significantly increase CTR without changing your ranking position 2. Find high-traffic, low-engagement pages - In the Google Organic Search Traffic report, look for landing pages with high click counts but low engagement rates. These pages successfully attract visitors from Google but fail to keep them interested. The content may not match what searchers expected, or the page may be slow or poorly formatted on mobile 3. Identify content gaps - Look at the queries where your site appears in positions 4-15. These are topics Google considers your site relevant for, but you are not ranking well enough to get significant traffic. Creating deeper, more comprehensive content on these topics can boost your rankings Understanding the Data Differences One important caveat: Search Console data only covers Google organic search. It does not include traffic from Bing, Yahoo, social media, direct visits, or paid ads. GA4’s Acquisition reports cover all traffic sources. So when comparing numbers, remember that Search Console clicks will always be lower than GA4’s total organic traffic (which may include search engines beyond Google). Also, there is typically a 48-hour data delay in Search Console data appearing in GA4. So the linked reports are best for weekly or monthly analysis, not real-time monitoring.

GA4 and Search Console are just two tools in a larger Google analytics ecosystem. Three other tools complete the picture: Google Tag Manager for managing tracking codes, Looker Studio for building visual dashboards, and Google Ads for connecting advertising data. Let us look at each one. Google Tag Manager (GTM) Think of Google Tag Manager as a central control panel for all the tracking codes on your website. Instead of editing your website’s HTML code every time you want to add or change a tracking pixel (GA4, Facebook Pixel, LinkedIn Insight Tag, etc.), you install GTM once, then manage everything through GTM’s web interface. GTM works with three core concepts: • Tags - the tracking codes you want to fire (e.g., GA4 event tag, Facebook conversion pixel) • Triggers - the conditions that determine when a tag fires (e.g., when someone clicks a button, submits a form, or scrolls to 50% of the page) • Variables - dynamic values used by tags and triggers (e.g., the page URL, the text of the clicked button, the form field values) When should you use GTM instead of installing GA4 directly? Use GTM when: • You manage multiple tracking tools beyond GA4 • You need to track custom events like specific button clicks or form submissions • You want to make tracking changes without asking a developer to edit website code • You need version control and a preview mode to test changes before publishing For a simple website with only GA4 tracking, direct installation (as we covered in Module 1) is perfectly fine. But as your tracking needs grow, GTM becomes essential. Looker Studio (formerly Google Data Studio) Looker Studio is Google’s free dashboard and reporting tool. While GA4 has its own reports, Looker Studio lets you create custom visual dashboards that combine data from multiple sources - GA4, Search Console, Google Ads, Google Sheets, and many more - all in one place. Here is how to build a basic GA4 dashboard in Looker Studio: 1. Go to lookerstudio.google.com and click "Create → Report" 2. Add GA4 as a data source (select your GA4 property) 3. Start building by dragging in scorecards (big numbers like total users, sessions), time series charts (traffic over time), tables (top pages, top channels), and pie charts (device breakdown) 4. Add date range controls so viewers can change the time period 5. Click Share to give access to your team or stakeholders A good starter dashboard includes five key widgets: total users and sessions (scorecards), traffic trend over time (line chart), top channels (bar chart), top pages (table), and device breakdown (pie chart). You can also add Search Console data to the same dashboard to show SEO metrics alongside engagement data. The biggest advantage of Looker Studio is automated reporting. Once built, your dashboard updates automatically with fresh data. Instead of manually creating reports each month, you share a dashboard link and everyone always sees the latest numbers. Google Ads Integration If you run paid advertising through Google Ads, linking it with GA4 unlocks two powerful capabilities: • Import key events as conversions - Instead of setting up separate conversion tracking in Google Ads, you can import the key events you have already configured in GA4 (like form submissions or purchases). Google Ads then uses these to optimise your ad campaigns through Smart Bidding • Build remarketing audiences - Create audiences in GA4 based on user behaviour (e.g., "visited the pricing page but did not submit the contact form") and share them with Google Ads for targeted remarketing campaigns To link Google Ads, go to GA4 Admin → Product Links → Google Ads Links and follow the same pattern as the Search Console linking process. You need admin access to both your GA4 property and Google Ads account.

You have spent the first six modules learning how to set up GA4, navigate reports, track events, use AI insights, build explorations, and connect the wider Google toolkit. Now it is time for the most important skill of all: turning data into decisions. The first step is learning what to focus on. Many business owners fall into the trap of tracking vanity metrics - numbers that look impressive but do not actually drive business outcomes. Pageviews alone do not tell you if your website is working. A page with 10,000 views but a 15% engagement rate and zero key events is not performing as well as a page with 2,000 views, 65% engagement rate, and 50 form submissions. The Five Metrics That Matter Instead of drowning in data, focus on five metrics that tell you whether your website is actually helping your business: 1. Users (and new vs returning) - Are you attracting new people? Are existing visitors coming back? A healthy split depends on your business, but most content sites aim for 20-40% returning users 2. Engagement rate - What percentage of visitors actually interact meaningfully with your content (stayed 10+ seconds, viewed 2+ pages, or triggered a key event)? An engagement rate below 50% suggests visitors are not finding what they expect 3. Key events - How many valuable actions are users completing? These are the actions you defined as important in Module 3: form submissions, sign-ups, purchases, downloads. This is the metric that connects website activity to business outcomes 4. Top channels - Where is your best traffic coming from? Not just the most traffic, but the traffic with the highest engagement rate and most key events. You might discover that email traffic converts at 3x the rate of social media traffic 5. Top landing pages - Which pages do visitors arrive on first, and do they engage? A landing page with high traffic but low engagement needs immediate attention Spotting Trends and Anomalies Always compare data over time periods. A single week’s data tells you very little. Compare this week to last week, this month to last month, and this quarter to the same quarter last year. Look for: • Upward or downward trends - Is traffic growing or declining over time? Is engagement improving? • Sudden spikes or drops - These usually indicate something specific happened: a viral social post, a marketing email, a Google algorithm update, or a technical problem on your site • Seasonal patterns - Many businesses see predictable traffic changes around holidays, school terms, or industry events When you spot something unusual, use Analytics Advisor (Module 4) to investigate. Ask questions like "Why did traffic drop last Tuesday?" or "What caused the spike in form submissions this week?" The AI can often pinpoint the cause faster than manually digging through reports. Benchmarking Against Yourself Avoid comparing your numbers to other websites or "industry averages" - these benchmarks are often misleading because every website serves a different audience in a different context. Instead, benchmark against your own historical performance. If your engagement rate was 48% last month and 55% this month, that is meaningful progress regardless of what other websites achieve.

The most powerful thing about having GA4, Search Console, and Analytics Advisor connected is that you can answer real business questions with data instead of guesswork. Here are five questions every business owner or marketer should be able to answer, along with exactly which reports and tools to use. Question 1: "Where do my visitors come from?" Go to Reports → Acquisition → Traffic Acquisition. This shows your traffic broken down by channel: Organic Search, Direct, Social, Referral, Email, Paid Search, and more. But do not just look at volume - add the Key events column to see which channels actually drive valuable actions. You might find that Social brings lots of visitors but very few conversions, while Referral traffic from a partner website has a much higher conversion rate. For campaigns with UTM parameters (Module 3), you can drill deeper. Go to Reports → Acquisition → Traffic Acquisition and change the primary dimension to "Session source/medium" or "Session campaign" to see performance by individual campaign. Question 2: "Which content performs best?" Go to Reports → Engagement → Pages and screens and sort by "Average engagement time per session." This tells you which pages people actually spend time reading, not just which pages get the most views. Then check the linked Search Console → Google Organic Search Traffic report to see which pages attract the most organic search traffic and what queries drive visitors to each page. Question 3: "Why are users leaving?" This requires a two-step approach. First, in the Pages and screens report, look for pages with high views but low engagement rates - these are your "leaky bucket" pages where visitors arrive and immediately leave. Second, build a Path exploration (Module 5) starting from these problem pages to see where users go next. Do they leave the site entirely, or do they navigate to unexpected pages? You can also ask Analytics Advisor: "Which pages have the highest exit rates?" or "Why is the bounce rate on my pricing page so high?" Question 4: "What drives conversions?" Go to Reports → Engagement → Key events to see how many valuable actions users are completing. Then use the Advertising → Attribution reports to understand which channels get credit for conversions. The Model comparison report lets you compare different attribution models - for example, last-click (which channel gets credit for the final visit before conversion) versus data-driven (which channels contributed most across the entire journey). For deeper analysis, build a Funnel exploration (Module 5) to see exactly where users drop off in your conversion process. If 500 users view the pricing page but only 50 click "Contact Us" and only 10 submit the form, you know exactly where the biggest drop-off occurs. Question 5: "How is my SEO doing?" Combine three data sources for a complete SEO picture: • GA4 Acquisition - check the trend of Organic Search traffic over time (is it growing or declining?) • Search Console Queries - which keywords are you ranking for? Are impressions and clicks growing for your target keywords? • Search Console Index Coverage - are all your important pages indexed? Are there crawl errors preventing pages from appearing in search results? By combining these three views, you can tell whether your SEO efforts are working, which keywords to focus on, and whether there are any technical issues holding you back.

The biggest mistake people make with analytics is treating it as an occasional activity - checking data only when someone asks a question or when something seems wrong. To get real value from GA4, you need a consistent routine. Here is a practical monthly plan that any business owner or marketer can follow. Week 1: Traffic and Acquisition Review Start each month by understanding how people found you: • Open GA4 → Acquisition → Traffic Acquisition and compare this month to last month • Check which channels grew and which declined • Review any active campaigns and their UTM-tagged performance • Note your total users, new users, and returning user ratio • Action question: "Which channel should I invest more time or money in next month?" Week 2: SEO and Search Performance Dedicate the second week to understanding your search presence: • Open Search Console → Performance and review clicks, impressions, CTR, and position trends • Look for new queries your site is appearing for (opportunities to create targeted content) • Find high-impression, low-CTR queries and update page titles and meta descriptions • Check Index Coverage for new errors or excluded pages • Review Core Web Vitals for any pages with poor performance • Action question: "Which SEO quick wins can I implement this week?" Week 3: Conversion and Key Event Audit The third week focuses on whether visitors are doing what you want them to do: • Open GA4 → Engagement → Key events and review the trend • Check your Funnel explorations for major drop-off points • Ask Analytics Advisor about any anomalies: "Were there any unusual changes in key events this month?" • Review the Attribution reports to understand which channels get credit for conversions • Action question: "Where is the biggest opportunity to improve my conversion rate?" Week 4: Insights Report and Action Plan The final week is about compiling everything into a shareable report: • Update your Looker Studio dashboard with any new data sources or widgets • Write a brief summary (3-5 bullet points) of the month’s key findings • List 2-3 specific actions for next month based on the data • Share the dashboard and summary with your team or stakeholders • Action question: "What are the top three priorities for next month based on this data?" Setting Up Automated Reports GA4 can send automated email reports so you do not have to remember to check data manually. Go to any standard report, click the share icon, and select "Schedule email delivery." You can set it to send daily, weekly, or monthly to yourself and your team. For more comprehensive automated reporting, set up a Looker Studio dashboard (Module 6) with email scheduling. Looker Studio can send a PDF snapshot of your dashboard to stakeholders on a regular schedule. The 15-Minute Daily Check Beyond the monthly routine, spend just 15 minutes each day on analytics. Open your Looker Studio dashboard (or the GA4 Home page) and check three things: (1) any unusual spikes or drops in traffic, (2) key events from the past 24 hours, and (3) any AI-generated insights flagged by Analytics Advisor. This daily habit means you will catch problems early and never be surprised by trends at the monthly review. Remember: the goal of analytics is not to collect data. It is to make better decisions. Every time you look at a report, ask yourself: "What should I do differently because of this data?" If the answer is "nothing," you are looking at the wrong metric.