Beyond Traffic and Conversions 

For many e-commerce business owners, logging into Google Analytics 4 has become a routine. A glance at traffic, maybe a dip into conversions, and that’s it. The platform is checked off the list, and the dashboard is closed until next week. But what if we told you that you’re only scratching the surface? 

While you’re watching visitors trickle in and out, the real story, the patterns, signals, and untapped opportunities, are happening just beneath your fingertips. Google Analytics 4 isn’t just a facelift of Universal Analytics; it’s a fundamentally new model tailored for modern businesses that operate in a cross-platform, event-driven digital ecosystem. Yet, most e-commerce brands are stuck using it like it’s still 2015.

The truth is, if you’re only tracking sessions, purchases, and bounce rates, you’re missing out on Google Analytics 4’s real power. Features like predictive metrics, GA4 custom explorations, granular event-scoped dimensions, and GA4 BigQuery integration weren’t made for vanity tracking; they’re here to help you truly understand your customer journey, anticipate behavior, and grow strategically. But tapping into that requires more than dashboards. It demands curiosity, strategy, and a willingness to explore the lesser-known paths of Google Analytics 4. 

Why Most Businesses Struggle to Use GA4 Effectively 

Let’s face it, Google Analytics 4 is overwhelming for most users. Its interface is different, the terminology unfamiliar, and the default reports feel limited compared to the classic views of Universal Analytics. But beyond the learning curve, there’s a bigger issue: most businesses don’t have a clear framework for what to track or why. 

Many eCommerce companies still see Google Analytics 4 as a checkbox tool: “We installed it, so we’re good.” But in doing so, they miss out on context-rich data that can highlight user pain points, identify conversion barriers, and even forecast customer behavior. 

Moreover, Google Analytics 4 is event-based, which means it tracks actions instead of sessions. Without an intentional tagging and reporting strategy, this granular data becomes noise. This creates a sort of “data debt”; you have the information but lack the infrastructure or knowledge to act on it. That’s not just a missed opportunity; it’s a competitive disadvantage. 

Unlocking Hidden Gems in GA4 
Google Analytics 4 is more than just a tool for tracking visits and conversions. It offers a suite of advanced features that, when utilized effectively, can transform your understanding of customer behavior. 

Explore: GA4 Custom Explorations for Deeper Insights 
The “Explore” feature in GA4 allows you to create custom reports tailored to your specific business questions. Whether you’re interested in understanding the customer journey, identifying drop-off points in your sales funnel, or analyzing the performance of specific products, GA4 custom explorations provide the flexibility to dive deep into your data. 

Use-Case Examples: 

• Identify the funnel step with the highest exit rate (e.g., users who view a product but never add to cart) 
• Analyze high-performing product categories among returning users 
• Segment users who interact with product videos but don’t purchase 

Steps to Utilize Explore:

• Navigate to your GA4 property. 
• Click on “Explore” in the left-hand menu. 
• Choose a template or start with a blank exploration. 
• Add dimensions and metrics relevant to your analysis. 
• Apply filters and segments to refine your data. 
• Visualize your data using various chart options (e.g., funnel charts, donut charts).

With GA4 custom explorations, you can create dashboards that reflect your exact business goals and customer behavior models, far beyond generic templates.  

Predictive Metrics: Anticipating Customer Behavior 

Google Analytics 4 leverages machine learning to offer predictive metrics, such as purchase probability, churn probability, and predicted revenue. These aren’t just numbers; they’re action triggers.

How to Use Predictive Insights: 

• High purchase probability users: Create custom audiences and run targeted upsell campaigns. 
• High churn probability users: Trigger re-engagement campaigns with personalized offers. 
• Revenue prediction: Prioritize marketing spend on high-value user segments. 

Steps to Access Predictive Metrics: 

• Ensure your GA4 property is collecting sufficient event data, particularly purchase events. 
• Navigate to the “Explore” section. 
• Create a new exploration and add predictive metrics as dimensions or metrics. 
• Segment users based on behavioral thresholds (e.g., last session source, time on site). 

Note: Predictive metrics require minimum thresholds, typically 1,000 users and 100 purchase events within 28 days, to be activated.

Interested in expanding your analytics toolkit beyond GA4? Take a look at “Beyond the Dashboard: 7 Advanced Power BI Features You Didn’t Know Existed” It’s packed with advanced yet practical Power BI features that complement the kind of predictive insights GA4 provides.

Creating Smarter Funnels with Event-Scoped Custom Dimensions

One of the most powerful, yet underutilized, features of Google Analytics 4 is the ability to define custom dimensions at the event level. This allows you to capture the context around specific user actions: what page they were on, what product they interacted with, and what button they clicked. 

Example:

Let’s say you want to track how many users click on the “Size Guide” link on product pages. You can create a custom event with a parameter like element_clicked: size_guide and assign it to an event-scoped dimension. Over time, this can reveal 

• Which products have the most confusion around sizing 
• Correlation between size guide clicks and product returns or cart abandonment 

Steps to Set Up Event-Scoped Custom Dimensions: 

• In your GA4 property, click on “Admin.” 
• Under “Custom definitions,” select “Custom dimensions.” 
• Click “Create custom dimension.” 
• Enter a name and select “Event” as the scope. 
• Specify the event parameter you want to track. 
• Save the custom dimension. 

Enhancing Data Granularity with Strategic Tagging 
A well-structured tagging strategy is crucial for capturing meaningful data. Implementing custom events and parameters through tools like Google Tag Manager (GTM) allows businesses to monitor specific user actions, such as product video views, filter usage, or search bar interaction. 

Best Practices for Tagging: 

• Use clear and consistent naming conventions for tags and triggers. 
• Test tags thoroughly before deployment to ensure accurate data collection. 
• Regularly audit tags to maintain data integrity and relevance. 

Example Tagging Use Cases: 

• Track clicks on “Add to Wishlist” buttons 
• Capture scroll depth for product description sections 
• Monitor use of product filters like “Color,” “Size,” or “Price Range.” 

Leveraging GA4 BigQuery Integration for Historical Data Analysis 
While Google Analytics 4 provides robust real-time analytics, integrating it with BigQuery unlocks the potential for extensive historical data analysis. GA4 BigQuery integration allows for the storage and examination of vast datasets over extended periods, facilitating: 

• Year-over-year comparisons 
• Customer lifetime value (CLV) calculations 
• Advanced cohort analysis 

Sample Queries You Can Run: 

• Identify the most common first product purchased by repeat buyers 
• Compare the average purchase frequency for different traffic sources 
• Track user journeys from organic search to final conversion over 6+ months 

Steps to Integrate GA4 with BigQuery: 

• In your GA4 property, click on “Admin.” 
• Under “Product Links,” select “BigQuery Linking.” 
• Click “Link” to create a new connection. 
• Choose your BigQuery project and configure the data export settings. 
• Confirm and save the integration.

Using GA4 BigQuery integration, businesses can go far beyond the 14-month standard data retention window, helping uncover long-term trends and strategies.  

To explore how GA4 BigQuery integration can unlock deeper insights, don’t miss “Unlocking Hidden Insights: How Google BigQuery Complements GA4 for Deeper Data Analysis” This post dives deeper into use cases, query examples, and how BigQuery adds scale and flexibility to your GA4 data strategy.

Avoiding Common Pitfalls: Ensuring Data Accuracy 

To fully benefit from Google Analytics 4’s capabilities, you must maintain clean and accurate data. Common pitfalls include: 

• Missing transaction data due to improperly set event parameters 
• Skewed reports from internal traffic are not being excluded 
• Overwritten user properties due to misconfigured tags 

Tips for Maintaining Data Accuracy: 

• Regularly review and update event configurations 
• Implement filters to exclude internal or irrelevant traffic 
• Monitor for anomalies or sudden trend spikes 
• Conduct monthly audits of the GA4 + GTM setup

GA4 Mistakes That Could Cost You 

Even well-meaning Google Analytics 4 setups can sabotage your data if not carefully managed. Here are some silent killers of insight: 

• Relying on default reports and ignoring GA4 custom explorations 
• Using inconsistent naming for custom parameters 
• Not activating Enhanced Measurement (scrolls, site search, etc.) 
• Tracking conversions but ignoring attribution windows 

These oversights create blind spots that ripple into marketing inefficiencies, product misfires, and lost revenue. 

Conclusion: Unlock GA4’s Full Potential with Ariel