Key Takeaways of Advantages and Disadvantages of Google Analytics (GA4)

• Google Analytics 4 (GA4) has shifted from simple session tracking to complex, event-based data modeling, fundamentally changing how marketing ROI is measured.
• The biggest advantage of GA4 is the free BigQuery export, allowing businesses to own their raw, granular data and bypass many reporting limitations.
• The major disadvantages include a steep learning curve, counterintuitive user interface (UI), mandatory data sampling/thresholding that hides data, and restrictive data retention limits.
• For high-growth SaaS, Agency, and eCommerce VPs, GA4 is often a “goldmine” of raw data but “hot garbage” in terms of out-of-the-box reporting efficiency.
• Achieving a “Single Source of Truth” requires moving beyond GA4’s interface and implementing a humanized, question-driven analytics framework.

Introduction: The “Ferrari Engine in a Go-Kart” Problem

Google Analytics 4 (GA4) is a Ferrari engine for data-driven marketing, but for the majority of users—the revenue leaders, marketers, and business owners—it feels like it’s been bolted onto a go-kart.

The blunt reality is widely shared by industry experts: Google made GA4 fundamentally better for power users and data analysts who thrive on raw, granular data. In doing so, they made it unnecessarily complicated and opaque for the 90% of business owners and marketing VPs who simply needed quick, basic reports and familiar metrics.

This is because GA4 represents a massive, fundamental shift. It is no longer a simple Reporting Tool; it is a powerful Data Collection Tool. You don’t go to GA4 to view data easily; you go to it to store data powerfully.

For SaaS, Agency, and eCommerce leaders, understanding this trade-off is the difference between having complete revenue visibility and facing operational paralysis due to a complex analytics foundation. This post breaks down the core advantages and disadvantages of GA4 to help revenue leaders determine if the effort is worth the trade-off, or if a solution like Abralytics is necessary to humanize the data and bridge the visibility gap.

The Advantages of GA4 (The “Pros” for Revenue Leaders)

GA4 was built to address the limitations of its predecessor, Universal Analytics (UA), in a world increasingly focused on privacy and cross-device usage. Its strengths lie in data modeling and ownership.

GA4 Advantages Summary

• Event-Based Tracking: Allows precise measurement of the full user journey and specific interactions beyond simple pageviews.
• Free BigQuery Export: Provides enterprise-grade data ownership, enabling integration with CRM and paid media platforms.
• Cross-Device User Journey Modeling: Unifies web and app data to reduce “Attribution Illusion” across devices.
• Predictive Audiences & AI: Uses machine learning to forecast user behavior like churn and purchase probability.

1. A Model Built for “User Behavior,” Not Just Clicks

The most significant architectural shift in GA4 is its move from sessions (UA’s core concept) to events.

Every interaction a user takes, from a pageview to a scroll depth, is now considered an “event.” This change has massive business value for SaaS and eCommerce leaders:

• It allows you to map the entire journey: from initial awareness, through product review, all the way to conversion.
• You can track granular interactions like video plays, file downloads, or specific button clicks without custom coding, providing a much richer view of engagement than was possible before.

This event-centric view is how GA4 supports deeper analysis of leading indicators of success.

2. Enterprise-Grade Data Ownership (BigQuery)

For revenue leaders, this is arguably the single greatest advantage of GA4.

GA4 offers a free, native export to Google BigQuery, a feature that was previously reserved for the expensive GA360 (Google Analytics 360) subscription, often costing $150,000 or more per year.

The Business Value of BigQuery:

• Data Ownership: You are no longer reliant on GA4’s interface or retention limits. You truly own your raw, unsampled data.
• Single Source of Truth: This ownership allows you to bypass GA4’s interface limitations and join web data with external platforms like your CRM (Salesforce, HubSpot) and Paid Media data.
• Custom Modeling: Experts like Abralytics can use this raw data to create custom attribution models that accurately reflect your sales cycle, bypassing the built-in limitations of GA4’s default models.

3. Cross-Platform Visibility

In a world where users browse on mobile, research on desktop, and purchase in an app, unified tracking is essential.

GA4 unifies app and web data streams. For SaaS and eCommerce brands, this is critical because users frequently switch devices before making a major purchase. This unified approach helps reduce the “Attribution Illusion” where a mobile click might be inaccurately lost or ignored before a final desktop conversion is recorded.

4. Predictive Audiences & AI

GA4 incorporates native machine learning for analyzing user behavior.

This feature allows the tool to move reporting from “what happened” (a lagging indicator) to “what will happen” (a predictive indicator). Features include:

• Churn Probability: Identifying users likely to abandon your product or service.
• Purchase Probability: Identifying users most likely to convert in the next week, allowing for targeted re-marketing.

This shift helps growth teams focus resources on nurturing the right users at the right time.

The Disadvantages of GA4 (The “Cons” That Kill Efficiency)

Despite its technical capabilities, the user experience and reporting fidelity of GA4 introduce significant operational challenges for efficiency-focused revenue teams.

GA4 Disadvantages Summary

• Steep Learning Curve: The UI is complex, forcing VPs and Account Managers to spend excessive time digging for basic data.
• Data Sampling and Thresholding: Google hides data to protect privacy and save processing power, leading to zero-value reports where sales occurred.
• Poor Default Reporting UI: The built-in reports are often not business-friendly and require significant customization via Looker Studio.
• Data Retention Limits: Granular user data is automatically purged after a short period, hindering Year-over-Year (YoY) analysis.

1. The Steep Learning Curve & UI Frustration

For the vast majority of marketers, the GA4 interface is a major pain point. It is often described as “unnecessarily complicated” for the 90% of users who simply need basic channel performance, goal completions, and trend analysis.

The Business Impact:

• Visibility Gap: Account Managers or VPs waste hours digging for basic answers that were immediately visible in Universal Analytics. This time is time lost on strategy.
• Barrier to Entry: The complexity forces teams to either learn SQL, rely on technical analysts, or become completely dependent on external dashboard tools like Looker Studio. For non-technical marketers, this significantly slows down the pace of decision-making.

2. Data Sampling and “Thresholding”

This is a critical concern for data accuracy. To save processing power and protect user anonymity (particularly in smaller segments), Google may “sample” data or impose “thresholds.”

The Pain Point: If you query a very specific user segment or have low overall traffic, GA4 will hide the data, showing a “0” or “Thresholding Applied” message.

The Business Impact: For decision-makers, “useful data” is not the same as “accurate data.” You might see a revenue report that shows “0” for a specific campaign, even if sales did occur. This forces teams to question the integrity of the data and damages confidence in the tool. This is a primary reason why a solution like Abralytics recommends relying on BigQuery for critical data points, bypassing GA4’s reporting issues.

3. Data Retention Limits

GA4’s standard data retention for granular user data is severely limited, often defaulting to only 2 months or a maximum of 14 months, depending on settings.

The Business Impact: You lose historical context. Conducting a granular Year-over-Year (YoY) analysis on specific user behaviors (e.g., comparing how users engaged with a feature in January of last year vs. this year) becomes impossible without an external data warehouse like BigQuery to store the raw data indefinitely. Strategic decisions rely on historical context, and GA4 removes this context by default.

4. The “Attribution Illusion”

While GA4 offers superior modeling, relying solely on any software attribution model leads to the “Attribution Illusion.”

The pain point is that digital analytics software often over-credits easy-to-track channels like “Direct” or “Organic Search” while failing to capture the true influence of “Dark Social” (podcasts, communities, word-of-mouth, private messages).

The Business Impact: Relying solely on GA4 leads to bad budget allocation. For many high-growth B2B companies, software might show 78% of conversions coming from Search, while self-reported data (asking customers “How did you hear about us?”) shows 85% came from Dark Social or a specific podcast. If you only look at GA4, you will defund the channels that truly drive growth.

Strategic Framework: Humanizing the Data

The stark contrast between GA4’s technical power and its poor user experience highlights a core truth: the tool is only as good as the questions you ask. Stop letting the tool lead your strategy.

Revenue leaders must adopt a Question-Driven Analysis framework. Instead of drowning in endless dashboards, focus every analyst’s time on answering three core business questions:

1. Where is traffic coming from? (Acquisition: Are we spending money in the right place?)
2. Are they interested? (Engagement/Behavior: Is our content and product resonating?)
3. Which sources drive meaningful actions? (Outcomes/Conversions: Is the traffic leading to revenue?)

The Shift: Managing Behaviors, Not Outcomes

Crucially, shift your focus from Outcomes (lagging indicators like Closed Won or MQLs) to Behaviors (leading indicators like Time on Site, Scroll Depth, or Feature Adoption).

You can manage behaviors directly through content and UX changes; you cannot manage outcomes directly. GA4’s event-based modeling is designed for this shift, but only if you use a streamlined interface, like those designed by Abralytics, that prioritizes behavior over raw data noise.

Frequently Asked Questions (Executive Summary)

Is GA4 GDPR Compliant?

Out of the box, no. GA4 stores data on US servers and transfers European user data, which can pose compliance risks for Agencies and EU-based companies under General Data Protection Regulation (GDPR) standards. True compliance often requires complex anonymization or server-side tagging. By contrast, a data-focused analytics partner like Abralytics specializes in setting up compliant data flows.

Why doesn’t my GA4 revenue match my Shopify/Salesforce revenue?

This common discrepancy is usually due to one of three issues: “broken tracking” (events not firing correctly), “data sampling” (GA4 hiding the true numbers), or a lack of server-side tagging (where browser tracking fails due to ad blockers). GA4 should always be treated as a trend tool, showing relative performance over time, not a precise bank statement. For exact revenue reconciliation, you must integrate GA4 data with your CRM via BigQuery.

Should I hire a full-time analyst just to manage GA4?

If your team of VPs, Directors, or Account Managers spends 10 or more hours a week manually exporting CSVs, building complex Looker Studio reports, or arguing over basic data accuracy, you have a “Data Spaghetti” problem. The “10% Rule” suggests if 10% of your current retainer or marketing spend could cover a specialist to clean the data, save employee hours, and improve client retention, the investment is justified. The goal is to maximize strategy time and minimize data cleaning time.

How does GA4 handle cookie consent and privacy?

GA4 introduced “Consent Mode,” which uses modeling to fill in the gaps for users who decline cookies. While this modeling helps recover some data, it still relies on statistical estimates, meaning the data is not 100% factual. This highlights the need for first-party data strategies that are not entirely reliant on browser cookies.

What is the biggest limitation of GA4 for attribution?

The biggest limitation is the inability to easily apply highly customized, fractional attribution models in the standard interface. For example, if you need a model that credits the first touch 40%, the last touch 40%, and mid-funnel interactions 20%, you must use BigQuery and SQL to create and visualize this model. The standard GA4 interface is restricted to a limited set of default attribution options.

Conclusion: Don’t Let GA4 Be a “Leaky Bucket”

Google Analytics 4 is a foundational piece of the modern analytics stack. Its advantages are clear: enterprise-level data ownership via BigQuery and advanced predictive AI capabilities. However, its disadvantages are steep: a counterintuitive UI, restrictive data sampling and retention, and a high barrier to entry for strategic users.

For high-growth companies, these “Cons” often translate directly into lost revenue because VPs are forced to waste time validating numbers instead of leading strategy. The tool, in its default state, becomes a “leaky bucket,” losing valuable data and efficiency.

The gap is simple: Most VPs are paid to define and lead the strategy, not to clean data, fix Google Tag Manager containers, or write complex SQL queries.

The Solution:

Abralytics acts as an extension of your team, not just a service provider. We do not just fix tracking; we implement a comprehensive Revenue Analytics foundation that seamlessly connects Marketing > Sales > Revenue. We replace fragmented tools and guesswork with a unified, accurate foundation, handling the technical “plumbing” (BigQuery integration, GTM governance, Looker Studio development) so you and your team can focus exclusively on the decisions that drive growth.

Stop guessing what drives your revenue and start trusting your data. Book a Strategy Call with Abralytics today to turn your fragmented GA4 data into a powerful, strategic asset.