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flowchart LR
A[Website or App Data] --> B[Google Analytics 4]
B --> C[Insight: High drop-off on landing page]
C --> D[Action: Retargeting and landing page improvements]
D --> E[Outcome Metric: Higher conversion rate]
Part 4 — GA4 301 Micro-Application: Integrations & Activation Plan
Overview
This report demonstrates my understanding of how Google Analytics 4 (GA4) connects to the broader marketing analytics stack and how those connections can be used to activate insights for a Customer Engagement Plan (CEP). The report includes evidence of module completion, screenshots from the GA4 integrations area, a workflow diagram, and short responses explaining how GA4 insights could be used for activation and deeper analysis.
Module Completion Evidence
The following screenshots show that I completed the GA4 training module related to using GA4 with other tools and data sources.
GA4 Training Certificate of Completion
This certificate confirms that I successfully completed the Google Skillshop module “Use GA4 with Other Tools and Data Sources.” The module focused on how GA4 connects with other tools, how data can be combined across systems, and how integrations support more advanced analysis and activation.
GA4 Course Completion Page
This screenshot shows the course completion page in Skillshop and provides additional evidence that all required training content and activities were completed.
Evidence of GA4 Integration Access
Figure 1. GA4 Admin → Product Links
Figure 1 shows the Product Links section inside the GA4 Admin panel. This area is where users can connect GA4 to other products such as Google Ads, BigQuery, Search Console, Display & Video 360, and other Google marketing tools. These integrations are important because they allow organizations to connect analytics data with advertising, search, and data warehouse systems for deeper analysis and better decision-making.
Figure 2. GA4 BigQuery Linking Page
Figure 2 shows the BigQuery Linking configuration page in GA4. This integration allows GA4 event data to be exported into BigQuery, which makes it possible to run advanced SQL-based analysis, combine GA4 data with other business datasets, and perform deeper customer journey analysis than what is typically available in the GA4 interface alone.
Workflow Diagram
The diagram below shows a simple activation workflow that connects data collection in GA4 to a marketing action and a measurable outcome.
Short Responses
1. Name one integration (Google Ads, Search Console, BigQuery, Looker Studio, etc.) that would most help your CEP and why.
One integration that would be the most helpful for my CEP is BigQuery. Connecting GA4 to BigQuery allows raw event-level data to be exported so analysts can run deeper queries and combine analytics data with other business data sources. This helps generate more advanced insights about user behavior and conversion patterns than what is available directly in the GA4 interface.
2. Describe one audience you would build in GA4 for activation (who is in it, and what they did).
One audience I would build in GA4 is users who visited main product pages but did not complete a purchase. This audience would include people who viewed product details or added items to their cart but exited before finishing checkout. These users could then be targeted with re-marketing campaigns to encourage them to return and complete their purchase.
3. If you had BigQuery export, what’s one analysis you’d do there that’s hard in the GA4 UI?
If I had BigQuery export enabled, I would analyze multisession customer journeys across different marketing channels. BigQuery would allow me to query raw event-level data and reconstruct how users interact with the website over time before converting. This type of detailed path analysis is difficult to perform in the standard GA4 interface but can reveal which marketing channels and behaviors lead to successful conversions.