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In the age of digitization, businesses are continuously striving for customer-centric marketing efforts. The integration of varied data streams, advancements in marketing platforms, and the evolution of analytical tools have empowered organizations to achieve through data-driven marketing. Central to these advancements are technologies and platforms such as Google Analytics 4 (GA4), Google Ads and email marketing solutions. By integrating these tools and leveraging marketing automation, businesses can streamline their processes and create more meaningful interactions with their customers.

1. Understanding the Customer Through Data Integration

The first step towards customer-centricity is to have a holistic understanding of the customer. This means breaking down silos between different data sources and integrating them to have a comprehensive view of the customer’s journey. The Google Marketing Stack provides tools that facilitate the integration of data from different touchpoints like the web, mobile apps, and even offline channels. By combining these data sources, businesses get a complete picture of how customers interact with their brand, empowering them to make data-driven decisions.

2. The Role of Google Analytics 4

Google Analytics 4 plays a crucial role in this integrated ecosystem. Unlike its predecessor, GA4 is event-based, allowing businesses to track a myriad of interactions on their websites or apps, right from page views to button clicks. This granularity in data collection ensures that marketers can understand the minutiae of user behavior, personalizing their approaches accordingly.

Additionally, GA4 introduces AI-powered insights, which provide businesses with actionable recommendations based on user behavior. It’s not just about understanding what the customer did but also predicting what they might do next, enabling proactive marketing strategies.

3. Marketing Automation and Its Benefits

Having an integrated data system is the foundation, but marketing automation is the machinery that brings customer-centricity to life. Automation can take various forms, such as triggering personalized email campaigns based on user behavior or automatically segmenting users for targeted advertising.

For instance, if a customer browsed a product on a website but did not complete the purchase, an automated email marketing system can send a personalized follow-up email with a special offer for that product. Such strategies lead to more conversions, as they align with the customer’s immediate interests and behaviors.

4. Email Marketing – The Evergreen Channel

Despite the emergence of numerous digital communication channels, email marketing remains one of the most effective tools for building and nurturing customer relationships. With the integration of all data from platforms like GA4, email marketing, CRM and offline data can be more tailored than ever. By segmenting the audience based on their interactions, preferences, and past behaviors, businesses can craft messages that resonate with the individual, fostering loyalty and driving repeat business.

Use Case: Activating Preventive Measures for Possible Customer Churn

Background: Suppose there’s an e-commerce business, “Example Shop” that sells tech gadgets. Over time, they’ve noticed a pattern where long-time customers suddenly reduce their purchase frequency or stop buying altogether. Example Shop uses a combination of tools: CRM, Email systems, Google Ads, and they store much of this data in Google’s BigQuery or is integrated in.

Objective: To predict and prevent possible customer churn by integrating data from various platforms using BigQuery and initiating an automated outreach strategy.


  1. Data Integration:CRM Data: Contains customer profiles, purchase history, customer service interactions, and loyalty program details. Email Systems Data: Captures email open rates, click-through rates, and responses. Google Analytics 4 Data: Holds information on users, events and conversions. Example Shop can pull these disparate datasets into BigQuery, integrating them to create a unified view of each customer’s interactions across various touchpoints.
  2. Identifying Churn Indicators with BigQuery: Once the data is in BigQuery, Example Shop can run advanced SQL queries to identify patterns associated with churn. For example:

SELECT customer_id,
SUM(purchase_amount) as total_purchase_last_3_months,
COUNT(distinct email_opened) as email_open_count_last_3_months,
AVG(sessions) as avg_sessions_last_3_months
FROM unified_customer_data
GROUP BY customer_id
HAVING total_purchase_last_3_months < 10
AND email_open_count_last_3_months < 2
AND avg_sessions_last_3_months < 1;

  • This query might return customers who have: Purchased less than a set amount in the last three months. Opened fewer than two emails in the same period. Had a session on average. These could be indicators of waning interest, suggesting potential churn.

  • Activation of Preventative Measures:Email Marketing: Using the list of potential churn candidates:Segment them in the email marketing tool. Launch a personalized email campaign offering special discounts or exclusive previews of new products. This email can also have feedback forms asking them about their shopping experience, providing valuable insights into why they might be drifting away.Google Ads Retargeting:Use the customer IDs to create a specific audience in Google Analytics and launch a retargeting campaign showcasing new products or offering special deals. These ads will appear to the identified customers across the web, reminding them of Example Shop’s value proposition.(we can add customer behavior to enhance audience creation)CRM Engagement:Alert the customer service team about these customers. If there’s any manual follow-up or engagement needed, like a personal call or offering a loyalty bonus, it can be triggered from the CRM.

  • Measurement & Feedback Loop:Monitor the engagement metrics of the identified segment closely. Measure open rates, click-through rates, redemption of special offers, and purchases.Adjust the predictive model and outreach strategies based on feedback and outcomes.

Use Case Conclusion: In this digital age, integrating data from varied tools, running advanced analytics like churn prediction, and initiating preventive measures in a timely fashion can play a significant role in customer retention. “Example Shop” approach, leveraging BigQuery’s power and an integrated marketing and CRM strategy, exemplifies the potential of modern data-driven customer engagement.


In essence, the path to customer-centricity in the digital age involves an intricate dance between data integration, analytics, and automation. Tools like Google Analytics 4 and the Google Marketing Platform act as catalysts, providing rich insights and seamless integration. When combined with the power of email marketing, businesses are equipped to deliver personalized experiences at scale, truly placing the customer at the heart of their strategies. In this era, businesses that can harness these technologies efficiently will undoubtedly stand out from the crowd, achieving greater customer loyalty and business growth.

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Photo credit to Blake Wisz

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