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18 Jul 2025
With the transition to Google Analytics 4 (GA4) from Universal Analytics (UA), Google’s native BigQuery integration has become a core part of digital analytics infrastructure. Many life sciences organizations now use BigQuery to derive in-depth first party data insights that go far beyond what the standard GA4 interface provides. This has opened new opportunities for granular audience analysis, downstream personalization, and long-term campaign optimization.
For life sciences, Google Analytics interface provides behavioral insights at an aggregate level; however, BigQuery offers a new window for custom queries and much deeper insights. BigQuery essentially stores the entire data set that is processed by Google Tag Manager (GTM) and can be used by life sciences organizations to derive combinations of metrics and dimensions that are not possible through the standard GA4 interface or application programming interface (API).
This is particularly useful for gaining insights into the engagement and behaviors of specific user groups and effectively personalize their experience with a brand and nudge them to conversion.
Let’s explore how GA4, BigQuery, and first-party data strategies can be effectively leveraged in the life sciences industry to enhance pharma analytics.
Data storage and management for reporting
BigQuery comes with powerful data warehousing capabilities, with most enterprise life science organizations beginning to use BigQuery specifically for this purpose. With Google’s sunset of UA, teams across life sciences organizations are looking for solutions to store the historical data they have previously collected from UA.
For organizations with a Google Analytics 360 subscription, BigQuery has become the tool of choice due to its native integration with GA4. It not only supports efficient GA4 data retention but also enables deeper first-party data insights that go beyond the standard interface.
BigQuery offers scalable storage and processing of massive datasets, allowing life sciences teams to run 1st party analytics and custom queries. Scheduled queries can be set up to transform these raw data into actionable and insightful reports, which are customized to the requirements of different brands and teams within these organizations.
In-depth User Behavior Breakdown and Orchestrations
GA4 data in BigQuery plays a critical role in powering 1st party analytics for life sciences organizations. By leveraging first-party data collected through life science Google Analytics implementations, teams can identify the exact sequence of events taken by HCPs on brand websites that most frequently lead to conversions, such as copay card downloads or brand promotion sign-ups.
Once user segments in this conversion pipeline are defined through Google BigQuery analytics, marketers can deploy targeted orchestrations. These may include personalized emails, ads, or field representative engagement, all informed by behavioral patterns and built on a robust first-party data strategy to improve engagement and conversion outcomes.
Omnichannel Data Correlation
Conversions with high degrees of correlations can also be identified using BigQuery. For example, one from the set of conversion events could be from an offline source. Using BigQuery, the offline prescription data can be stitched with web analytics data to make observations on HCP behavior, such as a high correlation between drug prescriptions (offline) and the download of efficacy-related content from the website of the brand (online). In addition, the general gap in time between these events can be calculated to tailor different online and offline marketing strategies targeted at those HCPs.
Predictive Analytics
The facilitation of predictive analytics is another area where BigQuery enables additional enhancements and insights based on existing GA4 data. For example, an important use case that is relevant for life science organizations is the use of logistic regression to classify HCPs, such as HCPs who are more likely to prescribe and those who are less likely to do so, based on their web interaction data. This would then enable more optimal resource allocation for each segment based on the brand and campaign objectives.
HCP and Patient Journey Mapping
Another key advantage that comes with leveraging BigQuery is in mapping out HCP and patient journeys across multiple touchpoints. Raw data can be analyzed to understand the way interactions across different touchpoints affect HCP and patient journeys.
In a detailed behavioral analysis conducted for a large global life sciences organization using BigQuery data, Indegene was able to uncover insights such as:
The combination of channel interactions that are most likely to drive conversions
The time that a user takes to convert after their first interaction with a touchpoint(s).
The analysis was able to identify those HCPs who had initially interacted with brand emails and subsequently with the brand’s paid search campaigns that had one of the highest conversion rates among other varied channel combinations. With this insight in hand, a new segment of HCPs was created who had interacted with mails but have not had any further interactions with any other brand touchpoints. Targeted paid search campaigns were then run only for this segment, thus saving campaign cost as well as improving conversions.
Looking to the Future of Pharma Analytics
The future is consented. It’s modeled. It’s first-party. So that’s what we’re using as our guide for the next gen of our products and solutions.
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Owing to the increasing privacy concerns and the growing significance of first-party data, web analytics data (in general) are becoming increasingly vital. With third-party cookies deprecated in most major browsers including Chrome, GA4 event-based tracking and Google BigQuery analytics have become essential components of a modern first-party data strategy for life sciences companies. BigQuery’s robust data analysis along with GA4’s event-based tracking will open the door to a multitude of use cases in the life science industry.
These can then serve as solid building blocks for life science organizations looking to build a long-term first-party data strategy. Indegene has been working with some of the world’s top life sciences organizations, helping them embrace this integration and gain a competitive edge in their digital strategy. Reach out to us to learn more about our work, and how we can help your life sciences business.
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