Our client is a leading manufacturer of healthcare devices for home use. Their business covers a broad spectrum of services that range from industrial automation and electronic components to social systems and healthcare.
 

• Incomplete GA Implementation: The existing Google Analytics setup was not well implemented and failed to track crucial custom events such as device login, pair, and sync.
• Data Aggregation Failure: Google Analytics could not provide simple aggregate counts (e.g., total number of users unable to pair), requiring complex manual analysis of multiple reports.
• Data Disparity: Reported app install numbers were inconsistent and showed significant disparities across Google Analytics, Google Play, and iTunes Analytics.
• Lack of Actionable Insights: Without reliable, consolidated data, the client was unable to make informed decisions about product features or user experience.
   

QBurst implemented a robust, data-driven analytics solution that went beyond the limitations of default Google Analytics. The core of the solution involved not only re-configuring GA but also creating a custom consolidation and reporting system using Microsoft Excel.

Our team first audited and corrected the flawed GA implementation by setting up custom dimensions, metrics, events, and goals to track specific, high-value actions (transfer, pair, sync) that were previously unmonitored.
 

To solve the data disparity and aggregation challenges, we developed a comprehensive monthly Excel dashboard. This report consolidated data from multiple sources—Google Analytics, Google Play, and iTunes—to provide a single, reliable source of truth for metrics that GA could not aggregate directly.
 

• Custom GA Configuration: Set up custom dimensions, metrics, and goals in Google Analytics to track crucial events not tracked by default.
• Multi-Source Data Consolidation: Developed a monthly Microsoft Excel dashboard that unified disparate data from GA, Google Play, and iTunes Analytics.
• GA Dashboards: Built four custom dashboards within Google Analytics (General usage, Features usage, Login/transfer/pair, Top 10 users).
• KPI Trend Analysis: Created Excel dashboards for weekly, monthly, and quarterly trends of important KPIs (e.g., active users, registrations, pair success rates).
• Granular Metric Reporting: Enabled tracking of specific metrics like sync success/failure rates, users with multiple devices, and inactive devices.
   

• Data-Driven Product Decisions: The client could finally identify which devices were active/inactive and which features were most used by customers, directly influencing future product versions.
• Enhanced Product Features: Crucial updates were made to both the mobile apps and the fitness devices based on the new, reliable insights into user behavior.
• Improved Operational Efficiency: The automated Excel reports provided a unified view of KPIs, saving an estimated 40% of the time previously spent on manual data consolidation.
• Increased User Engagement: By identifying and improving the most popular features, the client improved user experience, leading to a 30% increase in user engagement with key app functionalities.