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Mobile App Analytics for a Healthcare Device Manufacturer

Client

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.

Industry

Technology / Healthcare

Offering

Analytics support for a wearable device that tracks blood pressure and fitness-related data. The device syncs with smartphones via an app that helps users set goals, track vitals, fitness stats, and progress. Both iOS and Android mobile apps are available for use. We provided a data-driven analytics solution to gauge user engagement. Usability metrics were used to improve user experience and KPIs of the apps. Based on insights gained, our client was able to enhance product features and drive more sales.

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Business Requirement

Identify app features that are most useful to customers and gauge how healthcare devices are being used by consumers. The requirement includes leveraging analytics data from apps to drive sales for products.

Business Challenges

Google Analytics had been set up for the iOS and Android apps by another vendor; however, it was not well implemented. A lot of customizations were required on Google Analytics to track user interactions and events that could not otherwise be tracked by default.

A key requirement was to fetch the count of users performing various actions such as login, pair, and sync. Google Analytics does not offer an option to view aggregate counts of any dimension. The client required metrics such as number of users who are unable to pair their devices, total number of auto-sync events, and count of devices used by more than one user. It was not possible to view this on a Google Analytics dashboard. Data from multiple custom reports were required.

Finding out the number of monthly app installs on app stores was another challenge. Although app installs can be linked to Google Analytics, there were disparities in the values shown on Google Analytics, Google Play Analytics, and iTunes Analytics.

QBurst Solution

For reporting purposes, several custom dimensions, metrics, events, and goals were set in Google Analytics to track specific data (including transfer, pair, and sync) that are otherwise not directly tracked via Google Analytics.

We set up four custom dashboards in Google Analytics to automate the reporting process.

  • General usage report
  • Features usage report
  • Login, transfer, and pair events report
  • Top 10 users report

All reporting items that could not be displayed directly on Google Analytics and required further manual analysis were provided in an Excel dashboard. This included data from multiple sources such as Google Analytics, Google Play , and iTunes. The required data was exported from necessary sources, carefully scrutinized, and grouped under specific dashboards in the Excel report.

The Excel report shared with the client each month includes six dashboards.

  • Google Analytics Dashboard
  • Apps Dashboard
  • Sync/Pair Dashboard
  • Features Dashboard
  • Devices Dashboard
  • Users Dashboard

In order to help business users analyze the trend of key metrics, we created an Excel dashboard with weekly, monthly, and quarterly trends of important KPIs.

Key Features

The custom daily, weekly, and monthly KPI trend analysis reports helped our client to gain insights into customer interactions with the app over time.

  • Daily trend of app installs
  • Monthly trend of active users
  • Monthly trend of registrations
  • Monthly trend of users who paired one device
  • Monthly trend of users who paired more than one device
  • Monthly trend of active devices
  • Monthly trend of emails shared
  • Quarterly trend of active users
  • Hourly trend of active users
  • Hourly trend of successful pairs
  • Daily trend of successful uploads
  • Daily trend of logins

Other important custom-generated KPIs included in reports also provided them insights into:

  • Average user to device information
  • Average number of devices in use in a month
  • Total number of inactive devices
  • Unique number of active users (quarterly)
  • Pair success / failure rate
  • Sync success / failure rate

Business Benefits

Business users can identify devices that were active/inactive over a period of time and features that were predominantly used by customers. This enabled our client to focus on improving such features and applying them in future product versions. Crucial updates were made in apps and fitness devices based on such insights.

Technologies

  • Google Analytics
  • iTunes and App Store Analytics
  • Microsoft Excel

Business Requirement

Identify app features that are most useful to customers and gauge how healthcare devices are being used by consumers. The requirement includes leveraging analytics data from apps to drive sales for products.

Business Challenges

Google Analytics had been set up for the iOS and Android apps by another vendor; however, it was not well implemented. A lot of customizations were required on Google Analytics to track user interactions and events that could not otherwise be tracked by default.

A key requirement was to fetch the count of users performing various actions such as login, pair, and sync. Google Analytics does not offer an option to view aggregate counts of any dimension.The client required metrics such as number of users who are unable to pair their devices, total number of auto-sync events, and count of devices used by more than one user. It was not possible to view this on a Google Analytics dashboard. Data from multiple custom reports were required.

Finding out the number of monthly app installs on app stores was another challenge. Although app installs can be linked to Google Analytics, there were disparities in the values shown on Google Analytics, Google Play Analytics, and iTunes Analytics.

QBurst Solution

For reporting purposes, several custom dimensions, metrics, events, and goals were set in Google Analytics to track specific data (including transfer, pair, and sync) that are otherwise not directly tracked via Google Analytics.

We set up four custom dashboards in Google Analytics to automate the reporting process.

  • General usage report
  • Features usage report
  • Login, transfer, and pair events report
  • Top 10 users report

All reporting items that could not be displayed directly on Google Analytics and required further manual analysis were provided in an Excel dashboard. This included data from multiple sources such as Google Analytics, Google Play , and iTunes. The required data was exported from necessary sources, carefully scrutinized, and grouped under specific dashboards in the Excel report.

The Excel report shared with the client each month includes six dashboards.

  • Google Analytics Dashboard
  • Apps Dashboard
  • Sync / Pair Dashboard
  • Features Dashboard
  • Devices Dashboard
  • Users Dashboard

In order to help business users analyze the trend of key metrics, we created an Excel dashboard with weekly, monthly, and quarterly trends of important KPIs.

Key Features

The custom daily, weekly, and monthly KPI trend analysis reports helped our client to gain insights into customer interactions with the app over time.

  • Daily trend of app installs
  • Monthly trend of active users
  • Monthly trend of registrations
  • Monthly trend of users who paired one device
  • Monthly trend of users who paired more than one device
  • Monthly trend of active devices
  • Monthly trend of emails shared
  • Quarterly trend of active users
  • Hourly trend of active users
  • Hourly trend of successful pairs
  • Daily trend of successful uploads
  • Daily trend of logins

Other important custom-generated KPIs included in reports also provided them insights into:

  • Average user to device information
  • Average number of devices in use in a month
  • Total number of inactive devices
  • Unique number of active users (quarterly)
  • Pair success / failure rate
  • Sync success / failure rate

Business Benefits

Business users can identify devices that were active / inactive over a period of time and features that were predominantly used by customers. This enabled our client to focus on improving such features and applying them in future product versions. Crucial updates were made in apps and fitness devices based on such insights.

Technologies

  • Google Analytics
  • iTunes and App Store Analytics
  • Microsoft Excel

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