Refining user behavior analytics for SaaS based applications: product usage and customer churn analysis
Hakala, Veeti (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024121034280
https://urn.fi/URN:NBN:fi:amk-2024121034280
Tiivistelmä
The need for understanding user behavior through data analytics has been emphasized by the increased complexity of software-as-a-service (SaaS) applications, especially in the business-to-business (B2B) segment. Many organizations still face difficulties implementing efficient analytics solutions, which provide valuable insights. The research focuses on assignor company's challenges with user behavior and product usage analysis within their SaaS based applications.
The objective was to enhance the existing analytics setup by improving the data collection, cleaning the test users from analysis and to create new reports to identify the product usage and identify potential customer churn. The research was done as research-based development assignment.
The implementation contained further development of a Snowplow event tracker to collect user and registration information, custom queries in Big Query to link data from different data sources to exclude test environments from the data sets and creating new reports with Looker Studio.
As a result, two new reports were created: a report of product usage and customer churn indicator report to recognize decreasing customer engagement among recently registered customers.
Research demonstrated, that constructed user behavior analytics implementation can provide valuable insights to stakeholders. The primary objectives were achieved but needs for further development were recognized by expanding the depth of the created analysis tools.
The objective was to enhance the existing analytics setup by improving the data collection, cleaning the test users from analysis and to create new reports to identify the product usage and identify potential customer churn. The research was done as research-based development assignment.
The implementation contained further development of a Snowplow event tracker to collect user and registration information, custom queries in Big Query to link data from different data sources to exclude test environments from the data sets and creating new reports with Looker Studio.
As a result, two new reports were created: a report of product usage and customer churn indicator report to recognize decreasing customer engagement among recently registered customers.
Research demonstrated, that constructed user behavior analytics implementation can provide valuable insights to stakeholders. The primary objectives were achieved but needs for further development were recognized by expanding the depth of the created analysis tools.