Problem
Our client, an e-learning platform, faced a challenge in understanding and analyzing their customer behavior due to missing necessary insights. They had data, but it was not used effectively to generate value. The specific pain points and obstacles included:
- Inconsistent data quality
- Unstructured data
- Limited data visualization capabilities
- No unified data storage
- Limited insights into customer behavior and preferences
Solution
To address the challenge at hand, the SmartCat team undertook a comprehensive evaluation of the client’s existing tech stack and proposed a revamped architecture solution. The team employed the following strategies and tactics to achieve the desired outcome:
- Acquiring data from various sources: To ensure a comprehensive data collection process, the team selected Segment and implemented an ingestion pipeline solution. This enabled the swift gathering of events from multiple sources, including the main application, Google Analytics, Facebook, Contentful, and more. Additionally, Stich was utilized to facilitate seamless communication between databases, allowing for efficient data extraction into BigQuery.
- Data storage organization: In order to optimize data retrieval and reporting, the team meticulously organized the data within BigQuery. Raw data underwent processing to enhance readability, with a specific focus on highlighting key performance indicators (KPIs) and other essential metrics. This organization streamlined the subsequent reporting process.
- Developing a reporting solution: A dedicated connector was developed for Data Studio, facilitating the aggregation of events. The team meticulously defined and created events, ensuring data was structured in a manner that aligns with the requirements of the reports. Furthermore, visualizations for analytics purposes were crafted, and Data Studio reports were meticulously designed and developed.
- Advanced reporting capabilities: To cater to the need for more advanced reporting functionalities, the team implemented the reporting solution within Looker. This step enhanced the capabilities of the reporting system, enabling more sophisticated and tailored analyses and insights.
By implementing these strategies and tactics, the SmartCat team successfully addressed the challenge and provided the client with a robust and improved architecture solution.
Results
The outcomes of the solution were as follows:
- Collected events? and organized storage optimized for important metrics and KPI’s
- Reports were developed and optimized, and KPIs were visualized to bring important value to the client.
Key metrics included customer behavior and preferences, engagement, retention, and course effectiveness. The quantifiable results of our efforts were improved insights into customer behavior, more accurate and consistent reporting, and improved decision-making capabilities.
Smart Tip
Spend more time analyzing data quality to ensure successful planning and implementation of the solution. Quality and accuracy of reporting are crucial for generating value from data.
Smart Fact
The client hired a marketing agency to increase traffic, but after analyzing the increase in traffic, it turned out that the agency used a bot to provide traffic, which created a false impression about users. The SmartCat team identified the bot’s pattern and excluded the problematic data from the analysis.
About the Client
The client is an e-learning platform with over 20 employees in the education industry.
Technologies Used
The SmartCat team used MongoDB, BigQuery, Google Analytics, SQL for storage and queries, Stitch, Segment, DataForm for ETL, and DataStudio, Looker for reporting.
