PROPEL YOUR BUSINESS USING AI & FUTURE TECH

Automated Data Scraping and Tracking for Stream Analytics

Project Overview

WGMI Labs was tasked with creating a custom application for a client aimed at automating the tracking and analysis of streaming data from a specific platform. This project was crucial in transitioning from manual spreadsheet updates to an automated, efficient system. The application was designed to scrape data from the platform and present it in a tailored dashboard, streamlining the entire data management process.

The Challenge

The primary challenge was developing an automated data scraping system. This system needed to accurately and efficiently gather detailed information from the streaming platform, including metrics like sales, costs, stream duration, and viewer analytics.

Another significant task was creating a custom analytics dashboard. This dashboard had to not only display the scraped data but also offer comprehensive insights into various metrics. These metrics included sales per hour, streamer efficiency, and buyer ratios, which were critical for the client's analysis and decision-making processes.

Additionally, the application required advanced segmentation and search functionalities. This meant enabling users to segment data by stream, streamer, and account, and providing the ability to conduct advanced searches based on date and other relevant parameters.

Solutions

In response to these challenges, we successfully implemented an automated data scraping system. This system was meticulously designed to capture all the necessary data from the streaming platform with high accuracy and efficiency.

We also developed a custom analytics dashboard that displayed the collected data in a user-friendly format and provided deep insights into key performance metrics. Equipped with tools for analyzing sales, streamer efficiency, and other vital aspects of streaming performance, this dashboard enabled users to make informed decisions based on comprehensive data analysis.

Conclusion

The segmentation and search functionality were carefully integrated into the application. Users could now segment the data based on various categories and perform detailed searches.

This enhancement significantly improved the usability of the application, allowing for more targeted and efficient data analysis. With these advanced features, users could quickly and easily access the specific information they needed, making their analysis more precise and effective.