Leonard
Liebenberg

Data Analyst

SQL | Python | Power BI

Creating Lead Clusters
Using K-Prototype Algorithm

Our aim is to gain a deeper understanding of which agents are more effective in selling to specific lead profiles.
We seek to identify the most suitable agents for each lead profile by analyzing their performance and sales data.
By doing so, we can optimize our sales process and increase our conversion rates, ultimately resulting in higher revenue for the company.

Contactability Score
Using SQL

A complex SQL query that generates a comprehensive contactability score by analyzing multiple input parameters. This score is then utilized to prioritize leads, with those possessing a higher score given top priority.

A Speech-to-Text
Data Pipeline

The app includes a robust data pipeline that seamlessly extracts recordings from an SFTP server. The pipeline further creates a comprehensive CSV metadata file and efficiently uploads the data to an S3 bucket. Once the data is securely stored in the cloud, A speech-to-text engine (Made possible through Callbi) takes over, retrieving the data and transcribing it into a JSON format file. These Json files were later imported to a MongoDB database where they were used in creating dashboards for end users.