Beginner’s Guide to Machine Learning and Power BI: Building a Lead Scoring Dashboard
Step-by-Step Tutorial for Building a Machine Learning-Powered Lead Scoring Dashboard with Power BI
Introduction
This tutorial will walk you through the process of building a lead scoring dashboard with Power BI. We will use a dataset of 1000 leads and build a machine learning model with pycaret to predict the likelihood of a lead converting to a customer. We will then use the model to score the leads, store the new lead dataset in a PostgreSQL database and visualize the results in Power BI.
You can find the code for this tutorial on my GitHub here.
Prerequisites
- Basic knowledge of Python
- Basic knowledge of Power BI
- Basic knowledge of SQL
- Basic knowledge of machine learning classification models
What is Lead Scoring?
Lead scoring is a process of assigning a score to a lead based on their behavior and profile. The score is used to determine the likelihood of a lead converting to a customer. Lead scoring is a common practice in the marketing industry and is used to prioritize leads for sales teams.
