Lead Scoring is such a powerful metric when it comes to quantifying the lead & it is nowadays used by every CRM. In this repository, we are going to take a look at the UpGrad lead scoring case study and see how can we solve this problem through several supervised machine learning models.

Lead Scoring: Optimizing SaaS Marketing-Sales Funnel by Extracting the Best Leads with Applied Machine Learning

An end-to-end enterprise-grade example of working a data science problem.

Typescript library to access Faraday's API infrastructure for B2C predictions

Building a end-to-end lead scoring machine learning example with Jupyter, Sagemaker, MLflow, and Booklet.ai.

In this project, I leverage machine learning models including Logistic Regression, Decision Tree, Random Forest, XGBoost, CatBoost, and LightGBM to predict customer lead scoring. I apply WOE and SHAP for feature selection and use Optuna for hyperparameter turning, aiming to identify potential lead customers effectively.

Trained a model that estimates if a lead is likely to be converted based on lead behavior in historical customer data using ML.

An Automated Lead Management and CRM do star It If you like It.

A Logistic Regression project

Lead Scoring Case Study using Logistic Regression

The second iteration of Cuana, an E2E customer analytics solution for churn/CLV prediction, segmentation & lead scoring

Predictive lead scoring for corporate loan data

X Education has appointed you to help them select the most promising leads, i.e. the leads that are most likely to convert into paying customers.

Comprehensive customer acquisition systems covering modern lead generation, conversion optimization, and customer onboarding methodologies. Build sustainable customer acquisition processes.

Airflow Pipeline for Lead Scoring to Maximize Profit with retraining pipeline and Development experimentation using mlflow

A machine learning tool that predicts the conversion probability of customer leads using Logistic Regression. Helps businesses prioritize high-value prospects.

Lead intelligence dashboard for NHS & Digital market signals. Next.js 16 + Supabase with (n8n) AI-powered scoring, advanced filtering, team tagging, and Excel export.

"E-ticaret iade süreçlerini yöneten n8n workflow çalışmam."

App de Lead Scoring con Inteligencia Artificial para analizar mensajes y detectar intención de compra. Hecha con Python, Streamlit y OpenAI.