CRM Deal Prediction

Introduction

This tutorial will help you build a machine learning model using Catalyst QuickML that predicts potential deals analyzing the data in Zoho CRM. We will provide you with a sample dataset which can be used as a data source to the model.

In this tutorial, we will first preprocess the datasets to ensure the data is clean and ready for training. Next, we will be constructing a data pipeline to handle data transformation and an ML pipeline to train and evaluate the model. Finally, we will create an endpoint for the trained model, which allows external applications to interact with the model and receive real-time deal predictions.

The Zoho CRM Deal Prediction ML model is built using the following Catalyst service:

Catalyst QuickML : Using this service, we will first pre-process the sample dataset by implementing node operations on them and constructing the data pipeline. This pre-processed data will be used to create an ML model by executing ML algorithms. Finally, the CRM Deal Prediction ML model can be accessed by external applications using the endpoint URL generated in QuickML.

The final output, after creating all the required data and ML pipelines in the Catalyst console, will look like this: