CDP Training Course

In this LEO CDP Specialty course, students will learn about the LEO CDP framework, including how to unify customer data with pre-built connectors, predict customer intent with rich segmentation, and maintain control of customer data. 

This course begins with importing and transforming your customer data and culminates with extending your customer data platform solution into the LEO CDP

Customer Data Platform Course Benefits

1. Clean, transform, and ingest data into LEO CDP

2. Create a unified customer profile

3. Work with Customer 360 Profile insights

4. Enrich data and predictions

5. Set up and manage external connections

6. Administer and monitor Customer Insights

Prerequisites:

1. Knowledge about Linux, Dev-Ops and Cloud Computing

2. Digital Business and Internet

3. Basic Knowledge about HTML, CSS and JavaScript

4. Core Digital Marketing Mindset

5. Knowledge about Data Analytics

6. Understanding how to create a comprehensive Customer Journey Map

Who should attend?

Customer Data Platform specialists implement solutions with 3 purposes:

• Provide insight into customer profiles
• Track engagement activities to help improve customer experiences
• Increase customer retention

Module 1: Get started with LEO CDP

In this module, you will learn to:

1. Describe the value of a customer data platform

2. Describe the functionality of LEO CDP and system architecture 

3. Administer environments and users in LEO CDP

Lab: Setup and verify environment

Module 2: Ingest data into LEO CDP

In this module, you will learn to:

1. Perform data transformation and import data using CSV Data File 

2. Connect to LEO Profile API  and Common Data Model sources

3. Set up scheduling job for data refreshes and data importing automation

Lab: Ingest data from CSV and LEO Profile API

Module 3: Create a unified customer profile in LEO CDP

In this module, you will learn to:

1. Map data, including using intelligent mapping, primary keys, and attribute types

2. Match data, including specifying order, rules, conditions, and de-duplication

3. Merge data using system recommendations or manually

4. Configure search and filter indexes

5. Search for customers

Lab: Unify the data

Module 4: Work with LEO CDP

In this module, you will learn to:

1. Explore Customer 360 Analytics

2. Define activities and event metrics

3. Define event scoring model

4. Manage segments and get suggested segments

Lab: Work with event activities

Lab: Define event metrics

Lab: Create segments

Module 5: Enrich data and predictions with LEO Machine Learning Templates

In this module, you will learn to:

1. Identify the different options for data enrichment

2. Enrich customer data with LEO machine learning templates

3. Predict what the customer will most likely buy using LEO Personalization Engine

4. Use machine learning models

5. Describe responsible AI principles

Lab: Create a Customer Personalization Model

Lab: Deploy Product Recommendation in website

Lab: Enrich data with natural language processing analytics and third-party data platforms

Module 6: Manage external connections with Customer Data Platform

In this module, you will learn to:

1. Explore LEO CDP API

2. Surface Customer Insights data in LEO CDP

3. Use Customer Insights and Visualization with Jupyter Notebook / Google Colab

4. Build your own customer dashboard using Apache Superset and CDP

Lab: Extend with the LEO Data Connector

Lab: Extend with the LEO CDP apps