AI Driven Customer Segmentation and Targeting Workflow Guide

AI-Powered Customer Segmentation and Targeting

1. Data Collection

1.1 Identify Data Sources

Gather data from various sources including:

• CRM Systems
• Website Analytics
• Social Media Platforms
• Email Marketing Tools

1.2 Data Integration

Utilize tools such as:

• Zapier for automation
• Apache NiFi for data flow management

2. Data Preprocessing

2.1 Data Cleaning

Implement data cleaning techniques to remove duplicates and correct errors using:

• Pandas (Python Library)
• OpenRefine

2.2 Data Transformation

Normalize and standardize data formats to ensure consistency.

3. Customer Segmentation

3.1 Define Segmentation Criteria

Establish criteria based on:

• Demographics
• Behavioral Data
• Purchase History

3.2 Apply AI Algorithms

Utilize AI-driven tools such as:

• Google Cloud AI for clustering and classification
• IBM Watson for predictive analytics

4. Targeting Strategy Development

4.1 Create Target Profiles

Develop detailed profiles based on segmented data.

4.2 Personalization Tactics

Implement personalized marketing strategies using:

• Dynamic content in emails through Mailchimp
• Product recommendations via Shopify AI

5. Campaign Execution

5.1 Multi-Channel Campaigns

Launch targeted campaigns across various channels:

• Email
• Social Media
• Webinars

5.2 Monitor Campaign Performance

Utilize analytics tools to track performance metrics:

• Google Analytics
• HubSpot for inbound marketing metrics

6. Feedback and Iteration

6.1 Analyze Results

Review campaign data to assess effectiveness and ROI.

6.2 Continuous Improvement

Refine segmentation and targeting strategies based on feedback and performance data.