AI Driven Customer Segmentation and Targeting Workflow Guide

AI-Enhanced Customer Segmentation and Targeting

1. Data Collection

1.1. Identify Data Sources

Gather data from various sources including:

• Website analytics
• Customer purchase history
• Social media interactions
• Email marketing responses

1.2. Data Integration

Utilize tools such as:

• Google Analytics: To track customer behavior on the website.
• CRM Systems (e.g., Salesforce): To consolidate customer information.

2. Data Processing

2.1. Data Cleaning

Implement AI algorithms to clean and preprocess data, ensuring accuracy and consistency.

2.2. Data Enrichment

Enhance customer profiles using third-party data sources, such as:

• Clearbit: For additional demographic information.
• FullContact: To enrich customer data with social profiles.

3. Customer Segmentation

3.1. Define Segmentation Criteria

Establish criteria based on:

• Demographics
• Purchase behavior
• Engagement levels

3.2. Apply AI Algorithms

Utilize machine learning models for segmentation, such as:

• K-Means Clustering: To group customers based on similarities.
• Decision Trees: To identify key factors influencing customer behavior.

4. Targeting Strategies

4.1. Personalized Marketing Campaigns

Leverage AI-driven tools to create targeted campaigns:

• Dynamic Yield: For personalized product recommendations.
• Mailchimp: For tailored email marketing based on customer segments.

4.2. Predictive Analytics

Use predictive models to forecast customer needs and preferences, employing tools like:

• Adobe Analytics: For insights into customer behavior trends.
• IBM Watson: To analyze and predict customer purchase patterns.

5. Performance Measurement

5.1. Key Performance Indicators (KPIs)

Establish KPIs to measure the effectiveness of segmentation and targeting strategies, such as:

• Conversion rates
• Customer retention rates
• Return on investment (ROI) of marketing campaigns

5.2. Continuous Improvement

Utilize AI tools for ongoing analysis and refinement of segmentation strategies:

• Tableau: For data visualization and performance tracking.
• Google Optimize: To A/B test different marketing strategies.