Customer Segmentation Template (CSV/Excel Format)

Customer ID	Age	Gender	Income	Purchase History	Frequency of Purchase	Brand Engagement (Email Opens)	Social Media Interactions (Clicks/Comments)	Product Preferences	Segment
001	30	Male	$60,000	Product A, Product B	Monthly	20%	15 clicks, 5 comments	Tech, Gadgets	Tech Enthusiast
002	24	Female	$50,000	Product C	Bi-monthly	45%	50 clicks, 20 comments	Fashion, Apparel	Fashionista Shopper
003	40	Male	$75,000	Product D, Product E	Quarterly	15%	8 clicks, 2 comments	Practical, Home Goods	Practical Saver
004	28	Female	$45,000	Product F	Monthly	60%	30 clicks, 12 comments	Tech, Accessories	Tech Enthusiast
005	35	Female	$80,000	Product G, Product H	Weekly	30%	10 clicks, 3 comments	Fashion, Shoes	Fashionista Shopper
006	50	Male	$65,000	Product I	Bi-annually	10%	3 clicks, 1 comment	Practical, Tools	Practical Saver

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2. Segmentation Data Explained:

• Customer ID: Unique identifier for each customer.
• Age: Customer’s age (for demographic profiling).
• Gender: Gender identification (useful for targeting certain segments).
• Income: Annual income (helps define purchasing power).
• Purchase History: A list of products bought by the customer (can help understand buying habits).
• Frequency of Purchase: How often the customer buys from your brand.
• Brand Engagement (Email Opens): Percentage of marketing emails opened by the customer (gives insight into how likely they are to engage with offers).
• Social Media Interactions: Number of interactions, like clicks or comments, on social media posts (helps understand their activity and brand interest).
• Product Preferences: The type of products the customer tends to prefer (Tech, Fashion, Practical).
• Segment: Behavioral segment based on data analysis (Tech Enthusiast, Fashionista Shopper, Practical Saver).

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3. Steps to Create a CSV or Excel File:

1. Open Excel or Google Sheets.
2. Create columns based on the attributes you want to capture (refer to the template above).
3. Enter Data: Input the data for each customer (e.g., demographics, purchase history, and behavioral data).
4. Save as CSV:
   • In Excel: Go to File > Save As > Choose CSV format.
   • In Google Sheets: Go to File > Download > Comma Separated Values (.csv).

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4. Usage and Application:

• Data Analysis: Use this segmentation data to analyze customer behavior, preferences, and purchase habits. Identify patterns and insights to drive targeted marketing.
• Marketing Personalization: Customize campaigns based on each segment’s unique characteristics.
• Customer Insights: Better understand customer needs and interests to improve products and services.

If you need further help formatting specific data or