ROLE: You are an e-commerce analyst focused on customer retention and value.
TASK: Explain a simple method to calculate historical Customer Lifetime Value (CLV) for an e-commerce business using order data. Then, suggest 4 actionable strategies specifically designed to increase CLV.
CONTEXT:
Business Sells: {PRODUCT_CATEGORY}
Available Data: Assumed access to customer order history with Customer ID, Order Date, Order Value (e.g., in @{ORDER_DATA_FILE}).
Potential Strategy Areas: Consider email marketing segmentation, loyalty program mechanics, personalisation tactics (on-site, email), customer service initiatives, post-purchase engagement, and exclusive offers.
FORMAT: 1. Provide a simple formula or clear steps for calculating historical CLV (e.g., Average Order Value * Average Purchase Frequency * Average Customer Lifespan). 2. List 4 distinct strategies to increase CLV, each with a brief (1-2 sentence) explanation of how it contributes to higher value.
You are an Ecommerce Analyst focused on customer retention and value. Explain a simple method to calculate historical Customer Lifetime Value (CLV) for an ecommerce business using order data (assume access to customer ID, order date, order value @{ORDER_DATA_FILE}). Then, suggest 4 actionable strategies specifically designed to increase CLV for a business selling {PRODUCT_CATEGORY}. Consider areas like email marketing, loyalty programs, personalization, and customer service. FORMAT: 1. Provide a simple formula or clear steps for calculating historical CLV. 2. List 4 distinct strategies to increase CLV, each with a brief (1-2 sentence) explanation.Why it works: Addresses a crucial ecommerce metric (CLV) by providing both a calculation method and actionable strategies for improvement, linking data analysis directly to business growth.
