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Feb 17, 2025 12:00AM

Amazon's new Customer Loyalty Dashboard helps sellers track and grow customer value. The tool segments customers into loyalty tiers, provides detailed analytics, and enables targeted promotions through Seller Central's Brand Analytics tab.

Brett Bohannon | Link to post

Amazon just released a guide for the Customer Loyalty Dashboard. Summary is below but and the entire guide is attached.


Overview

The Customer Loyalty Analytics Dashboard is a tool available in Amazon’s Seller Central under the Brand Analytics tab. It provides insights into customer shopping behaviors, helping brands increase customer lifetime value (CLV) through data-driven engagement strategies.

Key Benefits
• Increase Customer Lifetime Value: Loyal customers (top 10%) spend 3x more per order than others. A second-time shopper has a 45% chance of buying again.
• Customer Retention vs. Acquisition: A 5% increase in retention can boost profits by 60%.
• Optimized Marketing & Ad Spend: Target the right customers at the right time to improve engagement and return on investment (ROI).
• Reduction in Customer Acquisition Cost: Engage customers who already show interest in your brand.

Dashboard Features

Customer Segmentation

Customers are categorized into four loyalty segments:
• Top Tier: Frequent buyers who spend the most.
• Promising: Occasional buyers with above-average spending.
• At-Risk: Customers who haven't bought recently.
• Hibernating: Inactive customers with infrequent purchases.

Two Dashboard Views:
• Brand View: Overall customer segmentation, sales trends, and targeted promotions.
• Segment View: In-depth data on each customer segment, including repeat purchase trends and predicted lifetime value.
Brand Tailored Promotions:
• New Audiences Feature: Identifies customers whose spending is expected to decline.
• Cart Abandoners Audience: Re-engages shoppers who left items in their cart.

Metrics Available:

• Total Sales
• Average Sales per Customer
• Total Orders
• Repeat Customers & Orders
• Repeat Purchase Rate & Interval

How It Works
• Segmentation is based on RFM (Recency, Frequency, Monetary Value) analysis.
• Machine Learning Predicts Future CLV: Uses customer history, purchase behavior, Prime status, reviews, and browsing activity.
• Actionable Insights:
- Identify and engage high-value customers.
- Target at-risk customers before they stop buying.
- Personalize promotions based on customer segments.

Eligibility

• Available to registered brands in North America, Europe, and Japan.
• Must be an internal brand owner with Brand Analytics access.

How to Access
Navigate to Seller Central > Brand Analytics > Customer Loyalty Analytics

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