Introduction

The Estimated Sales Conversion Rate metric offers valuable insights into product performance in the market. It indicates the likelihood of a customer purchasing a product while browsing its listing and is calculated in-house for all tracked Amazon products.

Purpose and Value

The Estimated Sales Conversion Rate helps businesses understand how effectively their product listings convert potential customers into buyers.

Use Cases

Here are some practical applications of the Estimated Sales Conversion Rate:

  1. Improve Low-Performing Products:
  2. Optimize Pricing Strategy:
  3. Target Competitors’ Audience:

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You can cross-analyze the Estimated Sales Conversion Rate data with the Listing Quality Analysis data to understand the correlation between listing quality and sales performance.

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Data Model

Your DataHawk-powered Snowflake or BigQuery database includes a table for the Estimated Sales Conversion Rate under the PRODUCT schema.

Schema Table About Refresh Rate Primary Key
PRODUCT PRODUCT_ESTIMATED_SALES_CONVERSION_RATE Displays the estimated sales conversion rate of each tracked product Daily product_key, observation_date

Technical Specifications

Interpreting the Estimated Sales Conversion Rate

The Estimated Sales Conversion Rate ranges from 0 to 1, with an average of 10% (0.1). For example, a rate of 0.5 indicates that 1 out of 2 users visiting the listing will likely purchase the product. The table includes lower and upper values for added clarity.

Calculation Method

The Estimated Sales Conversion Rate is computed using an in-house AI algorithm that evaluates key product features such as fair pricing, high-quality product information, fast delivery, positive reviews, and good ratings. This algorithm estimates the purchase probability with an average error margin of approximately 5%.

Considerations

The dataset is updated daily with new entries for each tracked product.