Introduction

The Estimated Sales Conversion Rate metric provides insights into how well products are performing in the market. It represents the probability of a customer purchasing a product while browsing the product listing. It is computed in-house for all tracked Amazon products.

Business Needs

The Estimated Sales Conversion Rate helps understand how effectively a listing is converting potential customers into actual buyers.

Benefits

Using the Estimated Sales Conversion Rate brings the following benefits:

• Lower customer acquisition costs by making informed decisions about your marketing and sales strategies
• Optimize your product listings
• Measure the effectiveness and optimize your marketing campaigns
• Stay competitive in your respective markets

Scenarios

Here are a few examples of scenarios you can implement:

1. Identify and optimize low-performing products:
   • Sort the data in the estimated sales conversion rate table to identify products with low estimated sales conversion rates
   • Analyze the data further to understand why these products are not selling as well as others. You can for example check their Listing Quality Score.
   • Consider making changes to the product's listing, packaging, pricing, or marketing strategy to improve its conversion rate
2. Determine pricing strategy:
   • Analyze the estimated sales conversion rate data to determine how price affects conversion rates for different products
   • You can experiment with different pricing strategies for low-performing products to see if a price adjustment improves their conversion rates
   • Use the data to set optimal prices for each product that maximize revenue and profitability
3. Target your competitors' audience:
   • Use our Competitors dataset to identify your product's competitors
   • Identify the competitors with a lower estimated sales conversion rate (SCR)
   • Advertise on these competitor products with a lower SCR to redirect their audience to your product

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Tip

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

These are a few examples of how you can use estimated sales conversion rate data to improve your business's overall performance.

Data Model

Using destinations, your accompanying DataHawk-powered Snowflake or BigQuery database contains one table that contains Estimated Sales Conversion Rate. This table is available under the PRODUCT schema.

Technical Specifications

How to read the Estimated Sales Conversion Rate?

The Estimated Sales Conversion Rate is a value that ranges between 0 and 1, with an average of 10% (0.1).

An Estimated Sales Conversion Rate of 0.5 means that 1 out of 2 users that visit the listing will likely purchase the product.

The table also provides lower and upper values to add clarity and precision to the interpretation of the estimated sales conversion rate.

How do we compute the Estimated Sales Conversion Rate?

Based on data collected from tens of thousands of products, we have identified the main product features that strongly influence whether a customer is likely to make a purchase. These criteria include fair pricing, high-quality product information, fast delivery, positive reviews, and good ratings.

The Estimated Sales Conversion Rate is computed by an in-house AI algorithm that combines these criteria and provides the probability that a customer will buy or not. It has an average error margin of approximately 5%.

Considerations

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

Future Development

Currently, this metric is only calculated for Amazon products. Support for Walmart products will be available in the future.