DataHawk's Listing Quality Score is a metric computed by DataHawk that assesses 15 different individual sub-score items related to 5 non - customizable sub-score categories that are based on Amazon's content guidelines:

  1. Image Standards Score (1 item)

  2. Title Standards Score (6 items)

  3. Key Features or Bullet Points Standards Score (6 items)

  4. Product Description Standards Score (1 item)

  5. A+ Content Standards Score (1 item)

The higher the score, the better!

Get started by creating your projects and adding products to them once you are logged in to the platform. There are two ways by which you can access the LQS:

1) Listing Analysis Tool:

The Product Details page gives you access to various tools that you can use to analyze your products.

Here, you have a snapshot of the selected products' LQS, enabling you to audit the quality of your product listings via detailed scores and monitor their changes. You can choose to analyze the LQS of the selected product for a desired range of time shown by day, week, or month.

DataHawk also provides you with recommendations to improve your listings. You can hover over each Subscore to view the suggestions for Amazon-compliant product listings.

While the detailed Product Listing Quality tool can be accessed from a product's page under the Listings Analysis tool, the executive Listing Quality Score Dashboard can be accessed from the SEO Section.

2) SEO Dashboard:

The Listings Quality Score section also sits in the SEO Practice section within DataHawk Analytics.

Click on the "Listing Analysis" tab under SEO from the navigation bar on the left.

This enables you to study the evolution of the Listings Quality Score of products on an account-level, project-level, and product-level basis. Furthermore, you have a breakdown of tracked products with detailed listing scores and status, namely, good, acceptable, improvable & bad.

(The Listing Quality Subscores go into the computation of the overall Listings Quality Score.)

Optimize the content with an analytical approach with DataHawk. Learn how to use the DataHawk Listing Analysis tool.

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