Listing Quality Analysis

Introduction

The Listing Quality Analysis (LQA) datasets are designed to help you optimize your Amazon and Walmart listings. The datasets provide an in-depth analysis of key criteria that impact the quality and performance of your listings, including title, description, bullet points, and media criteria. With these datasets, you can identify areas for improvement and make data-driven decisions to enhance the visibility and sales potential of your products.

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Considerations

This article details new LQA datasets. The following tables are independent material:

PRODUCT_LISTING_QUALITY_SCORE
PRODUCT_LISTING_QUALITY_SCORE_BREAKDOWN

Glossary

Criteria

Criteria are specific characteristics that can be observed in a listing, such as the number of images or the length of the title. Every day, we analyze your tracked products and extract the data corresponding to each of these criteria. This extracted data is the observed content for a specific criterion.

Rules

Every day, we compare your products against a set of Amazon guidelines and recommendations that we call Rules. They are sourced from Amazon’s official documentation. Walmart will be supported in the future.

Listing Quality Score (LQS)

The LQS is a default score that we compute based on the LQA rules, using weights assigned to each rule according to Amazon guidelines. The more important a rule is for the quality of your listing, the greater its weight.

This score is based on an in-house weighting system; we provide it as a starting point. You can build your score using all the available data.

Section

A section is a basic content element of your listing. We analyze four sections: Title, Description, Bullet Points, and Media.

Business Needs

This section details how to use the LQA datasets to:

  • Diagnose the quality of your listing content
  • Rank higher in search results
  • Convert more users to purchase
  • Diagnose the quality of your competition’s listing content

Content

With these LQA datasets, you will be able to improve the quality of your listings’ content.

  • Monitor the evolution of your listing quality over time to refine your listings with the historicized and daily updated datasets. Narrow down the listings that require improvements, implement the recommended changes, and track your progress.
  • Finetune your listings to be compliant and optimized on Amazon and Walmart with the LQA rules dataset. Leverage the LQA Criterion dataset to understand why each recommendation is provided by looking into the detailed analysis of your content.
  • Create your listing quality score by combining the available analyzed criteria and implementing the most relevant formula to your business.

Market

With these LQA datasets, you will be able to get Market insights.

  • Compare your products’ listing quality score with your closest competitors by leveraging the Listing Quality Score and the Competitors datasets.
  • Study how competitors with high listing quality build their listing.

Benefits

  • Improved visibility and sales: by identifying quickly which changes to implement on your listings, you help your products stand out on Amazon & Walmart, increase your visibility, enhance your customer experience, and increase your sales.
  • Efficient use of your time: by leveraging the LQA datasets, you prioritize your efforts and focus on the listings that are likely to have the most significant impact on your business.
  • Identify which of your products have an edge on the competition and which ones are falling behind in terms of listing quality.

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Tip

With destinations, you can enrich your analysis with all the information about your products, such as their sales or estimated monthly sales, price, rating... It enables to analyze specific subsets of products, such as those with the highest sales, the most significant volume, or newly launched ones. Additionally, you can leverage the tags system to analyze a specific selection of products.

Data Model

Using destinations, your accompanying DataHawk-powered Snowflake or BigQuery database contains multiple tables about Listing Quality Analysis. These tables have a very exhaustive list of data points as columns and are organized into schemas. All Listing Quality Analysis data is available under the PRODUCT schema.

SchemaTableAboutRefresh RatePrimary Key
PRODUCTPREVIEW_PRODUCT_LQA_CRITERIONDisplays the observed content of multiple criteria for each tracked productDailyproduct_key, criterion_key, observation_date
PRODUCTPREVIEW_PRODUCT_LQA_RULEProvides data on the compliance of tracked products with a set of Amazon or Walmart rules and recommendationsDailyproduct_key,
rule_key,
observation_date
PRODUCTPREVIEW_PRODUCT_LQA_SCOREDisplays the global Listing Quality Score as well as Title, Description, Bullet Points, and Media Listing Quality Scores of all tracked productsDailyproduct_key,
observation_date
PRODUCTPREVIEW_PRODUCT_LQA_RULE_CRITERION_ASSOCIATIONMatching table between rules and criteria tablesDailyrule_key,
criterion_key

Technical Specifications

Available criteria

CRITERIONSECTIONOBSERVED CONTENT EXAMPLEEXPLANATION
Character count in titleTITLE256The title is 256 characters long.
Stop words in titleTITLEforThe titlte contains one stop word, for.
Capitalized first letter in title's wordsTITLEtrue,true,true,true,falseThe first four words of the title are capitalized, the fifth one is not.
Capitalized conjunctions in titleTITLEFor,WithThe title contains two capitalized conjunctions, For and With.
All caps words in titleTITLEAMAZING,APPLEThe title contains two words in all caps, BEAUTIFUL and APPLE.
Brand name in titleTITLEThisismybrandThe title contains the brand name Thisismybrand.
Promotional words in titleTITLEdiscountThe title contains the promotional word discount.
Decorative characters in titleTITLE<,>The title contains two decorative characters, < _and >_
NON_ASCII characters in titleTITLE©,§The title contains two NON_ASCII characters, © and §.
Restricted keywords in titleTITLERated #1The title contains 1 restricted keyword, Rated #1.
Emojis in titleTITLE🙂The title contains 1 emoji, 🙂.
Price currencies in titleTITLE$The title contains 1 price currency, $.
Alphabetical numbers in titleTITLEFive, sevenThe title contains two alphabetical numbers in the title, Five and seven.
Bullet points countBULLET POINTS5The listing contains 5 bullet points.
Character count in each bullet pointBULLET POINTS400,326,161,249The first bullet point is 400 characters long, the second one 326, the third one 161, and the fourth one 249.
Total character count of all bullet pointsBULLET POINTS600The total count of characters of all bullet points is 600.
Ending punctuation in each bullet pointBULLET POINTSfalse,false,true,true,trueThe first two bullet points do not have ending punctuation, the last three bullet points have ending punctuation.
Capitalized first letter in each bullet pointBULLET POINTStrue,true,true,true,falseThe first 4 bullet points have a capitalized first letter, but not the 5th one.
Character count in descriptionDESCRIPTION858The description is 858 characters long.
A+ content includedDESCRIPTIONTRUEThe listing contains A+ content.
Image countMEDIA4The listing contains 4 images.
Video countMEDIA2The listing contains 2 videos.

The observed content may be null or empty.

A null observed content means that we were unable to extract the corresponding data, so we do not know what the observed content is.

An empty observed content means that we did not observe the criterion in question. For example, an empty observed content for the criterion Emojis in title indicates that we did not find any emojis in the title.

Available Rules and Listing Quality Score (LQS) weights

Our LQS score is based on a subjective weighting system, we provide it as a starting point for your analyses. You can also build your own score using all the available data. The more important a rule is for the quality of your listing, the greater its weight.

CHANNELRULESSECTIONDATAHAWK LQS WEIGHTLQS WEIGHT EXPLANATION
AmazonNo restricted keywords in titleTITLE5Amazon prohibits a list of keywords
AmazonNo characters decoration in titleTITLE2Moderately important to maintain readability
AmazonTotal bullet points length below 1000 charactersBULLET POINTS4Amazon recommends keeping the total character count for all bullet points to 1000 or less
AmazonAt least 3 bullet pointsBULLET POINTS5Amazon requires at least 3 bullets points that are concise and easy to read
AmazonDescription length at least 1000 charactersDESCRIPTION5Very important for a comprehensive explanation of the product and its features
AmazonAt least 1 imageMEDIA5Very important as it provides a visual representation of the product
AmazonAt least 1 videoMEDIA5Very important as it provides a visual representation of the product
AmazonBrand name included in titleTITLE5Important for searchability
AmazonBetween 5 and 6 bullet pointsBULLET POINTS3Moderately important to maintain readability
AmazonNo capitalized conjunctions in titleTITLE2Moderately important to maintain readability
AmazonBetween 5 and 7 imagesMEDIA3Considered optimal to showcase the product
AmazonNo Non-ASCII characters in titleTITLE3Important to maintain compatibility and readability
AmazonFirst letter of bullet points capitalizedBULLET POINTS2Not a strict requirement but helps improve readability
AmazonNo promotional words in titleTITLE5Use of promotional language is prohibited by Amazon
AmazonNo ending punctuation in bullet pointsBULLET POINTS3Not a strict requirement but helps improve readability
AmazonNo price currencies in titleTITLE3Moderately important to maintain readability and avoid confusion
AmazonWords' first letters capitalized in titleTITLE3Important to maintain readability
AmazonNo words in all caps in titleTITLE3Title may look aggressive and spammy with all caps words
AmazonTitle length below 150 charactersTITLE5Amazon requirement. Product title should be displayed properly on all devices.
AmazonBullet point length below 255 charactersBULLET POINTS5Amazon limits the number of characters per bullet point to 255, including spaces
AmazonNo emojis in titleTITLE4The use of emojis is prohibited by Amazon
AmazonA+ content includedDESCRIPTION5Very important to improve the customer experience
AmazonDescription length between 1800 and 2000 charactersDESCRIPTION3Moderately important to avoid overwhelming customers with a long description
AmazonTitle length between 60 and 100 charactersTITLE4Important for readability

How we compute the Listing Quality Score

The formula used to compute each product’s LQS is based on the weight of its corresponding section and the weight of the rule.

Rules weights are described in the table above.

Sections weights are as follows:

SECTIONLQS WEIGHTLQS WEIGHT EXPLANATION
TITLE5Highly important for searchability
MEDIA4Very important for understanding and visibility
BULLET POINTS3Moderately important for readability and understanding
DESCRIPTION2Slightly important for understanding

In the 'DESCRIPTION' section, we consider both the traditional product description and the 'a+ content'. If all data for this section is missing, the score isn't computed. However, if only some data is missing, we adjust the score accordingly. For all other sections, a missing data point means the score isn't computed.

Each section listing quality score (title, bullet points, media, and description listing quality scores) is computed using the following formula that takes into account the rules relative to the corresponding section:

Once all sub-scores are computed, we compute the global LQS following this formula:

Why are some LQS not filled out?

If one section score is missing because of missing data, then we do not compute the global LQS.

Future Development

Rules and Listing Quality Score are only supported for Amazon for now. Walmart will be supported soon.