Data Quality Management

Enhance the Quality of Your Product Data
As soon as false product data has been distributed to your sales channels, the damage has already been done. According to studies, corrections this late into the content process are the most resource-heavy and costly. Even worse: Your customers are irritated by false or missing information and, worst case, even choose not to make a purchasing decision so that you miss out on sales. In order to prevent this scenario from happening, you can use eggheads Suite to formulate your Data Governance Strategy on the basis of extensive quality and validation rules — and combine processes with defined Quality Gates.
 


 
Your benefits:

High data quality

Context-sensitive data quality

Workflow control through data quality

Quick quality reports via scoring

 

Data Quality and Validation Rules

In eggheads Suite, you define data quality and validation rules either globally or individually for specific assortments. This does not only encompass checking the completeness of each product attribute, but also covers aspects such as text length and minimum resolution of media, or the comparison of different product attributes on the basis of more complex rules.
 
 

Error Classes and Significance

Not all data quality rules have the same relevance. While missing prices in your online shop is an absolute no-go, a short product description text may not be pretty yet still tolerable for the sake of a better time-to-market. This is why you can assign different consequences and significance levels. Simultaneously, this provides you with a priority list for correcting identified errors, allowing you to focus on the most pressing issues first.
 
 

Context-Dependent Quality

Often times, there is no universally-applicable definition for quality standards available which fits all of your product data records. Even though a product may have sufficient information for web presentations, images, or logos etc., it may still not have a high enough resolution for print catalogs. Or it may be the other way around, as SEO attributes are not relevant for catalogs, while they are indispensable for online platforms. In eggheads Suite, you can optionally assign a context such as “Print” or “Web” to each quality rule, allowing you to always have the relevant quality scores and take corresponding measures for each channel, use case, and process step etc.
 
 

Data Quality Score

To have a quick overview of your product’s data quality, a score is calculated based on the result of the analysis of individual quality rules. This way, you immediately identify how good each of your products is described and where there is room for improvement. Of course, you can simply use the search function to display all products which are below or above the specified data quality score. All in all, you are provided with a healthy foundation for the improvement of your data quality.
 
 

Quality-Dependent Workflow Control

Providing you with an overview of the data quality of your products, however, is only one goal of our data quality management. Another, no less important goal is to define Quality Gates and control the workflow for products accordingly. For example, you may regulate the export of products with insufficient quality, or automatically generate and delegate tasks to cleanup relevant quality errors. This guarantees that your products’ data quality is enhanced, and that no false or incomplete information is distributed to customers.
 
 
 
You have any questions?
Write us
Ich erkläre mich damit einverstanden, dass meine Angaben gespeichert & zur Beantwortung meiner An­frage verwendet werden dürfen. Datenschutzerklärung*
SELECT YOUR LANGUAGE