4 Steps to Prevent eCommerce Choice Overload

Are too many choices making eCommerce difficult for consumers? Recently I listened to a TED Talk by Dr. Sheena Iyengar, Professor at Columbia University and author of “The Art of Choosing.” eCommerce managers who often pride themselves in how much content they provide their customers should take her observations into consideration.

Benefits of Master Data Management

Managing the catalog for an eCommerce site is hard enough, but when you have a database―which receives data from multiple sources—it is easy to have duplicates without even knowing it. This makes things hard to find and is very confusing for customers. The best way to solve this issue is to move to a Master Data Management philosophy. By standardizing the item names and consolidating the item descriptions, you create a catalog that is more understandable and easier to search. Here are some of the benefits of creating a database using Master Data Management.

Reduces errors
Increases reporting accuracy
Improves data usability
Simplifies design by standardizing data validation
Provides trustworthy data
Eliminates data inconsistency and improves accuracy and consistency
Improves data sharing
Enables consistent interactions between systems
Increases the quality and reliability of data
Provides clean data for the system
Establishes an authoritative source of information

The benefits of Master Data Management focus on either improved data quality or improvements in data governance. The major outcome of implementing a Master Data Management system is providing a unified view of all catalog items and streamlining the provision of high quality, consistent, and synchronized data. These good data management practices lead to operational efficiency improvements as well as enhanced search engine performance, reliable reporting, and an overall reduced item count.

The primary benefit of a Master Data Management system is establishing good data management practices, which improve operational efficiency. It is definitely something to think about if you are managing a large database that receives data from multiple sources.

Personal Hygiene and Data Quality

I read a blog post in LinkedIn recently comparing data quality to personal hygiene. The article stated that “If we are ill, then being clean and hygienic will not on its own make us better. We need medicine to do that. But being hygienic to start with may have prevented us from getting ill in the first place. And being hygienic will speed up the recovery process by preventing re-infection. Being hygienic keeps us fit and in tip-top condition.”

I want to take this analogy a step further. The company I work for, Partnet, is an expert in electronic marketplaces. In this environment, data quality is essential. Like personal hygiene, data quality represents your value and integrity as well as your health. It gives your customers a first impression. They make immediate judgments as to whether they want to do business with you based on the way your application and your data looks to them. How many people would go to a job interview with crumpled, stained clothing and disheveled hair. What kind of first impression would that give? Would you expect to get the job? Having poor data quality can give the same bad first impression.

With an eCommerce site, the customer has to have confidence in your ability to keep their financial information safe. Why should a customer trust a marketplace that does not offer accurate product descriptions, properly spelled words and good product images? If you can’t make sure your item descriptions are spelled correctly, why would they think you could keep their credit card information safe.

It is a poor reflection on both the individual vendor and the marketplace. It may cost money to get the haircut before the interview and to have […]

Why Should We Care About Data Standardization?

In my last blog, I talked about how Electronic Commerce Code Management Association (ECCMA) created an Open Technical dictionary based on the federal catalog system. This technical ontology can be used to describe items that you make, or that you buy. The question now becomes—why do should we care.  What do I get out of data standardization?

Apparently the answer is—a lot.

Data standardization has been shown to:

Increase sales in online catalogs by preventing returns because inadequate description make searching for items difficult.
Lower the overall cost of customer service by reducing customer complaints and questions.
Prevent incorrect forecasts and even packaging and transportation costs. You have to know the accurate size and weight of an item to know how to ship it properly.
Greatly enhance spend analysis and support financial reporting requirements.
Reduction in speed to market for new items.

The Data Warehouse Institute states “Poor data quality is costing US businesses more than $600 billion annually.”

A variety of issues such as legacy systems, poor accountability, measurement inconsistencies, and human error can cause poor data management. Companies need to develop data management plans that establish data strategies for data governance based on completeness, consistency, conformity and duplication. These plans will identify and correct potential risk areas.

Often it is hard to convince upper management that data standardization should be a priority within a company. By matching the data quality plan to the business metrics and strategic goals of your company or industry, you can gain support to carry out this important internal business function.

If you would like to know more about the ECCMA eOTD and how it can help you with data standardization, check them out at www.eccma.org.

Government and Industry Work Together to Support Data Standardization

In 1999, the Electronic Commerce Code Management Association (ECCMA) was founded as an international not for profit membership association with a mission to research, develop and promote better quality data for use in electronic commerce.

Soon after formation, ECCMA director Peter Benson discovered that the Department of Defense had been doing data standardization work to support military acquisition since the early 1960s. The government system, called the Federal Cataloging System (FCS), described items purchased by the federal government using Federal Identification Information Guides (FIIGs). These guides classified and described over 17 million items used by the US, NATO, and a series of friendly foreign governments. The Defense Logistics Agency Logistics Information Service in Battle Creek, MI manages the database and cataloging process. Benson convinced the government to collaborate with private industry to develop an international standard based on the work already started by the federal government.

ECCMA went on to develop the ECCMA Open Technical Dictionary (eOTD) to allow the creation and exchange of unambiguous, language independent master data. Data that identifies and describes individuals, organizations, locations, goods, services, processes, rules and regulations. The eOTD is based on the Federal Cataloging System and the NATO Codification System, the systems used to manage the world’s largest shared inventory developed by the Department of Defense and members of NATO and used today in over 50 countries.

Today ECCMA is the project leader for ISO 22745 (Open technical dictionaries and their application to master data) and ISO 8000 (Data quality). ECCMA is also the American National Standards Institute (ANSI) accredited administrator of the US technical advisory group, the committee responsible for the development and maintenance of international standards for industrial data.

This decade old partnership proves that government and industry can […]

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