Brands Brent Kepler By Brent Kepler

The Ones & Zeros of E-Commerce, Part I: Data in Context

Data is a foundational concept in commerce. It is arguably the most critical topic related to success. This blog series covers the different types of data that exist, the importance of data quality and ways data is prepared and transferred in e-commerce today — so you can make appropriate plans or changes to your relationship with data to build a greater chance of success.

Search for the word “data” in Google, and it will return over 14 billion results. If we told you that understanding data is critical to your success as a business owner, and threw you to Google alone to figure it out, you would probably get anxiety. 

To better understand key types of data that are involved in buying and selling products, today’s blog post will be of interest to you and should begin to ease your conscience. We’ll focus on the basic definitions of data that are available, and the workflow transfer of data between you (the merchant), ChannelAdvisor, and the channels on which you sell.

Data

The term “data” is heavily used in everyday life — it’s often referred to interchangeably for one (or a combination) of three things:

  1. Raw form “data” — such as a price, temperature, name, address, UPC
  2. Information — such as “data” about the history of my company, what occurred when
  3. Knowledge — such as “data” I hold about how to properly execute a particular process or task

Just for reference, the phrase “Big Data” is also thrown around frequently, maybe a little too much in recent years, but it refers to the practice of analyzing data sets that are too large, too complex to review and analyze in typical software platforms. Have you ever had a data set so big, Excel failed to open it? How about a data set so big, it took six hours to process a relatively basic query? If so, you are swimming in the realm of “Big Data”. Though it is something practiced by ChannelAdvisor on a daily basis, we do not intend to focus on that today.

Data Communication

Data needs to be moved from one place to another — in the context of ChannelAdvisor, here is a somewhat simplified version of the workflow related to data transfer:

  1. Seller (or Agent of the Seller) prepares data and sends/makes available to ChannelAdvisor
  2. ChannelAdvisor transforms data to meet channel requirements and sends data to channels
  3. Channels provide data back (raw and informational data), including listing status, orders, and statistics on clicks/impressions/etc.
  4. Seller retrieves this data and:
    1. Takes action to ship items to buyers
    2. Utilizes information resulting from the data to take some action to enhance their business
  5. Seller notifies ChannelAdvisor about shipments or makes adjustments to advertising spending
    1. ChannelAdvisor communicates these changes in information back to the channels

This overall process repeats with new products, or runs through revisions on existing products between steps 2-5.

These transfers of data are all considered data integrations. A lot of work typically goes into them, but they are critical to ensure data is communicated properly, and in a timely fashion. We will cover methodologies of data integration in a later blog post, but it is good to understand them in close context to our transfer workflow. Speaking of which, there is a little-observed concept behind data transfer worth noting here: communication frequencies.

Communication Frequency

ChannelAdvisor integrates with hundreds of channels through multiple different integration methods. All systems have limitations — usually a result of available resources, technology, and sometimes a result of design and planning. ChannelAdvisor, much like a seller or any other integrator, must observe the communication frequency limitations to ensure we aren’t violating agreements or crashing channel systems. Given the amount of data we transfer to these channels, that is a potential reality if we did not pay attention to the defined lane markers. 

Even the biggest players in marketplaces and digital marketing (e.g., Amazon and Google) have limitations for a reason. Changes triggered minute one usually are not transferred minute two. While ChannelAdvisor can quickly and efficiently execute within our own platform, the delays you may see between the time you give us a change and the time it is reflected in an ad or listing are often a result of these communication frequency limitations.

In part two of this data series, we’ll discuss the importance of data quality and the two primary types of data in e-commerce.