Completeness of Product Data as an Indicator of Quality

Completeness of Product Data as an Indicator of Quality

I want to start talking about Content Quality, this is a nebulous term and definitions may vary, but I believe there area number of dimensions of quality and I will describe them individually, starting with completeness, over a coming number articles. 

I must thank Charu Talwar, PHD for her contribution to the article below. 

High quality product information is the key enabler of customer experience in retail space today, especially when the opportunity to physically examine a product is limited if the customer chooses to browse the product digitally before proceeding to buy in store or online. In a recent article 'The new digital Divide " Deloitte research indicates that 76% of shoppers research products through a digital device. 

https://dupress.deloitte.com/dup-us-en/industry/retail-distribution/digital-divide-changing-consumer-behavior.html

One of the key indicators of quality content is its completeness. It refers to the state of data that has all the necessary information that is:

a. Needed by an external search engine to make the item discover-able or indexed. Example brand, style, pack size.
b. Needed by a customer to evaluate a product for purchase. Example: Images, descriptions, key features, benefits, uses, instructions and reviews.
c. Needed by back end systems to make the product transactable on various platforms. Example logistics information, dimensions, tax codes etc.

Completeness of product information helps in presenting an all-inclusive, unified view of the product with the end goal of the customer reaching a purchase decision. 

The larger the number of data points, the easier it is for customers to make an informed purchase decision. This is because attributes drive several aspects of transactability, a few of them listed below:

1. Organic and Paid Site Traffic

Search engine algorithms feed on high quality and relevant product data. Complete and

correct attribution ensures that the product shows up in top search results, thereby driving

traffic to a retail website.

2. Site’s Internal Browsing Experience
Once a customer is at a website, half the job is done! At this point good data makes ensures better browsing experience by making it easier to find and evaluate products to purchase.
3. Complete product data helps accurate category refinement so the customer can
easily navigate and find products they are interested in. If some of the data is omitted
during the setup process, it’s likely that particular item may not show up on the page
when customers are shopping. For instance, if “32 GB” is not filled out as a Product
Attribute, then that iPad will not come up in a search. The end result could mean a
loss in sales because customers may not know that camera was an option.
4. It determines what gets loaded in the specification tables and comparison charts on an Item web page for better differentiation and understanding of products.

Completeness of data in terms of product spec attribution and other elements of content help empowering customers by satisfying their ever increasing need for information and avoiding frustration. Frustration that leads to shopping cart abandonment. 

However, given the cost and complexity of data aggregation, aiming for 100% completeness at the time of  initial item set up may affect speed of getting products listed, not all information may be available. Brand owners need to understand that syndication and curation of content is not a one time activity,  but an incremental, iterative process of 
improvement.