How to Derive Meaning from Product Data - Indix



How to Derive Meaning from Product Data

We are living in the era of pervasive commerce – where every interaction with a consumer in the physical world or online, is an opportunity to inform, educate, and sell products and services. As consumer expectations rise with respect to relevancy, personalization, and targeting, there is a telling need for standardized and normalized product information. At Indix, we are solving this problem by building an infinite product catalog in the cloud. In the coming months, we will publish posts exploring different aspects of this catalog. Today, we will elaborate on the aspect of product attributes and what role they play in the infinite catalog.

Infinite Product Catalog

Infinite Product Catalog

When we think of a catalog, we think of a document that consolidates detailed information about a particular product. At Indix, we are trying to do this for every product in the world. Product data has two basic elements – the dynamic and the static. Dynamic data includes all aspects that are subject to change, i.e. price, promotion, availability, inventory, etc. The static or non-changing data is what we call attribute data. For a single unique product, the attribute data doesn’t change. Attributes include factors like color, material, where the product was designed, where the product was manufactured, size, brand, etc. There are also category-specific attributes. For instance, in case of women’s shoes, there are specific attributes like heel height, insole material, width etc. Or for televisions, there are attributes like screen size, resolution, screen material, and so on.

Attributes are very important for companies when trying to compare products with each other. Consider how helpful consumers find the comparison feature that a lot of e-commerce websites have these days. Say a consumer is on the Lenovo website. S/he can easily compare two or more laptops. In a few clicks, consumers are presented with a comparative view of their selected products across various attributes like operating system, RAM, resolution, hard disk capacity, etc.

Right now, brands have attribute data in a standardized form for their own products. But what happens when they want to compare similar products that are offered by different brands? Wouldn’t it be helpful if they could access that data in just a few clicks? This sort of competitive intelligence is one functionality that the infinite product catalog allows for.

When brands have access to product offers and attribute information for not just their own products but also their competitors’ products, they can plan better and ensure that they are generating the most relevant product offerings. Without an organized and standardized database of products and their attributes to work with, this is a very time consuming and tedious task.

At Indix, we extract tens of thousands of attributes for products and normalize them. Each attribute is verified against the Indix dictionary of standard attributes. So even if different websites use different units to express product attributes, we standardize all the product-related information and attributes through our patented algorithms.

Extracting deeper attributes provides more meaning to a product, making it richer and more usable. The more attributes there are, the more helpful it is for businesses to make sense of the data and design more relevant and personalized offers. The ultimate winner in this process is the end user who gets the best possible product offering. We are here to serve that business goal. Win-win!

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