The digital world has changed drastically over the past few decades, and eCommerce has become a major player in retail. As eCommerce continues to grow, so does the data associated with products and services.
As this data gets larger, it becomes increasingly important for businesses to understand and effectively manage their product data.
In this blog, we’ll discuss the concept of eCommerce product data modeling and what you need to know to make the most of your business’s product data.
What is Product Data
In eCommerce, product data is all the information about a product that you can read, manage, measure, and organize. This includes things like product descriptions, pricing, and sales performance.
There is no one set way to collect and organize all the information about a product, but there are tools that can help. A data warehousing company, for example, can help extract and organize product data so that it can be used to improve a business’s online sales.
In the eCommerce industry, companies use product data to gain insights into customer behavior and improve the online shopping experience. They also use it to understand how their business performs compared to their competitors.
What is Product Data Modelling
Product data modeling is the process of defining and organizing information about a product. This includes things like product descriptions, pricing, and sales performance. When you create a product data model, you are defining the data and its attributes, as well as how it relates to other data.
Data modeling is an ongoing exercise that helps businesses understand and improve their data system needs.
For example, in eCommerce, a product data model might detail the information that can be collected about a product and how that information should be analyzed to optimize the online sales process.
Data modeling techniques also define what kind of operations can be performed with the data and how the data infrastructure should be manipulated.
Components of eCommerce Product Data Modeling
The eCommerce product data modeling includes four main components with their own endpoints: charges, customers, refunds, and orders. Each of these elements, as well as their connections, are detailed in the following sections.
A charge is the main action taken. When your application needs to process a payment, it uses a charge to complete the transaction. The payment is taken from a source, like a credit or debit card that the hosted tokenizer has tokenized.
A charge is connected to other information in the following ways:
- It is linked to a specific customer.
- It is linked to a specific order.
- It can be refunded partially or completely.
Customers use your application to pay for goods or services you offer. Each customer has a unique account identified by their id.
Information about the customer includes their name, address, email, and information about how they want to pay and where they want the products shipped.
Cards on file are encrypted pieces of information saved as payment sources for a customer’s account.
A customer is connected to other information in the following ways:
- They can have one or multiple orders.
- Their account can be charged zero or more times.
Refunds store information about when customers receive a partial or full repayment of a charge. The amount field determines the amount of money be refunded. Reasons for refunds can include duplicate, fraudulent, or “requested by the customer.”
Refunds have the following connections to other information:
A refund is related to a single charge.
A refund is linked to a single order.
A consumer may receive zero or several refunds for an order.
Orders save information about the purchased things, the price the merchant charges the buyer, and when the order is placed.
Given that the consumer is most likely completing the purchase online, the order also includes shipping information, which may differ from the customer’s billing or shipping addresses.
The following approaches tie order to other data:
- A customer may place one order or more.
- A single fee can be applied to an order.
- A single consumer places an order.
Why eCommerce Product Data Modeling is Necessary
eCommerce product data modeling is necessary to keep track of the products that companies sell online. It helps businesses understand their data and decide how to market their products best.
Data modeling helps businesses organize their product information in a way that makes sense and is easy to read. This way, businesses can identify the best products to promote, create more effective marketing campaigns, and optimize their eCommerce stores for better customer experience.
A data warehousing company can help businesses build robust data models tailored to their specific needs.
It’s worth considering partnering with a data warehousing company that can help you design and implement a comprehensive data modeling solution.
eCommerce product data modeling is essential for any business that wants to succeed in today’s digital world. With the right data modeling, businesses can increase efficiency, maximize profits, and provide customers with an enjoyable shopping experience.