Data Categorization for Online Stores – How to Guide
July 25, 2022
If you want to know how to categorize data for an online store, why not read this guide. We’ll tell you everything from the different types of data available on your website and what they are used for to how you can use them effectively.
Definition of data categorization process in general
Data categorization is the process of identifying the different types of data that an organization creates and classifying it into appropriate levels. Data categorization can be automated or done manually. There are usually multiple classification levels required for a data categorization project.
The goal of data categorization is to organize and manage data so that it can be used more effectively. In order to do this, categories and classification criteria are defined, and the automated classification process is initiated. The outcomes and usage of classified data are then documented.
Data categorization for online stores
Data categorization for online stores is the process of organizing data in a way that makes sense for your business. The data categorization process involves analyzing and categorizing data based on predetermined parameters. The data categorization process involves assigning products to their proper categories. By categorizing your data, you can improve your customer experience and make it easier to find the information you need. The data classification process is performed based on brand guidelines and industry standards. The data categorization process should be automated to speed up the process.
There are three main methods of data categorization:
There are many different primary categories that you can use to categorize your store products depending on your offer like: Clothing, Accessories, Furnitures, Grocery, Electronics, …
Or go even deeper: Clothing / Shoes / Shoes for women / High heels
Customer Information categories
Customer information categories are the different types of data that a customer provides when creating an account. These categories can help you segment your audience based on their interests, hobbies, and preferences so that you can better target your marketing.
Order history categories. Order history categories are a feature that lets you see the products people have ordered previous to this, so they can be more inclined to purchase these items again. It allows your users to go back and see what products they’ve ordered before, so that you know how profitable these items were.
For example, you might have categories for products, customer information, order history, and payment methods. Or you might have categories for managing customers, processing orders, and tracking inventory levels. Or you might have categories for online sales data and offline sales data.
However, most businesses will benefit from using more than one method of categorization. For example, you might use product categories to organize your online store data and customer information categories to organize your offline store data.
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Why should you consider data categorization in the online store
There are three main purposes for categorizing data: to help shoppers make decisions, to easily sort products and categories, and to group similar products.
The first step in setting up a store with categories is deciding how many and which categories there will be.
Creating product categories can help you to get a better understanding of how someone shops based on context, and what is most relevant for that person. Categorizing products by function is less common than category-specific categories like Outdoor or Cooking & Kitchen Supplies. For brands, it’s harder to maintain product categorization based on purely taxonomic relationships.
Also consider the use of categories to make navigation easier. Data categorization is important for usability because it allows you to quickly find relevant information about your content and website. It also helps the user easily navigate through the site in order to find what they are looking for.
Consider the psychology behind merchandising as well, with an emphasis on design and mind set.
Data categorization is also important for SEO because it helps your website be found by the right people. On a site that offers information about many different topics, data categorization allows users to find what they are looking for more quickly.
Definition – Product Taxonomy
Product taxonomy is the way in which your product is classified based on its attributes and how they relate to each other. Examples of product taxonomies include clothing, food, healthcare, education, and more.
Retail product classification
Product data classification is the process of grouping products based on the hierarchical strategy of the retailer.
Product families are the collection of attributes that will be the same for all products related to that family.
Brands are products manufactured by a company under a specific name. Important for product types where shoppers are likely to search by preferred brand.
Categories are product categories groups like products together. You can assign several categories to a product. You can also go into the second level of sub-categories.
Parent product is the product may come in different colors, sizes, materials – but the basic elements of the parent product remain constant. The product detail page is generally at the parent product level.
Attributes are details about the product that will help describe it and give shoppers information they need to make purchase decisions, such as size, color, price, description, warranty information, etc.
Options are some attributes which may be available in different options – such as attribute color having several options of blue, green, red purple etc., these options need to be displayed in an easy way to select on a product detail page.
When categorizing data for an online store, the first step is to gather all data sources. This includes all catalogs, spreadsheets, product or data feeds, files, and so on. Once you have all of your data sources in one place, you will need to check with all departments for any siloed data. Siloed data is any information that is not readily available or accessible. Once you have gathered all of your data, you will need to prepare all data sources to send that information to one centralized location. If you have an ERP system, this may be a simpler process.
Data quality is important to ensure that your product data is accurate and relevant to your customers. Data quality is ensured through the use of human-powered processes, such as manual data entry and validation, as well as machine learning processes, such as predictive modeling.
Correct classification of your products into intuitive categories can help increase your eCommerce sales. Categorizing data can be a complex task, but there are a few tips that can help make the process easier. First, consider the structure of your data and how it can be organized into categories. Second, think about how you want your customers to search for and find products on your site. Finally, create clear and concise category names that will be easy for customers to understand.
The data model for an online store is a multi-task, multi-class classification problem. The data model is framed as a multi-class classification problem to incorporate learnings from previous attempts at solving the problem. The data model has seven output layers corresponding to the seven levels of the taxonomy. Each layer has its own loss function associated with it.
During the forward pass of the model, parent nodes influence the outputs of child nodes. During backpropagation, the losses of all seven output layers are combined in a weighted fashion to arrive at a single loss value that’s used to calculate the gradients.
Data categorization challenges
Online stores often have difficulty in categorizing data so items can be found quickly and presented accurately to customers. It is important that you consider the way your online store will work before creating a structure for your metadata.
Considering how your future store will work is important, so you can create your structure to work with the way your store will be. This can result in less problems for your organization
Here are some of the most common problems of data categorization:
Local differences in categorization can confuse customers.
Different terminology can lead to problems with creating a structured data hierarchy.
Ambiguous and complex data can make it difficult to find the same product under different categories.
Duplicate categories can be a challenge to manage.
An excess of categories can be confusing and discouraging to buyers.
Having doubts between a category and an attribute can be difficult to decide.
Conclusion on data categorization
As you can see, categorizing data for an online store is not as difficult as it may seem. By following the tips and guidelines in this article, you can easily categorize data and build an online store that is organized and easy to navigate.
Special Thanks to
Rongmei Zhang as co-author for outline creation and design
FAQs on Data Categorization
What are common E-commerce data categorizations?
There are a few different types of data that are commonly used in eCommerce:
Product Data: This is information about the products or services being sold. It can include things like descriptions, pricing, and images.
Customer Data: This is information about the people who are buying products or services from the eCommerce site. It can include contact information, purchase
How do you categorize products in online stores?
There are a few ways to categorize products on online shops. The most common is by using tags, which are keywords that describe the product. Other ways include using categories (such as men's clothing or women's shoes) or by using filters (such as size, color, or price).
How many categories should an online store have?
The number of categories an online store should have depends on the amount and type of products being sold. Generally, it is best to keep the number of categories to a minimum so as not to overwhelm shoppers.
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