DataWeave: Digital Shelf Analytics - Ecommerce Store Data
Edge by Ascential ⎢ Ecommerce Product Performance by Channel - Digital Shelf Data for Asia, Europe &
Dexi | Automated Web Data Capture | Digital Shelf for eCommerce Brands and Retailers | Channel Compliance
Dexi | Automated Digital Data Capture and Web Automation | Data Mining | SaaS | DaaS
Dexi | Automated Web Data Capture | Competitor Monitoring
The Ultimate Guide to Digital Shelf Data 2021
What is Digital Shelf Data?
Digitial shelf data is information about an ecommerce website’s product or service offering. In the contemporary business environment, ecommerce has carved a niche to become the center stage of consumer transactions globally thanks to ever-evolving technology. As ecommerce continues to gain traction in the business world, one of the key drivers that has kept ecommerce platforms alive is the ability for consumers to access goods and services with a simple click of the button.
The shopping journey for any digital shopper usually goes like this: consumers today discover, research, and shop for products with the aid of digital experiences that help them establish their own personalized, digitally-influenced path. These digitally-influenced paths are what make up a digital shelf for a business. As such, commerce today is driven by a single unit of interconnected digital shelves. Therefore, digital shelf data defines how and where a brand’s product is exhibited online, whether on a product description page on a retailer’s website, the third-party marketplace, mobile app, personal website, or any other e-commerce channel.
How is Digital Shelf Data collected?
The major source of digital shelf data is from search engines. As technology continues to drive business growth, many people now prefer to search for information about a product online. Therefore, for the majority of retailers, the principal digital shelf is the search results page of a search engine or website. It is at this point that most of the consumers look for items to purchase after inputting their direct inquiries into a search bar or filtering product choices based on their specific needs.
What are the attributes of Digital Shelf Data?
Digital shelf data is made up of what analysts call the 4Ps. The 4Ps include product, placement, price, and promotions.
• Product is the main item of the digital shelf that is listed by a seller to a potential buyer.
• Placement refers to strategies through which the product is listed on the digital shelf. This may infer to the positioning of the item on SERPs and websites so that it’s readily seen by a potential buyer.
• Price is the amount of money that the potential buyer is expected to pay for the product listed on the digital shelf.
• Promotions refer to any form of strategy that is undertaken by the business to help enhance the sale of listed products on the digital shelf. Promotions may be in the form of discount, or after-sale service referral services.
When combined, all these attributes are what make up a digital shelf. For marketing and sales promotion, ecommerce websites are intuitively designed to appeal to potential consumers. Furthermore, some of the content attributes that are needed for the digital shelf data comprise product variation options, images, videos, descriptions, instructions, pricing, and ratings and reviews as provided by clients at the point of sale.
# What is Digital Shelf Data used for?
Digital shelf data is particularly important to ecommerce business owners who use it to optimize their platforms in the following ways:
• Keeping track of out-of-stock issues on priority items listed on the digital shelf.
• Having a constant view of competitive launches to point out new ways to enhance the business’s digital shelf by keeping track of trends and opportunities.
• Using digital shelf data, businesses are also able to engage buyers in a multiplatform system.
• Digital shelf data can also help businesses to execute commerce strategies by learning fast, scaling what works and what does not work as far as assembling their digital shelf.
How can a user assess the quality of Digital Shelf Data?
For brands to gain any meaningful insight from digital shelf data, they ought to take into consideration how this data will influence their key performance indicators (KPIs). The core focus areas of quality for this dataset include:
• Content - the amount of content per product. The data should not leave room for any empty fields.
• Availability - the data should tell a user about the percentage of in-stock products as compared to listed products.
• The validity of data - the data should be verified and come from reliable ecommerce sources and digital shelf data providers.
Who are the best Digital Shelf Data providers?
Finding the right Digital Shelf Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Digital Shelf Data providers that you might want to buy Digital Shelf Data from are Edge by Ascential, DataWeave, Dexi.io, and Wake Commerce.
Where can I buy Digital Shelf Data?
Data providers and vendors listed on Datarade sell Digital Shelf Data products and samples. Popular Digital Shelf Data products and datasets available on our platform are DataWeave: Digital Shelf Analytics - Ecommerce Store Data by DataWeave, Edge by Ascential ⎢ Ecommerce Product Performance by Channel - Digital Shelf Data for Asia, Europe & North America by Edge by Ascential, and Dexi | Automated Web Data Capture | Digital Shelf for eCommerce Brands and Retailers | Channel Compliance by Dexi.io.
How can I get Digital Shelf Data?
You can get Digital Shelf Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Digital Shelf Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Digital Shelf Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Digital Shelf Data?
Digital Shelf Data is similar to Online Shopping Data, Ecommerce Product Data, Ecommerce Sales Data, Ecommerce Customer Data, and Ecommerce Store Data. These data categories are commonly used for purchase behavior analytics and Ecommerce Analysis.