Bright Data | Retail Data - Global Coverage - Pricing Data, Seller Ratings Data, Customer Reviews Data
X-Byte | Retail Pricing Data Global & ecommerce API's from our Enterprise Crawling
MBI Geodata - Retail Centrality Index Worldwide
aKQired Ecommerce Database - Shopify Stores, Retail Database [Owners, Emails, Phone]
Retail data worldwide & ecommerce APIs from Datahut
Automaton AI Video Data - video of products in a retail store
List of 38M Retail companies worldwide
90 West Data - US Consumer Credit Card / Debit Card / Transaction Data - Retail Panel
BDEX Retail Foot Traffic Data⎢USA⎢Any Major Retail Chain
Edge by Ascential ⎢Retail Insight - 2.5K+ Retailers over North America, Australia, China, India, EU-5
The Ultimate Guide to Retail Data 2021
What is Retail Data?
In the day-to-day running of a retail business, owners of such businesses are faced with the need to make decisions to drive growth through enhanced sales. In the contemporary business environment, driving growth is not effective if retail data analytics is not used as a fuel to propel growth. Consequently, owners of retail stores can take advantage of retail data analytics to paint a clear picture of their business’ health in terms of sales while making improvements and reinforcement for customer satisfaction.
How is Retail Data collected?
Technological advancement has brought along a new wave of possibilities including a collection of retail information. Modern retail stores go the extra mile to develop customized apps for mobile phones and PCs. While these apps are important in enhancing customer experience, retailers also use them to monitor customer shopping habits and interests. This method of in-store customer data collection helps retailers to tailor services to each customer. Retailers can also collect retail data by the use of guest satisfaction surveys, as a result of helping the business point out the key trends in buying behavior and formulating initiatives to drive more sales. By tracking website activities, retailers can also gather retail data about the number of potential buyers that have shown interest in the business.
What are the key attributes of Retail Data?
The attributes of retail data are grounded on two factors: customer insights, and business insights. Retail data’s attribute of customer insight involves a information on customer behavior. Understanding customer behavior is crucial for retailers to improve customer satisfaction and as result bolster sales. On the other hand, business insight is data that pertains to the business’ supply chain and inventory tracking that can help retailers make procurement decisions to ensure a steady supply of goods. Taking command of the supply chain through retail analytics helps the business to be highly reliable because customers are sure to get what they need at the right time and place.
What is Retail Data used for?
The benefits of retail data are twofold, helping retailers to optimize their supply chain and identify customer trends and preferences. As far as optimizing the supply chain is concerned, retailers can use retail data to revamp their inventory and procurement systems. This undertaking can be achieved by the use of predictive tools in which the business makes use of historical data and trend evaluation to define the order in which to bring in new products and the precise quantities of products needed. This inventory optimization is ensuring that customers get the products they need while reducing space usage in stores. Identifying customer trends and preferences is another important use of retail data analytics. Retailers can easily match up sales data to predict consumer behavior hence creating cross-functional marketing strategies that target just the right consumers.
How is Big Data changing retail marketing analytics?
Companies such as Amazon, Wal-Mart, eBay and Costco are prime examples of how modern retailers have successfully harnessed the real power of big data analytics across processes in the businesses. The companies, which are largely retail stores that are based online, have amplified the power of big data analytics by making retail data useable throughout company departments, hence leading to wide-spread optimization of core business goals and smaller routine daily tasks. Here’s some examples of how using big data in retail adds value to business operations:
• Pipeline development for store location
• Pricing optimization
• Personal data protection
• Customer service
• Inventory management
• Promotion intelligence
• Fraud protection and prevention.
What is the definition of Retail Data analytics?
Retail data analytics refers to the process of analysing information related to retail businesses to establish insights including sales data, inventory data, customer data and other critical pieces of information that play a role in the decision-making initiatives of business owners and merchants. Ascertaining a retail business’ operations and overall health is only possible with the right data. Retail data analytics draws on various data points as evidence, allow the user to paint a picture of the overall business health of a given retailer. In turn, strong retail analytics foster better choices by retail business managers, from operating the business efficiently, to delivering customer-centric service.
How to analyze Retail Sales Data?
Retail business look to acquire retail sales data to improve their own sales. There are numerous retail sales data vendors on online data marketplaces where retail business managers can buy retail sales data and use it for their own analysis. The general process of analyzing retails sales data involves the following core steps:
• Identifying the specific use case for the data.
• Selecting a sales analysis tool to help in the process of analyzing the data.
• Drawing results and sharing the data with the necessary stakeholders to help make inferences from the data and put it to use.
What is a Retail Data model?
A retail data model gathers logical information covering the entire retail industry. Such a data model is usually made up of enterprises, business area, and manufacturers. Retail data models allow businesses to understand the retail ecosystem, which helps them optimize their marketing and selling strategies through retail outlets. Retail data models account for wide-ranging business data on reports and analytic needs concerning the key areas of customer needs, products pricing, marketing initiatives, financial reporting and analysis, inventory management and overall business metrics and analytics.
What is a Retail Data collector?
A data retail data collector gathers price points for many categories of merchandise, to then be compiled in a commerical dataset by a data vendor. Data vendors then provide the collected data on data marketplaces where retailers can shop for the right retail data and use it to enhance their business.
How does Nielsen collect Retail Data?
As a leader in retail measurement services, Nielson’s purchasing data provides detailed and timely data on market shares, competitive sales volumes and overview of distribution, pricing and merchandise promotion. Nielson has a business presence in more than 100 countries and amasses data from close to 900,000 stores in its global retail network who willingly share their data. The process of collection of this information involves point of sale data that is collected through store’s checkout scanners. In the event that this POS data is not available, Nielson uses field auditors who amass sales data via in-store inventory and price checks. Before the data is made available in its propriety software, Nielsen ensures that it undergoes stringent quality control checks through an established quality control system. As such, retailers can use Nielson’s retail sales data subscription services to enrich their business’ sales information and discover intuitive ways to improve the overall performance of their business.
How can a user assess the quality of Retail Data?
Users can assess the quality of retail data by its ability to accurately depict the current trends in market behavior both, for the customers and the business. Quality data is tailored to a specific business in terms of needs and trends. It is up-to-date and it accurately provides trends as far as the retailers’ line of business is concerned. Quality retail data also takes into account the aspect of consumer private data protection. When collecting retail data, the data provider must abide by data privacy regulations to ensure consumers’ PII isn’t compromised.
What are Retail Data statistics for 2021?
The retail reports that are now available on data marketplaces can be used by retail business managers and owners to get to grips with developments that are emerging the in the retail business world. A detailed analysis of retail data reveals how the retail market is experiencing shifts in economies all over the world. For instance, retail data reports show that total global retail sales are expected to reach new heights of $27.73 trillion by 2021. Furthermore, as China is expected to remain the largest ecommerce market in the world, 95% of all retail purchases are projected to be done through ecommerce platforms.
Who are the best Retail Data providers?
Finding the right Retail Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Retail Data providers that you might want to buy Retail Data from are Bright Data (Formerly Luminati Networks), X-Byte, MBI Geodata, Datahut, and Automaton AI.
Where can I buy Retail Data?
Data providers and vendors listed on Datarade sell Retail Data products and samples. Popular Retail Data products and datasets available on our platform are Bright Data | Retail Data - Global Coverage - Pricing Data, Seller Ratings Data, Customer Reviews Data by Bright Data (Formerly Luminati Networks), X-Byte | Retail Pricing Data Global & ecommerce API’s from our Enterprise Crawling by X-Byte, and MBI Geodata - Retail Centrality Index Worldwide by MBI Geodata.
How can I get Retail Data?
You can get Retail Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Retail 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 Retail Data APIs, feeds and streams to download the most up-to-date intelligence.