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Retail Data Sales Analytics
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nisrina
Posted: Tuesday, February 06, 2018 11:22:58 PM
Rank: Advanced Member
Groups: Member

Joined: 6/9/2016
Posts: 35
Location: Indonesia
Sales Analytics - Analytics plays an important role in data flow schemes within retail organizations. Typical retailers generate more than thousands of data points via a POS machine. It is difficult for retailers to make strategic decisions based on this raw data. Typical retailers have large amounts of sales data stored on their systems. This new technology has the ability to use this historical data to improve retail productivity. To create sustainable benefits from competition, retailers are trying to improve their product offerings, service levels, and pricing models.
Businesses sales analytics help gain insights from structured data, such as sales and productivity reporting, forecasting, inventory management, market basket analysis, product affinity, customer clustering, customer segmentation, identification trends, seasonal identification and hidden patterning for loss prevention and store administration.
Analytical techniques such as statistical analysis, data analysis, and analysis tools help in understanding patterns and trends in large databases. When we use them to create analytical models, they give the edge to decision-making. While descriptive analysis helps identify problems and examines their causes, predictive sales analytics increases the accuracy and effectiveness of the decision-making process. Some of the analyzes that apply to retailers are: Predictive analysis helps retail organizations to increase their decision-making power by looking at the future with analytical rigor.
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