Visionet Systems Inc. - VisiAnalytics for Apparel
VisiAnalytics for Apparel is a cloud-hosted BI and Analytics platform that provides insights to critical insights to help business decision makers make the right decisions based on the facts. In addition to the pre-built reports and dashboards, it provides a comprehensive set of dimensions and measures for self-service BI.Contact partner Watch video
- Gold Application Development
- Gold Cloud Platform
- Silver Data Analytics
- Gold Enterprise Resource Planning
Based on Microsoft Cortana Intelligence Suite, VisiAnalytics for Apparel has hundreds of points driving permutations of the critical KPIs and measures that matter most to you, providing scale, speed to market, maximum efficiency and cost savings.
Business Benefits for Apparel
Better Margins – discover hidden connections in your customers buying habits and stock the stores with the right products at the right price.
Better Assortments – Better assortments by identifying the size/color acceptability within different regions and geography.
Better Customer Management – know the churn probability for customers based on their buying patterns using predictive models on Azure Machine Learning. Adopt and sell the right products to your customers.
Daily Sales Flash
•Day level store performance summary
•Key sales KPIs including GM%, ADT, AUR, UPT
•TY vs LY comparison for key KPIs
•Top and bottom stores by sales
•Hourly sales and GM trends
•Drill options for time hierarchy
Color & Size Analysis
•Top Selling Colors and Sizes
•Product Hierarchy Stats
•Size Level Analysis for Sales $, Units, GM$ with drill down to product level
•Color Level Analysis for Sales $, Units, GM$ with drill down to product level
•Selection for Store and Time Hierarchy
Customer Churn Analysis
•Usage of Predictive Model using Azure ML for Customer Churn probability predictions
•Identification of the churn customers for targeted campaigns
•Analysis of the Key KPIs including AUR, ADT and UPT to prepare right campaigns for specific segment of customers
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