Column Description
store_code Store code of store/POS
channel Channel
store Store name of store/POS
store_class Store grade or store class of the store/POS
city City which the store belongs to
region Region which the store belongs to
is_new_store New stores which were not live in OD period are marked 1
period Input Period for which the data is shown
attribute_group Attribute groups
style_id If the ag is NOOS then style code will be printed as NOOS AG have single style
master_category Master category of the AG
category Category of the AG
subcategory Subcategory of the AG
brand Brand of the AG
brand_segment Brand segment of the AG
gender Gender of the AG
mrp_bucket MRP Bucket of the AG
theme Theme displays if the AG is NOOS - Core/ Bestseller, or Fashion
attribute1 Secondary attribute as per style  master
attribute2 Secondary attribute as per style  master
attribute3 Secondary attribute as per style  master
attribute4 Secondary attribute as per style  master
attribute5 Secondary attribute as per style  master
segment Displays if the AG is top segment or slow segment based on rev/day
historical_sales_qty No of pieces sold for the store-AG in the analysis period
historical_raw_revenue Revenue generated by store-AG in analysis period
historical_raw_discount_value Discount value of store AG in analysis period
sales_quantity_after_liquidation_and_brokenness_clean_up Sales quantity of store AG after cleaning up broken and liquidated sales
revenue_after_liquidation_and_brokenness_clean_up Revenue generated by store AG after cleaning up broken and liquidated sales
discount_value_after_liquidation_and_brokenness_clean_up Discount value in store AG after cleaning up broken and liquidated sales
relevent_sales_quantity Cleaned up sales quantity of relevant weeks- First n days when the style got live
relevant_revenue Cleaned up revenue of relevant weeks- First n days when the style got live
revenue_per_live_day Relevant cleaned up revenue/live days for the style in AG
revenue_per_live_day_per_style revenue_per_live_day/No of styles in AG
revenue_contribution (%) Revenue contribution at store level for each AG as per relevant revenue
asp ASP of AG
revenue Projected revenue for store AG based on relevant revenue and AOP/ store targets
date_range Start and end data of the analysis period