Optimum Depth Output
- Jaikirat Singh (Unlicensed)
- Mansvi Vohra (Unlicensed)
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 |