Introduction:

This module recommends, on the basis of each style's/ SKU’s ongoing performance and stock status if we should continue the current discount on the style/ SKU is working for it or if we should increase or decrease the discount on it to improve its sales or margins respectively.

Business use-cases:

It is capable of handling business cases like -

• In-Season discounting (Business as usual)
• Event discounting like - End of season sale, Platform events, etc.
• Old merchandise liquidation
• Identifying styles breaching guardrails, and many more...

Impact delivered:

1. Up to 6% margin improvement on fast movers for online point of sales
2. 71% improvement in ROS and a 10% discount increment for low-performing styles in offline stores
3. 2x increase in the frequency of decision making
4. Successfully handled liquidation scenarios for in-season and old-season scenarios.

Parameters:

The algorithm takes into consideration all the important parameters to make decisions -

• The True Rate of Sale $^{TM}$ - i.e. ROS of a style when it was present in a healthy size set to compare true performance amongst styles
• The Ageing of style - for how many days has the style been trading for / how old is it
• the stock cover of the style - how many days of stock do we have for that style and then also
• the Health of the style - if the style is currently available for sale in a healthy size set or with only a few sizes options left.
• Sellthrough has been added as another option for offline brands that prefer this over inventory cover.