Retail sales key performance indicator (kpi) prescriptive analysis

A method comprising:

• receiving historical sales data for a plurality of retail stores;
• training a multi-layer architecture of regression machine learning models (MLMs) using the historical sales data;
• applying the multi-layer architecture to a set of sales key performance indicators (KPIs);
• detecting, using a first layer of the multi-layer architecture, at least one underperforming sales KPI where a store is underperforming;
• setting, using the first layer, a measurable and achievable target to improve the at least one underperforming sales KPI;
• determining, using a second layer of the multi-layer architecture, a particular action to achieve the measurable and achievable target;
• and
• providing the particular action as one or more recommendations for improving a sales performance of the store.

A system comprising:

• a processor;
• a memory storing instructions that, when executed by the processor, cause the system to:
• implement a multi-layer architecture of machine learning models (MLM) for a set of sales key performance indicators (KPIs);
• identify, using the multi-layer architecture, at least one underperforming sales KPI for a store;
• set, using the multi-layer architecture, an achievable and measurable improvement target for the at least one underperforming sales KPI;
• generate, using the multi-layer architecture, a list of recommendations for meeting the achievable and measurable improvement target;
• and
• provide the list of recommendations to enable an improvement in a sales performance for the store.