The sales force of a leading manufacturer of cooking oil, needs a statistical model to forecast daily sales at retail outlets – for 200 sales personnel serving 6000 plus retail outlets.
With sales targets need to be set at weekly and monthly levels, the daily sales forecasting at retail outlets done using simple excel extrapolation techniques is questionable. Forecasts are aggregated at various levels for target setting and any approximation has a cascading effect through the hierarchy.


Forecasting models are used on current sales data to generate accurate daily forecasts for the retail outlets. These daily level forecasts are then leveraged for better target setting at weekly and monthly levels. Other inherent patterns extracted from the sales data (such as best days of week to call, best product mix for up-sell, best discount promotion period and many more) provide key insights for the sales team to target their retailers better. Sales team is educated on the insights at the retailer level that can help improve their overall performance and sales incentives.


Intelligent Sales Forecasting (Daily, Weekly, Monthly) at Retailer level from historical sales data – that could positively impact potential supply chain and marketing decisions.
Insights for managing salespeople – determining incentives for salesman by Route, realigning salesman by Retail outlets for better customer relationships.
Insights for products and promotions – timing and depth of discounts, product sales decline predictions, understanding what SKUs to promote/discontinue.


Retail, Sales Forecast

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Acies is a design and development firm helping organizations transform their business and increase market value. Acies helps businesses cope and innovate in the digitalization era using a unified framework of technology, data, insights, design and strategy.