Price optimization

Find the perfect balance of profit, revenue and customer demand

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Black Fridays, Cyber Mondays, Season sales, this week’s promotions and tomorrow’s special offers.

Customers are all the rage on different campaigns and sales.

That translates to a simple thing: Retailers’ worlds revolve around campaigns and pricing. The more attractive pricing, the higher the volumes.

But at what cost?


Pricing strategies optimized by data science

Generate effective promotional strategies, price points and tactics by category down to individual SKU’s at scale.

Compare pricing scenarios and enhance understanding between financial impacts, competition, customer perception and reactions.

Apply pricing effects to improve forecasts, planning, execution and measurement of campaigns & promotions.


Data collection and processing


Required: Product master, receipt data. 

Optional: Survey and competitor data.

Pre-built models are being taught with client data

Price elasticity models are calculated at scale. Products are being categorized based on their elasticity. Forecast and optimization models can be run based on various scenarios. 

Price elasticity models are used to maximize revenues or profits 

Price elasticities are calculated on product and category level. In addition, the process produces product level sales forecasts per transaction and per day at different price points. These highlight the price point at which revenue is maximized.  Price elasticities are stored into product master. 


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