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Today’s contemporary world has pushed businesses away from reactive traditional pricing approaches that mainly banks upon cost plus markup. Unlike past, to match customer expectations amid cut-throat competition, today, a product manager has to consider a myriad of factors to set a feasible price for its offering. To name a few: deep knowledge about consumers’ preferences, buying habits, spend capacity, market dynamics, supply performances, inventory position, competitor activities, short product life cycle, apart from the historical demand and customer segmentation. Considering many such inputs to set price using manual and archaic approaches is an arduous task and prone to errors that lead to lost opportunity or margins. Hence, the need of the hour is to incorporate an intelligent pricing approach that brings in distinct advantages by unleashing the true potential of artificial intelligence (AI) and machine learning (ML).
Businesses are exploring robust pricing strategies to ensure revenue maximization and, at the same time, assuring capacity optimization. As the market dynamics continue to influence pricing models, the need to augment demand through intelligent pricing becomes inevitable; especially when it can incorporate surge pricing mechanisms during peak demands. Leveraging the power of AI and ML, the new-age intelligent pricing framework automatically fluctuates the prices based on real-time data about supply, historical demand, and competition to adapt to changes in the marketplace and improve profitability quickly.