Case Study

Run centralized pricing strategies with real time offer optimization


Retailers can feel overwhelmed as the market place is abundant with pricing products with all of them claiming to be built on AI framework. The reality is most of these solutions miss the mark and cannot mirror how customers, prices & brands interact in the market. All this leads to an inaccurate demand estimation, inaccurate price elasticity measures eventually leading to a weak pricing solution.

In the example below, we helped our client implement a centralized base price optimization (feature-based pricing for SKUs) and using that as foundation to setup store level offer & mark-down optimizations. Our client had gone through two failed implementations from other vendors and 


For a premium watch retailer, Convergytics deployed a pricing solution based on choice-based conjoint framework and surface optimization models. The custom solution developed for our client get a deep understanding of demand patterns, elasticity measures, product-price interaction effects across categories. These insights were the basis of an optimal base price and helped in defining various pricing / promotional strategies 


As a result of the engagement, the retailer saw an increase in profitability by 17%. The solution simplified pricing analysis with a web-based interface that allowed users to analyze key pricing metrics and their impact in real time. Today, pricing analysts using the solution to test several “What If Scenarios” and chose the winning pricing strategy

Increase in profitability by


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