Case study: Pricing Optimization for a Fortune 500 Memory Manufacturing Company

Business Context

Our Client, a global Fortune 500 semiconductor and memory manufacturing company, works in an intensely volatile market that sees a significant chance of human error. Given the extent of liabilities, they were looking to build an intelligent price recommendation engine for sales representatives that could predict prices that would consider supply/demand variations and market dynamics while also focussing on margin enhancement.

How BRIDGEi2i Delivered Value?

BRIDGEi2i leveraged the right combination of data engineering, machine learning, and advanced algorithmic AI accelerators to develop an intelligent pricing engine.

This engine was capable of self-learning and took in customer buying and quoting behavior, product attribute, volume distribution across customer regions. With real-time price intelligence that could be embedded in the Client’s system and a stream of regular feedback on the stability of the model and market dynamics, the recommendation engine proved to be extremely useful. With a massive revenue increase that boosted the win rate, the Client observed a high percentage of adoption in the intelligently recommended prices.

This AI-Powered Pricing Engine Makes all the Difference!

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