Adhesives & Industrial Products
The client is one of the world's leading supplier for adhesives, sealants and functional coatings. In addition to enhancing its operational efficiency and procuring eco-friendly raw materials, the business division strives to take the lead in technological innovation and create significant influence through its wide-ranging product portfolio.
Our client's technologies and solutions, serving over 100,000 clients across 750+ industry segments worldwide, have already made a substantial impact, contributing to their impressive annual revenue of over 20 billion euros and employing 50,000 individuals across the globe.
They searched to optimize pricing & the digitalize their overall process, in doing so working with a Pricing Vendor, however there was no pricing & data maturity assessment done prior, resulting in the overall platform utilization and trust to be low.
PricingWorks successfully guided the client through the pain points by offering insights on how the price optimization algorithms are working and performing. This was done by recreating from scratch the Pricing Vendor's AI engine and comparing it to an in-house model. We have drafted recommendations on how to improve the vendor's model performance and have developed a new AI model that better suits the client's needs and performs better than the current ones.
Highlights
- Conducted a full data quality, structure and integrity check to understand feature importance & relevance in an ML model.
- Developed a ML model to replicate our client's VENDOR AI capabilities and understand shortcomings.
- Offered recommendations to improve the model's output and data utilization by using different features, data structure changes and model parameters.
Benefits Achieved
- Comprehensive understanding of entire the data quality (gaps) and points of improvement moving forward.
- Identified key attributes and elements of the AI model used by the vendor that by altering resulted in positive top & bottom-line impact.
- Optimized ML model by adding set of attributes that were highly relevant for the predictability of the price positioning, equipping the client with more targeted pricing strategies.