Industry
Chemicals and Manufacturing
More than a million products mapped through a Single Source of Truth
in sales opportunities identified
uncovered across four business units
A leading global chemical producer wanted to generate additional revenue from its top 25 customers. However, account managers lacked visibility into more than one million products distributed across approximately 20 planning units, limiting their ability to identify relevant cross-sell and upsell opportunities.
Altimetrik created a Single Source of Truth that unified product, customer, sales, and market data. Machine learning algorithms analyzed this information alongside geographic restrictions and customer spending capacity, generating actionable recommendations through an intuitive dashboard.
The client’s sales process was primarily relationship-driven. Account managers responded to customer requirements but lacked the product knowledge and cross-business visibility needed to recommend additional solutions proactively.
Rapid product expansion through acquisitions and innovation made it difficult to track new offerings. Product customization, geographic sales restrictions, and ingredient regulations added further complexity. These limitations prevented teams from consistently matching the right products with the right customers and markets.
Without a unified view of products, customers, and sales constraints, the organization could not fully capitalize on its extensive portfolio. Sales teams needed trusted, accessible insights to move from a reactive pull model to a proactive, data-driven growth strategy.
Altimetrik created a Single Source of Truth by integrating invoice data, product and customer master records, market intelligence, and customer spending capacity.
An ensemble of machine learning algorithms analyzed historical sales and product attributes to identify cross-sell and upsell patterns. Business rules incorporated industry requirements, geographic restrictions, customer-specific products, and spending capacity to ensure recommendations were relevant and commercially viable.
Recommendations were validated using historical data and secondary research before being presented through a user-friendly visual dashboard. Account managers could review opportunities across business units and geographies without navigating complex source systems.
Regular feedback sessions with sales teams helped assess recommendation adoption and refine algorithmic rules through continuous iteration.
Identified $540 million in sales opportunities across the client’s top 25 customer accounts.
Uncovered 1,000 opportunities across four business units using eight recurring sales patterns.
Mapped more than one million products into a trusted data foundation, enabling account managers to recommend relevant offerings while considering customer needs, spending capacity, and geographic constraints.
Altimetrik combined data engineering and machine learning to transform fragmented product data into actionable sales intelligence.
