Turning 70% Revenue Concentration Into ₹1.2 Crore of Additional Sales
Mapping the products and customers behind 70% of revenue gave the sales team a forecast-driven view of what to make, for whom, and what else to offer them.
ITChamps implemented an AI-enabled sales forecasting, finished-goods planning, and cross-sell/upsell solution for a tool holder and tool design manufacturer, built around the products and customers contributing roughly 70% of revenue.
The Challenge
Finished-goods demand was hard to forecast, so sales were left on the table
The company experienced both excess finished goods and stock-outs against sudden demand, along with missed sales opportunities from not knowing what to manufacture, in what quantity, and for which customers.
- Excess finished goods resulted in inventory that went unsold.
- Finished-goods shortages meant sudden customer demand couldn't always be met.
- Missed sales opportunities arose from inadequate product availability at the right time.
- There was no systematic way to decide what to manufacture, for whom, and how much.
The Solution
Forecast around the product–customer pairs that drive revenue
The solution mapped the products and customers contributing approximately 70% of revenue, forecast demand at monthly and quarterly levels, translated forecasts into finished-goods plans, and layered in cross-sell/upsell modelling.
Identified the products and customers contributing approximately 70% of revenue and mapped key products against key customers.
Analyzed historical sales patterns and seasonal/recurring demand for priority product–customer combinations.
Engineered sales, customer, product, and historical demand variables for forecasting.
Generated monthly and quarterly forecasts, with quarterly forecasting supporting ~45–60 day lead-time products.
Translated forecasts into recommended finished-goods requirements.
Analyzed customer–product relationships to recommend additional products to existing customers.
Results
Measured business impact
Share of revenue covered by the priority product–customer combinations.
Additional revenue from forecast-driven planning and cross-sell/upsell.
Monthly and quarterly forecasting, matched to ~45–60 day lead times.
Reduced risk of both overstocking and stock-outs.
Highlights
- Improved understanding of what products were required, by which customers, and when.
- Reduced the risk of both overstocking and stock-outs.
- Enabled the sales team to target the right customers with the right products.
- Helped stabilize revenue through better product targeting and inventory planning.
Services and technology
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