A leading CPG firm wanted to know the effect of new product on parent brand volume, effects of promotion and new product incrementalities.

• A six member AbsolutData team worked in close cooperation with the client for about six months.
• Previous two years’ panel data was collected from world’s leading warehouse. This data was subjected to thorough exploratory analysis and sense check.
• We decided to use constrained regression technique with lag variables. Constrained conditions were set up for Price Elasticity and New Product Incrementality.Constraints are input to reflect changing business scenario.
• We built a Parent Brand Volume forecasting model using SAS and in-house regression tools.
• This was used to accurately explain new product potential, promotion effect, and forecast parent brand sales for next 2 years.
• Pivotal promotions and New Product derived from final model.RMSE levels as low as 1% guaranteeing near pin point precision for the model.

• Client issues with New Product Potential and effective promotion resolved.
• Significant improvement in brand recognition and effective cost streamlining.
• Consistent modeling solutions for client across geographies viz. Latin America, Asia and Asia Pacific regions.