F500 CPG Giant – Innovation Analytics

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Client wanted to find the incrementalities caused by each of their innovation products launched in the past and to predict similar metrics for future innovations
Prior to this project, customer's analysis of the performance of innovation products was based on rough estimates and ad-hoc market studies

Customer's sales data was taken from Big Query. Innovation products and their corresponding incrementality rates across different time frames were identified through multi-layer Bayesian regression modelling
Post this, a supervised learning model was used to predict incrementality for future innovations. This whole process was automated and scaled across markets

Fractal provided an end-to-end scalable solution for measuring incrementalities of innovation products launched by the customer
Client now has exhaustive datasets of each innovation launched in corresponding markets, leading to more informed decision-making on future innovation strategy
Automation of the process also enabled scalability and quick adoption
Client now has a robust and reliable source of analyses at their disposal. They can leverage the insights from this project, and use it at the crux of their future product strategy

Modeling technique and algorithmic expertise helped solve the business challenge
Data engineering standards and processes were essential in ensuring the automation and scalability of the solution

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