Originally Published on: QuantzigHow we Helped FMCG Client To Measure Cannibalization at an SKU Level

In a strategic partnership, Quantzig collaborated with a prominent consumer goods manufacturer headquartered in the USA. Boasting a dedicated workforce spanning the USA, Europe, and Asia, the client faced the challenge of comprehending the impact of cannibalization on their SKUs, posing obstacles to strategic decision-making and resource allocation. The client's emphasis on brand-level ROI inadvertently overlooked crucial shifts in demand between brands, exacerbated by the in-house analytics team's limitations in SKU-level cannibalization analysis.

Innovative Solutions: Quantzig's sophisticated model meticulously analyzed sales dynamics, incorporating competitive activities, category expansion, and promotional efforts. A decomposed model delved into demand transference among SKUs, evaluating both marketing impact and cannibalization effects. A specialized measurement tool provided real-time insights into immediate cannibalization impact, leveraging a PowerBI dashboard and a Python model on an Azure container.

Impact Realized: The implemented strategies yielded valuable insights into SKU-level cannibalization, facilitating the reallocation of 15% of the budget and streamlining promotion planning within a mere 3 days.

Client's Profile: A leading consumer goods manufacturer headquartered in the USA, renowned for its diverse product range, the client grappled with challenges in measuring ROI at the brand level and orchestrating cohesive marketing efforts across their extensive portfolio.

Overcoming Challenges: The client's focus on brand-level ROI resulted in resource allocation inefficiencies, while a lack of coordination impeded improvements in category share. Limited SKU-level cannibalization analysis hindered strategic decision-making.

Strategic Interventions: Quantzig's model deciphered the intricacies of sales drivers, optimizing competitive actions, category growth, and promotional strategies. Simultaneously assessing marketing impact and cannibalization, the decomposed model offered comprehensive insights. The dedicated tool, complemented by a PowerBI dashboard and a Python model on an Azure container, seamlessly integrated visual appeal with advanced machine learning capabilities.

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