Problem Statement

The CPG brand was overspending on marketing as duplicate offers were being sent to multiple members of the same household. Without visibility into collective household behavior, campaigns were fragmented, discounts were overextended, and promotional costs escalated—reducing ROI and customer satisfaction.

Key Challenges

• Duplicate offers were sent to

  multiple members of the same household, driving up promotional costs.

• Broad-based individual targeting overlooked

  household-level purchase behavior and shared consumption patterns.

• Marketing budgets

  were wasted on redundant rewards with little incremental value.

• Teams lacked visibility into

  the “true customer unit” (the household), making it difficult to personalize campaigns effectively.

• Global variations in family

  structures and shared accounts further complicated segmentation accuracy.

• Over-distribution

  of discounts eroded brand profitability and led to customer fatigue.

Solution Implemented

Use AI-driven data matching to group individual loyalty accounts into accurate household profiles.

• Eliminate duplicate offers : across family members, reducing redundancy and wasted spend.

• Shift campaign strategies : from individual to household-level targeting, ensuring relevance at scale.

• Gain visibility into household: purchase patterns and collective spending behavior.

• Personalize loyalty campaigns : with offers tailored to household consumption needs, not just individual actions.

• Standardize householding logic globally, : accounting for cultural and regional differences in family structures.

Business Impact

In the first quarter, the CPG brand realized:

• -18% reduction in duplicate offers,

  cutting wasted marketing spend.
  
  
  

• Improved customer satisfaction,

  as households received relevant, non-redundant offers.

• Better ROI

  from loyalty campaigns due to smarter segmentation and targeting.