Customer story
Supermarket Chain Boosts Loyalty with Personalized Campaigns
The challenge
44% of all purchases not attributed to any customer profile
Duplicate profiles equaled 3x the country's total population
Inability to personalize loyalty messages due to conflicting profiles
The solution
Align and engage 22 separate business units
Resolve identities across the business matched on transaction data
Personalize loyalty campaigns
The Results
The full story
This leading North American supermarket, grocery store, healthcare, and pharmacy chain pioneered the self-service grocery store model, allowing customers to browse and add to cart themselves. The chain boasts 2,400 locations and 90% of the country's population conveniently live within 10 minutes of a store, resulting in a wealth of first-party customer data.
Growth stalled due to inaccurate first-party data and duplicate profiles. The first step was laying a foundation of unified customer profiles across the entire martech ecosystem, including all 22 business units, to streamline fragmented data.
The goal: develop targeted campaigns that would boost loyalty spending and unlock new markets through segmentation built on transactional data—none of which was possible with their existing customer profile information.
The Challenge
Disproportionate duplicate records hinder personalization
Imagine running the largest grocery chain but not knowing who your shoppers really were. Their system showed nearly 3x more customers than the country’s entire population. Worse yet, 44% of all purchases were not linked to any customer profile. They had to find the right tool to sift through millions of duplicated profiles.
Although 75% of adults were enrolled in the grocery store’s loyalty program, inaccurate customer profiles stood in the way of being able to personalize messaging to drive incremental revenue from existing members. Moreover, the fragmented customer profiles yielded lower match rates across digital media platforms. This made it harder to develop effective audience segments within third-party media networks.
The Solution
Collaboration fuels alignment of identity resolution needs
Banded together under the CEO’s vision, all 22 business units came together for monthly meetings during the evaluation phase.
The VP of Technology and Analytics had previously implemented Amperity and recognized its superior customer profiling capabilities. Leadership agreed personalization was crucial for increasing revenue from loyal customers and attracting new ones through paid media. Collaborating with Accenture on an RFP for identity resolution revealed broader departmental needs, making an in-house solution impractical due to time constraints.
"Once Amperity’s ID Resolution deduplicated 41 million profiles, we saw an 18% improvement in customer profile accuracy and were able to drastically improve our match rate. Experimentation and personalization at scale went from a pipe dream to our reality."
The results
Knowing customers led to increased loyalty spending
Amperity’s AI-powered ID resolution and commitment to customer profiles proved to be key differentiators. The ID resolution process stitched together 102 million customer records and deduped 41 million—a 60% reduction. This resulted in an 18% improvement in customer profile accuracy by backfilling past transactions matched on tokenized credit cards and other PII. Today, they integrate all audience products into Amperity, with 63 audience feeds per day powering personalization.
The chain boosted incremental loyalty revenue through personalized campaigns, like “Spend an additional $10 over the course of six days for 500 extra loyalty points,” generating nearly $2.5 million each year. This approach saw increased spending, enhanced engagement, and fortified brand loyalty.
Improved customer profile accuracy significantly boosted third-party media network match rates. Phone number identification shot up by 60%, while email matches increased by 4.3%. This initiative also led to a 5% increase in Meta response rates and a tenfold growth in transactional data within retail media networks.
Conclusion
Accurate customer records boost loyalty revenue
Through its strategic partnership with Amperity, the grocery store chain successfully transformed their disparate customer data into a unified, accurate system that delivered tangible business results. By removing duplicate profiles by 60% and boosting accuracy by 18%, they successfully deployed hyper-personalized loyalty campaigns that generated $2.5 million yearly in revenue.
The project consolidated their 22 business units' data and significantly improved media matching capabilities— phone number identification increased by 60% and email matches rose by 4.3%. This case is a masterclass in how organizing customer data can turn a messy situation into a powerful engine for personalization, customer engagement, and revenue growth.
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