95% anonymous, 0% actionable
This chain is one of the fastest-growing grocery retailers in the United States, and one of the most data-challenged. As a low-friction, no-frills grocery model, it does not have a traditional loyalty program. That means the overwhelming majority of its in-store transactions are anonymous: a basket of groceries, a payment, and nothing else.
The chain processes over 43 million in-store transactions every month. Before Deep Sync, approximately 95% of those transactions had no customer identity attached. They were commercially invisible. The retailer could not personalize, suppress, retarget, or attribute media spend to in-store revenue.
The standard industry answer, launching a loyalty program, is a multi-year, multi-million-dollar undertaking.
Resolve identity from the transaction signal itself
Deep Sync's Transaction Matching is a fundamentally different answer: resolve the identity of the buyer using the transaction signal itself, with no customer opt-in required. Three sequential passes run against the full monthly POS file, each capturing what the previous pass missed.
- 01
Loyalty signal match
For the small share of transactions where loyalty data exists (card swipe, app scan), Deep Sync uses that PII anchor to resolve identity first. High-confidence, exact matches.
~9.6Mtransactions resolved - 02
Card & payment signal match
Deep Sync matches payment card signals against our identity graph, resolving transactions that have no loyalty data but do have card-level signals, the vast majority of grocery POS events.
~3.3Mincremental transactions - 03
Store catchment match
For remaining unmatched transactions, Deep Sync uses store-level geographic catchment modeling combined with household identity data to probabilistically resolve the buyer. This is the step that catches what pure exact-match methods miss.
~18.1Mincremental transactions
The grocery identity waterfall
Deep Sync processes the full monthly POS file, tens of millions of raw transactions, in a single production run, with no loyalty program required.
What the chain can now do that it couldn't before
Reach specific shoppers with relevant offers based on resolved purchase history and basket composition, even without a loyalty program.
Exclude existing customers from acquisition campaigns, reducing wasted media spend and improving the cost efficiency of new customer acquisition.
Build addressable audiences from resolved in-store buyers and serve them ads across Google, Meta, and CTV, connecting digital spend to physical store behavior.
Close the loop between digital ad exposure and in-store purchase, without a loyalty program, making true closed-loop attribution possible at grocery scale.
Transaction matching is not a feature most identity vendors offer. It requires a proprietary matching methodology, a deep consumer identity graph, and the operational infrastructure to run monthly production pipelines against tens of millions of records.
“Transaction matching doesn't just improve data quality. It fundamentally changes what the retailer can do with marketing: personalization, suppression, attribution, retargeting, capabilities that were impossible before because 95% of their customers were completely invisible. By resolving roughly 70% of those buyers into known, addressable individuals, Deep Sync transformed invisible purchase activity into measurable customer intelligence.”
You don't need a loyalty program to market like you have one
The chain resolved most of its monthly volume without asking a single customer to sign up. If your stores run on anonymous transactions, the same waterfall applies to your file.