Retailers are data-rich but identity-poor. Transaction Matching resolves anonymous media, POS, loyalty, and card data to real people and households, so you can finally measure who actually bought.
If you operate in grocery, QSR, convenience, or any other kind of retail, you already have massive amounts of data. Media data. POS data. Loyalty data. Card transaction data. On the surface, your organization looks data-rich and analytics-driven.
And yet, despite all of it, most enterprise brands still struggle to answer one fundamental question: Who actually bought?
That gap is not a data issue. It's an identity issue.
Data is everywhere. Identity nowhere.
Media platforms tell you who saw an ad, not who purchased. POS systems record transactions, not people. Loyalty programs capture behavior, but only for a subset of customers. Card transaction data shows real-world spend, but without a customer identity attached.
Each dataset is valuable on its own. None of them connect. And that's assuming the data you have is fresh and up to date, which is rarely the case.
This fragmentation leaves brands with dashboards full of activity but very little clarity. Transactions happen at scale, yet they can't be consistently resolved to real individuals or households. Without identity resolution, measurement becomes an approximation, retail media optimization turns into a guessing game, and market share is modeled instead of observed. Brands believe they are optimizing growth, but they are really optimizing anonymous behavior, and anonymous behavior doesn't scale.
The challenge isn't collecting more data. It's connecting the data you already have.
Media data, loyalty data, POS data, and card transactions all exist today. But without a unifying identity layer, they are fragmented and isolated, creating a blind spot exactly where business decisions matter most.
Identity is the bridge, the layer that makes data usable. It brings continuity to disconnected transactions and enables brands to move from counting purchases to understanding real people and households.
From anonymous spend to people-based intelligence.
An identity layer functions as foundational infrastructure across the commerce ecosystem. This is exactly what Transaction Matching delivers.
Transaction Matching resolves anonymous transaction data to verified individuals and households in a privacy-safe, deterministic way. It does not replace existing platforms or workflows; it integrates with them, creating continuity across media, POS, loyalty, and card transaction data.
With identity in place, organizations gain a clear view of who is actually buying beyond loyalty programs. It empowers them to measure media performance against real purchasing behavior, understand true shopper overlap across brands and categories, and make decisions based on people rather than inferred proxies.
Deep Sync provides that layer. We act as the identity bridge, transforming fragmented transaction data into measurable, people-based intelligence, because sustainable growth is driven not by more transactions, but by understanding who is behind them.
Stop measuring transactions. Start understanding people.
