Your CDP Copied The Data And Kept The Duplicates
A packaged CDP asks you to copy customer data out of your warehouse into its own store, where identity resolution runs as a black box. You pay twice for the data, lose control of the matching rules and still cannot explain why two profiles merged.
Data copied out, matching rules you cannot see, and profiles your warehouse does not agree with.
Identity Shouldn’t Leave The Warehouse
Most customer data already lands in a warehouse or lakehouse. A packaged CDP copies it out again, resolves identities with rules you cannot inspect, and sends the result to marketing tools. Now there are two versions of every customer, and they rarely agree.
When a profile merges two people, or fails to merge one, there is no way to see why or to fix the rule. Privacy reviews get harder, because personal data sits in another vendor’s store. And the cost grows with every record copied.
A composable CDP keeps the data where it is and assembles the rest from parts. The part most teams struggle with is identity resolution.
Data Leaves Your Account
Customer data is copied into a third-party store to be resolved.
Black-Box Matching
You cannot see or tune the rules that merge and split profiles.
Two Versions Of Truth
The CDP and the warehouse disagree about who your customers are.
Resolve Identity Where The Data Lives
Build the identity graph inside your own data platform. Resolve customers across every source there, give each one a stable ID, and let segmentation, activation and reverse ETL tools read the resolved profiles directly.
Own the matching: train it on your data, see why records were merged, and change it when your business changes, without asking a vendor.
Activation tools read this graph where it lives.
Warehouse-Native Graph
The identity graph is a set of tables in your own platform.
Transparent Matching
Every merge can be explained and tuned.
Any Activation Tool
Reverse ETL and marketing tools read the same resolved profiles.
The Identity Layer Under Customer Analytics
Zingg runs as a workload inside your data platform and gives every entity one persistent ZINGG_ID. Everything above it reads the same resolved entities.
Reads your tables in placeWrites golden records and ZINGG_ID backNo copies leave the platform
The same layer powersFinancial Crime & RiskPrivacy & ComplianceSupply Chain & ProcurementProduct 360Master Data ManagementAI and Agentic Foundations
The Identity Engine For A Composable CDP
Runs In Your Platform
Zingg runs inside Databricks, Snowflake, Microsoft Fabric, Google Cloud or AWS. No customer data leaves your account.
Persistent ZINGG_ID
Profiles keep the same ID across runs, so audiences and syncs stay stable. ZINGG_ID
Explainable Merges
See the evidence behind every profile merge. Explainability
Incremental Updates
New events and sign-ups join existing profiles without rebuilding the graph. Incremental flow
For the first time, we’re able to understand how customers are shopping with us — online, in-store, over the phone, or in restaurants. Zingg has helped us unify this data and gain insights we never had before.
Composable CDP Questions
What is a composable CDP?
A customer data platform assembled on top of your own warehouse or lakehouse, instead of a packaged product that copies the data into its own store.
Where does Zingg fit?
Zingg is the identity resolution part: it builds the resolved customer profiles and identity graph inside your data platform.
Does Zingg activate audiences?
No. Zingg resolves identities. Your reverse ETL and marketing tools activate audiences built on the resolved profiles.
Who has built a composable CDP with Zingg?
Fortnum & Mason built a composable CDP using Zingg for entity resolution.
Own YourIdentity Graph
Resolve customers inside your own data platform and activate from there.