Your Best Customer Looks Like Three Strangers
Customers buy online, in store and over the phone, and every channel keeps its own record of them. A different email here, a nickname there, an old address in the loyalty system, and one valuable customer becomes three ordinary ones.
Three small customers worth $210, $2,840 and $3,150. In reality, one customer worth $6,200.
Every Channel Has A Different Customer
A customer who signs up online, pays in store with a loyalty card and calls support creates at least three records. Each system keys them its own way: an email, a card number, a phone number. None of those keys is shared, and the names, addresses and spellings rarely line up exactly.
So every report built on those systems undercounts loyalty and overcounts customers. Lifetime value is split across rows, the best customers look average, retention looks worse than it is, and marketing sends a welcome offer to someone who has shopped with you for ten years.
Exact joins on email or phone catch only the easy cases. The hard ones, a maiden name, a work email, a typo in the street name, are exactly the ones that hide your most engaged customers.
Split Histories
Purchases, visits and support calls for one person are spread across records that never meet.
Undervalued Customers
Lifetime value and loyalty tiers are calculated per record, so top customers look ordinary.
Wrong Treatment
A long-time customer gets a new-customer offer, or a support agent cannot see their history.
Resolve The Customer, Then Build The View
Match customer records across every channel before building the profile. Combine fuzzy matching on names and addresses with exact rules where you have a shared key, and give each real customer one stable ID.
Build the Customer 360 on that ID, inside the data platform where the channel data already lands, and keep it current as new orders, sign-ups and support tickets arrive.
Store, web and support history now sit on one customer.
One ID Per Customer
Every channel record for the same person carries the same customer ID.
Built Where The Data Lives
The profile sits in your warehouse or lakehouse, next to the data that feeds it.
Always Up To Date
New activity joins the existing customer instead of creating a new one.
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
A Customer 360 You Own
Your Fields, Your Rules
Train Zingg on the customer attributes you care about, and add deterministic rules on keys like email or loyalty ID. Entity resolution engine
Persistent ZINGG_ID
Every customer keeps one global ID across systems and runs. ZINGG_ID
Scales To Millions
Zingg learns which records are worth comparing, so matching stays fast as customers grow. Scale
Incremental Updates
New and changed records join the right customer without a full rerun. 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.
Customer 360 Questions
What is a Customer 360?
A single view of each customer that combines their records from every channel and system: purchases, visits, support, marketing and account data.
Why isn’t matching on email enough?
People use several emails, share household addresses and leave fields blank. Exact keys catch the easy duplicates and miss the customers who engage across the most channels.
Where does the Customer 360 live?
In your own data platform: Databricks, Snowflake, Microsoft Fabric, Google Cloud or AWS. Zingg writes resolved customers with a ZINGG_ID to your tables.
Does the customer ID change when new data arrives?
No. The ZINGG_ID persists. New and updated records join the customer they match.
Know Every CustomerOnce
Resolve customers across channels inside your own data platform.