Customer Data Platform
The customer data platform layer in DriveMetaData is the foundation for reporting, AI insight, segmentation, and activation. It brings customer signals from multiple systems into a unified, usable customer view.
What the CDP layer solves
Customers rarely interact through one clean channel. A single journey can include an ad click, anonymous web session, mobile app install, email open, purchase, support interaction, and offline conversion. Without a shared customer view, teams see fragments instead of behavior.
The CDP layer helps teams:
- Connect behavior, campaign, CRM, product, and transaction data.
- Resolve identities across permitted identifiers.
- Build profiles that update as new events arrive.
- Make reporting and activation use the same customer definitions.
- Reduce manual reconciliation across tools.
Customer profile structure
A typical profile includes:
| Profile area | Examples |
|---|---|
| Identifiers | User ID, anonymous ID, CRM ID, device ID, email hash |
| Traits | Region, lifecycle stage, account type, language, preferences |
| Events | Page view, app open, signup, add to cart, purchase, renewal |
| Campaign history | Source, medium, campaign, ad group, creative, click metadata |
| Predictions | Conversion likelihood, churn risk, LTV band, engagement momentum |
| Activation status | Audience memberships, channel eligibility, suppression flags |
Identity resolution
Identity resolution connects related signals into one profile when the data supports it. For example, an anonymous web visitor can become a known profile after signup, or a mobile app event can be connected to a CRM user after login.
Good identity rules should be:
- Deterministic where possible.
- Reviewed by analytics and privacy stakeholders.
- Documented for reporting users.
- Tested with edge cases such as shared devices, duplicate emails, and account transfers.
Do not merge identities only because two records look similar. Use approved identifiers and consent-aware rules defined by your organization.
Real-time and batch data
DriveMetaData-style workflows often combine both:
- Real-time events for journeys, segment updates, fraud signals, and behavior-triggered actions.
- Batch data for CRM fields, revenue adjustments, offline conversions, refunds, and warehouse enrichment.
When a report seems delayed, confirm whether the underlying source updates in real time, on a schedule, or after an internal approval workflow.
Data quality checklist
Before using a dataset for reporting or activation, check:
- Event names are consistent across web and app.
- Required event properties are present.
- Timestamps are in the expected timezone.
- Revenue and currency fields are normalized.
- Test traffic is labeled or excluded.
- Consent and suppression fields are available to activation workflows.
- Duplicate records are handled before KPIs are published.
How the CDP layer supports other features
- Attribution uses profile and campaign history to connect touchpoints to outcomes.
- AI analytics uses behavioral patterns to identify intent, churn risk, and likely value.
- Segmentation uses profile traits, events, predictions, and eligibility rules.
- Fraud protection uses traffic, device, click, install, and event patterns to flag suspicious activity.