Collect
Define the event taxonomy and campaign parameters, then validate the selected collection interface.
- Receives
- Web, channel and approved server events
- Produces
- Validated measurement events
Marketing analytics platform
Unify campaign, channel and lifecycle data into a measurement environment that supports informed decisions.
Let’s connect
From channel signals to a defensible measure
Bring web, campaign and CRM data together while preserving the limits of identity matching and attribution.
Connect
Associate eligible events with campaign and customer references through documented identity rules.
- Receives
- Event records and CRM context
- Produces
- Matched and unmatched datasets
Model
Apply the agreed attribution and metric definitions with clear date windows and exclusions.
- Receives
- Connected datasets and metric contract
- Produces
- Marketing measures with lineage
Interpret
Present operational context and distinguish observed association from evidence of incremental impact.
- Receives
- Validated report and campaign context
- Produces
- Actionable measurement review
Step 1 of 4
Inspect the data contract.
Select a field to examine its owner, permitted changes and conflict handling. Clear ownership keeps updates consistent across systems.
| Field or object | Accountable owner | Mapping and control |
|---|---|---|
| Marketing operations | Connects taxonomy to platform campaign references. | |
| Analytics owner | Uses a maintained dictionary with required parameters. | |
| Data steward | Records the approved basis for joining customer activity. |
Resolve the important decisions.
GA4 server events
Measurement Protocol supplements automatic collection. Its validation endpoint checks payloads without adding events to reports.
Attribution coverage
A model cannot allocate credit to interactions it does not observe. Keep this limitation visible beside the measure.
Validate before handover.
Select the scenarios to discuss with your implementation team.
0 of 3 selected
Test an example workflowPlatform documentation
Built around how you operate.
This solution brings marketing data together at a defined grain so channels and campaigns can be compared with appropriate context. It connects collection standards, transformation rules and reporting views rather than treating analytics as a set of separate dashboards.
Discovery identifies the questions that matter, the available data and the limits of the analysis. The implementation can include campaign dimensions, event taxonomies, warehouse models and attribution views, with quality checks that show when the evidence is incomplete.
What we help you build.
Campaign data model
Relate campaigns, channels, spend and outcomes through consistent identifiers and dimensions.
Event taxonomy
Specify actions, parameters and identity rules for relevant customer interactions.
Attribution views
Compare supported credit models and preserve the assumptions behind each interpretation.
Quality and freshness
Make missing data, delayed sources and definition changes visible to report users.
How the work comes together.
Collect with intent
Start with a tracking plan tied to business questions and approved data use.
Transform consistently
Normalize campaign dimensions and validate relationships between source datasets.
Interpret carefully
Review performance with coverage, timing and attribution limitations in view.
The engineering detail.
Read the contracts, controls and failure behavior behind a maintainable implementation.
A few practical questions.
Can advertising data and CRM outcomes be combined?
Yes, where suitable identifiers and access are available. The matching approach and the coverage of the resulting dataset must be documented.
Will all platforms report the same conversion count?
Not necessarily. Attribution windows, identity methods, time zones and event definitions can differ. A useful model explains those differences.
Make the next connection.
What could work better, together?
Tell us where your operations are today. We’ll help you see what comes next.