Customer Journey Analytics · Data views
Same data, different reports
Laura arrives through paid search, returns through an email link and buys later. Sales sees one purchase. Marketing compares conversion and channels. Change how the same events are read and see why their reports can differ.
Example assumptions
Example: one person, six events and a €120 purchase. No stitching, filters or extra session rules. Session persistence; No Value does not overwrite. Person attribution over 09:00–10:10, one dimension. Not a full CJA replica.
The reading changes; the purchase does not
Reference versus your settings
A stays fixed. B uses your controls. The rate is purchasing sessions divided by sessions, not people who purchase.
Evidence behind the calculation
The same events from Laura
The channel is collected only on the two campaign touchpoints. An empty value does not mean direct traffic. Times are from the same morning.
The recommendation
Agree what the report measures before comparing numbers
A data view defines a reading of the data. Two configurations can answer different questions without Laura's behaviour changing.
- 01
Set the session definition
The gap between events determines whether the purchase falls in a new session. Document the timeout and any other session-start rules before comparing rates.
- 02
Separate missing values from persistence
Without persistence, the channel applies only to its own event. With persistence, an earlier value can accompany the purchase. The original event is not rewritten.
- 03
Name the model and window
In this single-dimension report, explicit attribution overrides its allocation. We use person scope and the displayed reporting window. Do not extend this calculation to multi-dimension reports.
- 04
Do not confuse credit with impact
Splitting revenue across channels does not establish which one caused the purchase. Attribution describes a model; estimating incremental impact needs a different comparison.
Explore this decision
- Fix the data or fix the report?
A misclassified channel can be fixed at source, during ingestion or in CJA. Compare who receives the correction and what happens to historical data.
- The purchase is in AEP. Where does it go missing in CJA?
Trace a purchase missing from CJA through the dataset, connection, historical import, data view and filters before loading the data again.