Adobe CJA Business Practitioner Pro cheat sheet

CJA connections accept only Experience Platform event datasets; profile and lookup datasets cannot be enabled for CJA reporting.

Every CJA event dataset requires an event timestamp and a person identifier (identity map or ECID) for reporting and stitching.

A connection is scoped to one Experience Platform sandbox and can include multiple datasets; data views select which datasets and fields are exposed.

Data Prep field mappings are applied before CJA ingestion and are dataset-level, so they affect every data view using that dataset.

CJA retains event data for 25 months; dataset retention settings in Experience Platform do not extend CJA retention.

Cross-device stitching uses the person ID with a 25-month lookback and periodic replay of data as identities resolve.

Streaming ingestion via Web SDK, Mobile SDK, or HTTP API makes data available in CJA after pipeline processing; batch cloud-source data follows connector schedules.

A data view defines session timeout (default 30 minutes), attribution defaults, and which components users can see.

Component curation (hide, rename, describe) changes the data view presentation, not the underlying XDM schema fields or data.

Component IDs are stable; renaming a dimension or metric does not break saved Workspace projects that reference it.

Data views can include multiple datasets from the connection and exclude datasets that should not appear in reporting.

Metric attribution settings in the data view set the default model and lookback; Workspace panels can override them.

Derived fields and calculated metrics are created at the data view or component level and become reusable components.

Schema changes in Experience Platform should trigger a data view review to confirm mapped components remain valid.

A freeform table breaks down metrics by dimensions; each breakdown applies the panel's date range, segment, and attribution context.

Panel types include freeform, attribution, fallout, flow, cohort, and experiment; the panel type determines available visualizations.

Fallout reports require an ordered sequence and show progression and drop-off between steps.

Cohort tables group people by a first-event date and track retention or metric values in later periods.

Anomaly detection flags values outside a statistical expected range; it uses the selected granularity and training period.

Date comparisons show current versus prior period; percentage change = (current - prior) / prior × 100.

Scheduled projects and data extracts deliver Workspace output on a recurring basis to specified recipients or cloud destinations.

Segment containers are event, session, and person; choose event for single-hit criteria, session for within-visit criteria, and person for cross-visit criteria.

Sequential segments use Then logic; the order of conditions matters and is evaluated within the selected container.

Exclusion in a segment removes matching people, sessions, or events depending on the container used.

Calculated metrics combine metrics, numbers, and functions; they cannot directly use dimensions.

A segment can be applied at the panel, table, or metric level; stacking segments intersects their populations.

CJA audiences are person-level populations published to Experience Platform for activation in Real-Time CDP destinations.

Audience membership updates as new data arrives; activation latency depends on the destination and platform processing.

Attribution models include Last Touch, First Touch, Linear, Participation, Same Touch, U-shaped, J-shaped, Time Decay, and Custom.

Last Touch gives 100% credit to the final touchpoint; First Touch gives 100% to the first touchpoint.

Linear splits credit equally across all touchpoints in the lookback window; Participation gives full credit to each touchpoint.

The lookback window limits which touchpoints are eligible; touchpoints older than the window receive no credit.

Attribution can be set as a data view metric default or overridden in a Workspace attribution panel or column.

Cross-device stitching affects attribution because touchpoints are linked to the person ID, not only the device ECID.

Compare models side by side to see how credit shifts between channels before changing reporting defaults.

CJA stitches events to the selected person ID from the identity map; ECID is the fallback identifier when no person ID exists.

Identity namespaces such as ECID, email, and CRM ID define identifier types and feed the Experience Platform identity graph.

Cross-device stitching uses a 25-month lookback and weekly replay to update historical events with resolved identities.

Fallout and flow visualizations analyze ordered journeys; fallout shows step drop-off, and flow shows pathing between touchpoints.

Channel classification rules or derived fields assign touchpoints to marketing channels; consistent rules are required for cross-channel comparison.

Journey analysis should align the identity namespace with the business question, such as known-customer versus anonymous journeys.

Cross-channel metrics can differ from single-channel metrics because stitching changes person-level attribution and deduplication.

Experience Platform data usage labels (contract, identity, sensitive) are enforced in CJA; labeled fields can be restricted from reporting or activation.

Privacy Service requests delete or anonymize data by identity across Experience Platform and CJA; processing is asynchronous.

Admin Console product profiles control CJA permissions, including data view access, component creation, and administrative rights.

Data view access can be limited by product profile; users see only components and data views granted to their profile.

CJA retains event data for 25 months; plan reporting and exports around that retention horizon.

Audit logs in Experience Platform and Admin Console record administrative changes for governance review.

Consent and data usage policies should be evaluated at the dataset and field level before enabling CJA reporting.

A measurement plan maps business objectives to questions, KPIs, metrics, dimensions, segments, and data sources before implementation.

A KPI tree links the North Star or primary KPI to supporting drivers so teams can see how lower-level metrics affect the outcome.

Conversion rate = conversions ÷ sessions (or visitors) × 100; specify the denominator in the KPI definition.

ROI = (revenue - cost) ÷ cost × 100; use consistent time periods and include all relevant costs.

Funnel analysis measures step-to-step conversion; step conversion = step completions ÷ previous step entrants × 100.

Segment-level KPI comparisons reveal whether aggregate changes come from mix shifts or within-segment performance.

Executive communication should state the decision, the evidence, the confidence level, and the recommended next action.