Analytics, Reporting, and Optimization Measurement
Target reporting has two modes: Target's native reports (conversion rate, lift, confidence) and Adobe Analytics for Target (A4T), which uses Analytics as the source of truth for metrics and segments. Know the A4T architecture: the Target decision returns activity/experience identifiers, which are captured in Analytics (via mbox3rdPartyId/tnt/tntId and the A4T payload) so reports can attribute conversions.
Understand statistical concepts: confidence level, lift, sample size, and the difference between frequentist (p-value) and Bayesian (probability to beat control) reporting. Know that Auto-Allocate and Auto-Target use their own reporting views.
Traps: comparing a metric across activities when the metric definitions differ; forgetting that A4T requires the Analytics tracking server and correct trackingServer/trackingServerSecure settings; assuming Target native reports and A4T reports always match (they can diverge due to attribution windows and data collection). Also watch for questions on response tokens (e.g., activity.id, experience.id) used to pass decisions downstream.
Rule of thumb: pick one source of truth per program. If you need rich segmentation and cross-channel analysis, use A4T; if you need quick in-tool lift, native reports suffice - but don't mix them for the same decision.
Worked example: an A/B test shows +8% in Target native but +3% in A4T. Investigate attribution window and whether the conversion event fires before the Target call on the page.