--- title: Post Lab Resources slug: multi-customer-cja-hol-apr-2026 docTags: createdAt: 2024-01-23T00:00:22.306Z --- # Feedback Survey **[https://forms.office.com/r/C3XRqN8E9Z](https://forms.office.com/r/C3XRqN8E9Z)** ::Image[]{src="https://api.archbee.com/api/optimize/1Jp0iolWv35Z_mkI7oUiT/ThFmINZ81Mfk6mgNjqcHh-20260402-193301.jpg" size="20" width="279" height="278" position="flex-start" showCaption="false"} # HOL Presentation ::File{src="https://api.archbee.com/api/presign/1Jp0iolWv35Z_mkI7oUiT/v6cgjxGzHCJT3T8Aff08z-20260408-203146.pdf" label="Multi-Customer CJA HOL - Apr 2026.pdf"} # HOL Recording ::embed[]{url="https://vimeo.com/1181986568"} # Completed Workspace ::File{src="https://api.archbee.com/api/presign/1Jp0iolWv35Z_mkI7oUiT/z8D8REVypnSLoLqPzgVrc-20260407-221202.pdf" label="Multi-Customer HOL - April 2026 (Complete).pdf"} # Resources - [Customer Journey Analytics Resource Guide](https://experienceleague.adobe.com/en/docs/analytics-platform/using/cja-landing) - [Data Ingestion Priority and Latency](https://experienceleague.adobe.com/en/docs/analytics-platform/using/cja-data-ingestion/data-ingestion#ingestion-prioritization-and-latency) - [Stitching: Graph or Field Based](https://experienceleague.adobe.com/en/docs/analytics-platform/using/stitching/overview) - [Data ingest overview](https://experienceleague.adobe.com/en/docs/analytics-platform/using/cja-data-ingestion/data-ingestion) - [AA to CJA Migration](https://experienceleague.adobe.com/en/docs/analytics-platform/using/compare-aa-cja/upgrade-to-cja/cja-upgrade-recommendations) # Q\&A ## Identity, Stitching, and Customer Identification ### Q: Are changes in Customer Journey Analytics retroactive? *A: Yes. Changes made in Data Views are retroactive and non-destructive. Historical data does not need to be re-ingested; changes are applied at report time and do not alter the underlying data stored in Adobe Experience Platform.* *[Adobe Experience League Reference](https://experienceleague.adobe.com/en/docs/analytics-platform/using/cja-dataviews/data-views)* ### Q: What is the difference between anonymous and known identifiers? *A: Anonymous identifiers include ECID, cookies, or device IDs prior to authentication. Known identifiers include email, CRM ID, or loyalty ID after login. Identity stitching connects these to enable person-level analysis.* *[Adobe Experience League Reference](https://experienceleague.adobe.com/en/docs/analytics-platform/using/stitching/overview)* ### Q: How is identity stitching in CJA different from Real-Time CDP stitching? *A: CJA stitching supports cross-channel analysis for reporting, while Real-Time CDP primarily uses stitching for activation. CJA supports field-based and graph-based stitching.* ### Q: Does CJA create a new customer ID? *A: No. Customer Journey Analytics does not generate new IDs; it uses existing identifiers already present in your datasets.* ## Data Views and Reporting ### Q: Can one panel use multiple Data Views? *A: No. Each Analysis Workspace panel supports only one Data View, though multiple panels can be used side-by-side.* ### Q: Should transformations be done at ingestion or in Data Views? *A: Best practice is clean ingestion, but Data Views and Derived Fields allow non-destructive report-time transformations when upstream changes are not feasible.* ## Attribution and Marketing Measurement ### Q: Why does revenue initially show as zero? *A: Revenue often occurs after marketing dimensions are set. Attribution models are required to associate downstream success events with upstream touchpoints.* ### Q: What attribution models are available? *A: CJA supports First Touch, Last Touch, Linear, Participation, Same Touch, and Algorithmic Attribution with configurable containers and lookback windows.* [Adobe Experience League Reference](https://experienceleague.adobe.com/en/docs/analytics-platform/using/cja-workspace/attribution/overview)** ## Experimentation Panel ### Q: Can we calculate incremental lift between experiment variants? *A: The Experimentation Panel computes lift for each variant relative to the single control you specify. It does not automatically compute “Variant B vs Variant C” lift directly. Variant‑to‑variant comparisons require either re‑defining the control or building a calculated metric.* *If you need lift of Variant B relative to Variant C (where neither is the designated control), you have two options:* 1. * Re‑run the panel with a different control* - *Set C as the control once, then B as the control, to get each one’s lift vs the other.* - *This is simple but requires a couple of panel runs.* 2. *Use calculated metrics with the Lift function* - *The Experimentation feature exposes Lift as an advanced calculated metric function, where you can specify experiment, control variant, success metric, and normalizing metric * - *You can define a calc metric that:* - *Picks one variant as “control” for the purpose of the formula, or* - *Derives a ratio between two non‑control variants’ conversion rates using standard calc‑metric arithmetic (since conversion rates per variant are available).* *If you want to add a view of incremental **counts** (additional revenue $, additional application #, etc.) you can add a calculated metric from the Experimentation Panel. Create a metric from Lift that simply multiplies its value by your success event. * *In this example, the success metric of Product Views applies to the current view of Lift, so we multiply the percentage of lift by the Product Views metric. * *(Note: this method is specific to the produced Lift and Experimentation Panel setup, so a new calculated metric is required for each panel build).* ![](https://api.archbee.com/api/optimize/1Jp0iolWv35Z_mkI7oUiT/v5pA5ZDZFCn9MqLrrvWcQ-20260413-171825.png) ::Image[**]{src="https://api.archbee.com/api/optimize/1Jp0iolWv35Z_mkI7oUiT/VWSDBa48YYeiSPyHQMfs4-20260413-171825.png" size="36" width="233" height="503" position="center" showCaption="false"} ![](https://api.archbee.com/api/optimize/1Jp0iolWv35Z_mkI7oUiT/h-gJTfoF1UgCU05VuhbkH-20260413-171825.png) [Adobe Experience League Reference](https://experienceleague.adobe.com/en/docs/analytics-platform/using/cja-workspace/panels/experimentation) ## AI Assistant and Guided Analysis ### Q: What can the AI Assistant do? *A: The AI Assistant can answer product questions, troubleshoot issues, generate visualizations, and provide intelligent captions based on Experience League documentation.* ### Q: What is Guided Analysis? *A: Guided Analysis provides preconfigured workflows such as funnels, retention, and release impact for fast, self-service insights.* [Adobe Experience League Reference](https://experienceleague.adobe.com/en/docs/analytics-platform/using/guided-analysis/overview)** ## Audiences and Activation ### Q: Can audiences be created from CJA analysis? *A: Yes. Audiences can be created directly from CJA tables, flows, and journeys and published to Adobe Experience Platform for activation.*