Current-State Analytics: Provides a data-driven snapshot of how customers have interacted with your journeys based on historical data from your live environment. It helps teams uncover actual behavior identifying common paths, drop-offs, and friction points, so they can improve experiences using evidence rather than assumptions. By grounding journey design in real-world data, Current-State Analytics supports faster optimization, smarter decisions, and better alignment across teams.
This release introduces a Current-State Analytics that allows teams to ingest historical, transactional, and event-based data into Xponent. Users map the incoming data to existing Journey Steps, Interactions, Identifiers, or define new ones if the data reveals previously unknown milestones or patterns. Once mapping is submitted without errors, the system acknowledges the setup and begins transforming the data in the background typically completing within an hour, even for large datasets.
A key enhancement is the automatic generation of Journey Steps and Interactions based on the mapped data. This reduces manual setup and ensures consistency across projects. Business users benefit from faster time-to-insight, as the foundational components of journey orchestration are now created for them based on real, production-sourced behavior.
The submitted data flows directly into the Journey Discovery Analytics dashboard. Once processing is complete, users can explore it through familiar visualizations like the sankey diagram to analyze how customers progressed through their journeys. Teams can pinpoint high-friction areas, observe behavior across segments, and understand the most common user paths based entirely on data drawn from real interactions.
For added flexibility, teams working in non-production environments can now replace previously ingested data from the profile store. This allows them to restart the Current-State Analytics workflow with new or corrected datasets especially useful for testing and iteration. Together, these updates bridge the gap between historical data and journey orchestration, enabling evidence-based design with greater speed and confidence.