The new Data Insights Agent in Adobe Customer Journey Analytics helps teams move from building dashboards to interpreting insights. By using natural-language prompts, it speeds up reporting, lowers the learning curve, and encourages broader adoption. After beta testing, we’ve seen how it sparks better questions, faster answers, and more confident data-driven decisions.
In most organizations, Adobe Customer Journey Analytics (CJA) is used by a wide range of people—from beginners just getting started with Workspace to experienced analysts who run weekly business reviews. Supporting all of them can be a challenge, especially when teams are under pressure to move faster and do more with data.
That’s why the release of the Data Insights Agent is such a promising development. The assistant is already proving helpful in several ways:
- It guides users of all experience levels through natural-language interactions
- It reduces the time spent building dashboards and reports
- It generates quick, directional insights to explore further
- And it encourages broader adoption of CJA by lowering the learning curve
What’s most exciting is how the assistant shifts the workflow—from time spent building dashboards to time spent interpreting insights. And because it works across connected journey data—not just web analytics—it helps teams unlock richer, more actionable understanding.
How we got started with the Data Insights Agent
We had the opportunity to be part of the beta testing program for the Data Insights Agent, working closely with Adobe’s product team before the feature was generally available. This early access allowed us to test a wide variety of prompts, explore its behavior in different reporting contexts, and provide direct feedback that helped shape the feature.
During testing, we focused on real-world business questions—like which products were driving high conversion, or how different audiences behaved across their journey—not just technical queries. We also explored how well the assistant handled requests for things like metric definitions, visualizations, and follow-up questions. This phase gave us an early understanding of where the AI excels, and where human interpretation is still essential.
Now that the assistant is live in production, we’ve begun integrating it into our CJA user training sessions, especially as part of onboarding new users. We include a live walkthrough of the AI Assistant so users can see how it works and start asking their own questions right away. The interest has been strong—even among users who are still new to CJA. We see it as a bridge that helps more people engage with data faster and more confidently.
What’s working – Tips for new users
Here are a few lessons learned that helped teams get more value from the Data Insights Agent:
- Start with real questions, not keywords.
Begin with real business questions like “Which sources drive the highest conversions?” or “What are the top exit pages?” This keeps the assistant useful and grounded in actual decisions. - Use it to reduce dashboard setup time.
Instead of building every table manually, use prompts like “Sessions by country over the last 30 days.” The assistant quickly builds visualizations, saving analysts time to focus on interpreting results. - Let it help with definitions and charts.
Users often ask, “What’s the difference between people and sessions?” or “How do I make a line chart?” The assistant handles these efficiently, making it great for onboarding and product adoption.
These small habits help teams build confidence, move faster, and get more value from Customer Journey Analytics—especially as the assistant continues to evolve.
Lessons learned & surprising moments
One interesting discovery: the assistant doesn’t just answer your question—it sometimes helps expand your thinking. For example, when asking “Which source drives the highest conversions?”, it may respond with clarifying prompts like:
- “Which product drives the highest conversions?”
- “Which cart source contributes most?”
- “Which URL or version performs best?”
This opens up new angles that teams might not have considered initially.
Another benefit: the assistant becomes a reliable fallback during working sessions. Instead of waiting for an analyst to explain a term or help build a view, users can get instant support—keeping discussions flowing without delay.
These moments, while small, build momentum and increase usage over time.
Looking ahead
In the coming Quarters, the goal is to more deeply integrate the AI Assistant into everyday workflows—especially during dashboard creation, business reviews, and ad-hoc analysis. By sharing feedback with Adobe, we’re confident the assistant improves quickly and become even more useful.
The long-term vision is clear: less time spent wrangling charts and metrics, more time focused on meaningful insights. And with CJA’s ability to surface connected customer journeys—not just channel-based snapshots—the potential impact is significant.