CX Enterprise Coworker
7 min
Overview
Adobe CX Enterprise Coworker is an AI-powered teammate that reimagines the nature of work for organizations, teams, and individuals. Coworker elegantly automates customer experience and marketing workflows so organizations can focus on realizing their business goals and transforming outcomes, not coordinating tasks. As an agentic engine, Coworker takes a new innovative approach to automating business process. It elevates AI model performance and accuracy by bringing together data, intelligence, collaboration and agentic skills execution with enterprise context, governance, and human oversight built in.
Key Benefits for Analysis in Coworker Chat
- Less time building reports: It creates visualizations in Analysis Workspace from your data view components and your real data, so you don't build each table and chart by hand.
- Easier to learn: You don't need to know where every dimension and metric lives, which helps beginners and people who use CJA occasionally.
- More people can use the data: Marketers and business stakeholders can get quick, directional answers themselves, so analysts have more time for strategic work.
- Time goes to interpreting: The work moves from building dashboards to understanding what the numbers mean.
- Covers all your channels: It works on connected customer journey data, not just web analytics.
- Follow-up questions: You can chain prompts to narrow in on a finding, such as summarize, then compare, then break down.
Sample Chat Prompts
- General
- What can you help me with?
- What kind of analysis questions can I ask for CJA?
- Product Knowledge
- How is CJA different than AA?
- What are the guardrails and limits for CJA connections and data views?
- When was the latest release of CJA and what were the updates?
- What is real-time reporting in CJA and how do I enable it?
- What is the difference between field based and graph based stitching in CJA?
- How does the Target integration work in CJA?
- Analysis
- Trend events listing first and last date of events recorded.
- Now break down by channels
- What marketing channels are most effective at converting orders in the last 90 days
- What web pages triggered the most call center calls in June 2026?
- Now what I can do to reduce the calls to the call center?
- What were the top products by loyalty tiers?
- Root Cause Analysis
- Were there any anomalies across channels for the last 6 months across people, events, orders and revenue?
- Investigate the cause of the February Orders spike
- What caused the People drop on between May 9 and 10?
Skill File Download
Documentation
- Overview
- Chat