Key takeaways

In this module, you learned:

• The Quick Insights panel provides a guided path for analysts who are newer to Analysis Workspace. Rather than requiring drag-and-drop familiarity, Quick Insights offers a form-based workflow where you select a dimension, metric, and filter, and it automatically builds the table and visualization for you. It's designed to lower the barrier to entry while still producing meaningful output.
• Calculated metrics like "orders divided by people" enable fair comparison across segments of different sizes. Raw order counts alone can be misleading — a channel with more visitors will naturally have more orders. Dividing orders by unique people gives you a conversion rate that normalizes for audience size, revealing which channel or segment is actually more effective at turning people into customers.
• Intelligent captions automatically surface the narrative behind a line chart. Rather than having to interpret a visualization yourself, this AI-powered feature reads the data and generates written summaries of key trends, peaks, anomalies, and patterns. It's particularly useful for quickly communicating findings to stakeholders who may not want to stare at a chart.
• A function line in a combo visualization adds a statistical reference point to a bar chart. Overlaying a median or mean line lets you instantly see which individual data points — such as orders by city — fall above or below the central tendency of the dataset. This makes outliers and high performers visually obvious without needing a separate calculation.
• Persistence settings in a data view control which touchpoint gets attribution credit. A dimension configured without persistence only reflects the current event. When persistence is applied, you can configure first-touch attribution (credit goes to the first interaction), last-touch attribution (credit goes to the most recent), or other models. The same channel data can tell a very different story depending on which model is applied — which is why comparing them side by side is a meaningful analytical exercise.