How do I gain insights from trading platform data?

Upload your help articles, trading guides, and API docs to Chatref, and its AI agent becomes an expert on your platform. The agent resolves common queries about order types, margin calculations, and data analysis tools automatically, in your brand voice. Every chat is logged, building a rich dataset of user intent that feeds directly into the insights engine.

Chatref's insights feature mines all conversations to surface trading platform insights automatically. No manual tagging required. You'll see which data analysis questions repeat most - like how to backtest a strategy or interpret chart patterns - and which performance metrics traders ask about, from win rate to risk-adjusted returns. This helps you identify gaps in your documentation and training materials.

With insights highlighting customer behavior trends, you can refine your trading platform. If users consistently ask about a specific feature path, you might streamline that workflow. Frequent questions about a particular metric signal the need for a new dashboard widget. Chatref's digest emails keep you updated, so you're always optimizing based on real interaction data.

How do I analyze trading data for insights?
With Chatref, you don't need to manually sift through logs. After your AI agent engages with users, the insights tool categorizes conversations automatically, highlighting trending data analysis questions, favored asset classes, and technical hurdles. You get digest emails summarizing patterns, freeing you to make data-driven improvements.

What performance metrics are available?
Chatref insights shows you which trading metrics users care about most - profit/loss, win rate, Sharpe ratio, maximum drawdown, and more. You'll see aggregate conversation volumes around each metric, helping you understand what traders need to evaluate their own performance.

Can I track customer behavior on the platform?
Yes. Every chat is recorded, so Chatref reveals how customers interact with your platform through their questions. You'll learn which features they explore, where they encounter friction, and when they seek help, giving you a clear picture of behavior patterns to guide UX and documentation updates.