Performance visibility
DChat analytics help you understand workload, responsiveness, and customer satisfaction while keeping reports tied to your own deployment. Review trends for operators, departments, and sessions without relying on a hosted reporting product that bills you again for your own data.
See which operators are carrying the heaviest load and where staffing or routing needs attention.
Track chat patterns by hour and identify spikes so your team can plan coverage with more confidence.
Review how customers rate sessions and use that signal to improve coaching, scripts, and escalation paths.
Get a fast view of the team state, current session load, and recent support activity from the same admin workspace used to run the system.
The Web Forms edition has a Reports page for any date range: chat volume by day, chats and messages per agent, missed chats, and the one-to-five satisfaction breakdown, all exportable as CSV. The ASP.NET Core dashboard shows live counts and the satisfaction summary, and exports sessions and missed chats as CSV for your own reporting tools.
Reporting is only useful if it changes a staffing or coaching decision. These are the questions DChat reporting is built to answer, all from data held in your own database.
A conversation-volume trend over the window you choose, plus a busy-hours heatmap across the days of the week. Together they show whether your shift pattern matches when customers actually arrive, rather than when it is convenient to staff.
An agent leaderboard with session counts and average first-response time, so you can see both who is handling the most conversations and who is keeping people waiting - which are not always the same person.
Post-chat ratings roll up into an average, a full one-to-five distribution, and the most recent written comments. The distribution matters: an average of four looks healthy right up until you notice it is made of fives and ones.
An optional first-response SLA shows conversations met, at risk and breached, with an attainment rate. It respects your configured operating hours, so time when you were legitimately closed never counts against the target.
Agents currently online, sessions active in the last five minutes, and visitors waiting unassigned - so a supervisor can see support pressure at a glance rather than reconstructing it later.
Yes. The agent leaderboard reports session counts alongside an average first-response time, measured from when the conversation began to the agent's first reply.
Visitors can rate a conversation when it ends. The dashboard shows the average score, the full one-to-five star distribution so an average of four does not hide a cluster of ones, and the most recent written comments.
Yes. Sessions, missed chats and the audit log all export as CSV with correct RFC-4180 escaping, so a comma or quote in a visitor message cannot break a column. Because the data sits in your own SQL Server you can also query the tables directly.
In your own database on your own server. There is no hosted reporting product in between and no per-seat analytics upsell - the reports read the same tables your conversations are written to.
DChat gives you the installable server, web dashboard, website widget, and desktop agent tools in one self-hosted product, with live chat free to run, and an AI agent that answers, acts with the approvals you set and hands off to your team when you want one. Run it on infrastructure you trust, on the model you choose.
Deployment
Install on Windows or Linux, behind IIS or Nginx, in a VM, or in Docker if that fits your stack.
Commercial model
Live chat is free with unlimited agents. Premium, with the AI agent, is billed per agent per month, never per conversation.
AI Flexibility
Run the AI agent on a local Ollama model, or connect OpenAI and Anthropic with your own provider accounts.