Dashboard KPI Overview

Summary

This article explains how to interpret each primary KPI card on the dashboard and how to avoid false conclusions when values change quickly. For operators, this page should be used as a decision surface, not only as a UI form. Always pair page actions with downstream validation in the relevant live workflow.

What this page is for

• Understand what each top KPI represents in day-to-day operations.
• Detect whether a performance change is monetization, conversion, or traffic related.
• Create a shared reading standard across operators.

Before you start

• Use a date range that includes real sales and conversations.
• Confirm the selected bot scope in the header filter.
• Avoid comparing cards from different filters without noting context.

Step-by-step workflow

1. Open /dashboard and verify the selected date range.
2. Read Stars Earnings first to check absolute monetization.
3. Read Avg Stars / Sale to understand purchase quality per transaction.
4. Read Chat Conversion to assess reply-to-sale efficiency.
5. Read AI Conversations to validate message volume pressure.
6. Cross-check all four values before changing scripts or persona.

Key states and error handling

• Cards show '...' while summary APIs are loading.
• Values can look flat if the selected period is too narrow.
• A spike in revenue with flat conversion often means order size shift, not funnel improvement.

Best practices

• Review KPIs in the same order every day to spot anomalies faster.
• Log KPI snapshots before and after major configuration changes.
• Treat conversion and conversation volume together, not separately.

Troubleshooting

• If all values are zero, verify date range and bot filter first.
• If KPIs look outdated, refresh after bot sync and wait for data propagation.
• If conversion drops suddenly, inspect Fan Inbox quality and script transitions.
• If issue persists after one clean retry, capture exact toast/banner text, selected bot, and timestamp before escalation.

UI reference (what each control does)

• Date range picker controls all KPI cards, the pulse chart, and recent sales together.
• Bot scope selector switches from aggregated view (All bots) to single-bot diagnostics.
• Stars Earnings card displays stars and an approximate USD conversion in the selected range.
• Avg Stars / Sale is a per-transaction quality metric, not a traffic metric.
• Chat Conversion is shown as AI replies vs sales ratio and must be read with volume context.
• AI Conversations card uses a rolling window, so it can move independently from revenue cards.
• Telegram Stars Pulse chart reflects timeline dynamics and should be read before tactical changes.
• Recent Stars Sales panel is your recency heartbeat for monetization continuity.

Operator checklist (before shipping changes)

• Confirm date range and bot scope are documented before sharing conclusions.
• Cross-check KPI movement with chart shape and recent sales recency.
• Avoid changing scripts or pricing from one isolated spike.
• Capture a screenshot with visible filters for auditability.
• Validate one downstream signal in Fan Inbox before closing analysis.
• If data is ambiguous, widen period before escalating operational changes.

Real-world scenario

A team sees Stars drop in 24h. They verify date and bot scope, then confirm whether recent sales are truly stale or only filtered out. They compare conversion and AI conversation volume before deciding if the issue is traffic, script quality, or offer pricing.

1. Identify the exact scope (bot, period, module) before any change.
2. Apply one targeted correction based on observed UI state and messages.
3. Validate outcome in the live operational flow linked to this page.
4. Document the final state so future incidents can be solved faster.