feat(storm-intel): Phase 3 — Revenue Attribution dashboard

Adds an Attribution tab to Storm Intel showing full ROI breakdown of storm-sourced canvassing. - MOCK_STORM_ATTRIBUTION_LEADS: 35 realistic leads across 7 storms, with addresses, statuses (New / Contacted / Appointed / Closed) and contractValues for closed deals — $218,900 total revenue - useStormAttribution hook: merges historical mock leads with any session-created storm leads, aggregates per-storm stats (leads, closed, conversion rate, revenue, pipeline estimate, avg deal size) - Attribution tab in StormIntelPage: - 6 summary stat cards: Total Leads, Closed, Conversion Rate, Revenue, Pipeline, Avg Deal - Grouped bar chart (Recharts) — leads generated vs closed per storm, bars colored by severity - Per-storm revenue cards ranked by revenue: severity badge, stats row, animated revenue progress bar relative to top performer - "Top Performing Zone" insight card at bottom - Tab switcher (Map / Attribution) added to header; filter bar only shows on Map tab
2026-05-18 17:16:34 +05:30
parent 4cface49da
commit df50f27ba6
3 changed files with 387 additions and 15 deletions
@@ -0,0 +1,79 @@
+/**
+ * Aggregates storm-sourced leads into per-storm revenue attribution stats.
+ *
+ * Merges MOCK_STORM_ATTRIBUTION_LEADS (historical) with any live storm leads
+ * created in the current session via the Storm Intel → Create Lead flow.
+ *
+ * Returns summary + per-storm breakdown sorted by revenue descending.
+ */
+
+import { useMemo } from 'react';
+import { MOCK_STORM_ATTRIBUTION_LEADS } from '../data/mockStore';
+
+// Estimated average pipeline value for an Appointed (not yet closed) lead
+const AVG_PIPELINE_VALUE = 17500;
+
+export function useStormAttribution(events = [], sessionLeads = []) {
+    return useMemo(() => {
+        // Merge: mock historical leads + any new storm leads from this session
+        const mockIds = new Set(MOCK_STORM_ATTRIBUTION_LEADS.map(l => l.id));
+        const newSessionLeads = sessionLeads.filter(l => l.stormSource && !mockIds.has(l.id));
+        const allLeads = [...MOCK_STORM_ATTRIBUTION_LEADS, ...newSessionLeads];
+
+        // Build a quick lookup of storm metadata from the events array
+        const stormMeta = Object.fromEntries(events.map(e => [e.id, e]));
+
+        // Aggregate per storm
+        const buckets = {};
+        allLeads.forEach(lead => {
+            const sid = lead.stormSource?.id;
+            if (!sid) return;
+            if (!buckets[sid]) {
+                buckets[sid] = { leads: [], closed: [], appointed: [], contacted: [] };
+            }
+            buckets[sid].leads.push(lead);
+            if (lead.status === 'Closed')    buckets[sid].closed.push(lead);
+            if (lead.status === 'Appointed') buckets[sid].appointed.push(lead);
+            if (lead.status === 'Contacted') buckets[sid].contacted.push(lead);
+        });
+
+        const perStorm = Object.entries(buckets).map(([sid, b]) => {
+            const storm = stormMeta[sid] ?? b.leads[0]?.stormSource ?? { id: sid };
+            const revenue = b.closed.reduce((s, l) => s + (l.contractValue ?? 0), 0);
+            const pipeline = b.appointed.length * AVG_PIPELINE_VALUE;
+            const conversionRate = b.leads.length > 0
+                ? Math.round((b.closed.length / b.leads.length) * 100)
+                : 0;
+            const revenuePerLead = b.leads.length > 0
+                ? Math.round(revenue / b.leads.length)
+                : 0;
+
+            return {
+                storm,
+                leadsCount:      b.leads.length,
+                closedCount:     b.closed.length,
+                appointedCount:  b.appointed.length,
+                contactedCount:  b.contacted.length,
+                revenue,
+                pipeline,
+                conversionRate,
+                revenuePerLead,
+            };
+        }).sort((a, b) => b.revenue - a.revenue);
+
+        // Overall summary
+        const totalLeads     = allLeads.length;
+        const closedLeads    = allLeads.filter(l => l.status === 'Closed').length;
+        const appointedLeads = allLeads.filter(l => l.status === 'Appointed').length;
+        const totalRevenue   = allLeads.reduce((s, l) => s + (l.contractValue ?? 0), 0);
+        const pipelineValue  = appointedLeads * AVG_PIPELINE_VALUE;
+        const conversionRate = totalLeads > 0 ? Math.round((closedLeads / totalLeads) * 100) : 0;
+        const avgDealSize    = closedLeads > 0 ? Math.round(totalRevenue / closedLeads) : 0;
+
+        return {
+            summary: { totalLeads, closedLeads, conversionRate, totalRevenue, pipelineValue, avgDealSize },
+            perStorm,
+            allLeads,
+        };
+    }, [events, sessionLeads]);
+}