Technology - Intelligence Dashboard Planning

Overview of Pride Intelligence Dashboard project scope, data audit findings, technology stack decisions, and implementation priorities.

Strategic Objective

Live web dashboard combining 8 years of venue data with trends to support daily decision-making

Target users: Venue owner (Mat) requiring event P&L reports, weekly P&L, and cash forecasts

Critical Business Needs

Three deliverables that don’t exist today:

1. Event P&L reports — revenue and costs per event
2. Weekly P&L summary — rollup of daily/event P&L
3. Cash forecasts — visibility of cash position trends

Data Sources Audit (Assessed 25 March 2026)

High-Value Sources Ready for Dashboard

Square POS (since ~2018):

• Status: Production, actively used
• Data: Sales by item, category, register, channel; multi-location sales; tab and ticket data
• Export: CSV/PDF reports available
• Issues: Stock tracking inaccurate (staff type amounts); no staff-level sales attribution
• Dashboard value: CRITICAL for revenue tracking, spend per head, product mix, day-of-week trends

TryBooking (since 2018 — 8 years):

• Status: Production, underutilised for reporting
• Data: Ticket sales, customer emails, event attendance records, promo code usage, ticket tier performance, package upsells
• Export: Built-in reporting features; email export to PinTuna confirmed
• Issues: CRITICAL GAP — attendance lists printed and discarded. Actual attendance vs tickets sold not tracked digitally.
• Dashboard value: CRITICAL for event-level revenue, attendance patterns, customer acquisition metrics, 8-year historical decision support

Xero (since inception):

• Status: Production, but data quality concerns
• Data: Chart of accounts, P&L, Balance Sheet, payroll, invoices, bank transactions
• Export: CSV, PDF reports; API available
• Issues: “Not trusted” by stakeholders; bookkeeper departed Nov 2025; data likely contains errors
• Dashboard value: HIGH (pending cleanup) for weekly cost tracking, labour ratios, supplier spend, cash flow visibility
• Prerequisite: Data cleanup and bookkeeper support required before deployment

Supporting Sources

Deputy (rostering and time tracking):

• Status: Production, manual processes downstream
• Data: Staff rosters, clock-in/out times, shift data
• Export: CSV export (confirmation needed)
• Issues: Shifts not closed same day; manual transfer to Xero
• Dashboard value: MEDIUM for labour hours per event, staff utilisation, labour cost integration

PinTuna (loyalty and membership):

• Status: Production, underutilised
• Data: Shareholder records, membership data, loyalty participants, digital wallet data
• Export: Unknown (requires investigation)
• Dashboard value: MEDIUM for customer segmentation, loyalty usage, repeat visit patterns, email marketing targets

Instagram/Meta Business Suite:

• Status: Active marketing channel
• Data: Follower metrics, engagement, post performance, ad spend, content scheduling
• Export: Meta Business Suite built-in analytics
• Dashboard value: MEDIUM for marketing spend vs ticket sales correlation, content performance, audience demographics

Google Business Profile:

• Status: Active, passively maintained
• Data: Customer reviews (4.7 rating, 100+ reviews), search impressions, customer actions
• Export: Google Business Profile Insights
• Dashboard value: LOW–MEDIUM for reputation tracking, local search visibility, review trends

Key Data Loss Risks

TryBooking attendance scanning: Tickets printed and attendance data discarded. Implementing digital scanning would immediately unlock years of lost insights and enable real-time attendance tracking going forward.

Xero data integrity: Bookkeeper departure created governance gap. Data cleanup required before trustworthy financial dashboards can be deployed.

Technology Stack Decision: Next.js + Supabase + Railway

Architecture:

• Framework: Next.js 16 (App Router, React Server Components, Server Actions, React 19)
• Database + Auth + Storage: Supabase (PostgreSQL, Google OAuth, Row Level Security, file storage, real-time subscriptions)
• Hosting: Railway (app server) + Supabase Cloud (database, auth, storage)
• ORM: Prisma (type-safe database access, migrations, schema management)
• Styling: Tailwind CSS
• Charts: Chart.js or Recharts
• Background jobs: Railway cron jobs (scheduled data pulls)
• AI API: Anthropic API (for email triage, event discovery, regulatory monitoring)

Rationale:

• Supabase bundles auth, database, storage, and real-time (eliminates 4 separate services)
• Google OAuth built into Supabase auth (team already uses Google Workspace)
• Row Level Security means data access rules live in database (not scattered across API routes)
• Next.js is the framework Claude Code knows best (fewer hallucinations, more working code)
• Server Actions simplify form handling (venue operations CRUD)
• Railway handles background jobs natively; generous free tier alternatives available
• Cost estimate: $10–30/month

Implementation Priorities

Phase	Focus	Data sources	Timeline
Phase 1	Revenue and attendance baseline	Square POS, TryBooking	Weeks 1–2
Phase 2	Financial performance	Xero (post-cleanup)	Weeks 3–4
Phase 3	Labour and customer insights	Deputy, PinTuna, Instagram	Weeks 5–6
Phase 4	Decision support	Integrated analysis across all	Weeks 7+

Data Source Readiness Assessment

Source	Ready for Dashboard	Prerequisite Work
Square POS	✓ Yes	None (export capability confirmation)
TryBooking	✗ Partial	Explore reporting features; implement attendance scanning
Xero	✗ No	Data cleanup; bookkeeper support
Deputy	✓ Mostly	Export capability confirmation; Xero integration planning
PinTuna	? Unknown	Confirm export capability
Instagram/Meta	✓ Yes	None
Google Business	✓ Yes	None

Key Success Metrics

• Dashboard deployed and running within 2 weeks
• Event P&L available within 24 hours of event close
• Weekly P&L shared with leadership every Monday
• Historical data (8 years) queryable for trend analysis and decision support

Next Steps

1. Confirm export capabilities for Square, Deputy, PinTuna
2. Engage bookkeeper to assess Xero data cleanup scope
3. Investigate TryBooking reporting features in detail
4. Design and pilot attendance scanning process
5. Map data integration strategy (manual, API, ETL)
6. Build Phase 1 prototype with Square + TryBooking

Related Pages

• Humphrey Intelligence App — dashboard entity page
• Data Integration Architecture — detailed ETL and data pipeline
• Automation Opportunities — systems automation priorities