PMS Report · Gemini AI · NewsAPI · Dynamic Forecast
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🏨 Hotel Analytics Intelligence Report —
🔑 API Configuration — Masukkan token Anda
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●Not tested
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●Optional
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●Not tested
Free tier available · console.groq.com
🔐 API keys auto-saved in this browser only (localStorage, encoded). Not sent to any server. Auto-loaded when you reopen the file in the same browser.
📁 Upload PMS Report (.xlsx)
📊
Upload Excel Files from PMS
Select files from one or multiple month folders. Supports 1–2 years of data. File & folder path auto-detected.
by Arrangementby Guest Typeby Nationalityby Source of Bookingby Room Categoryby Arrival Detail (w/ Departure)by Cancellation
📋 MTD Columns Read
by Arrangement.xlsx
Package / Room Type
by Guest Type.xlsx
Travel Agent / OTA
by Nationality.xlsx
Guest nationality
by Source of Booking.xlsx
OTA / Direct / Walk-in
by Room Category.xlsx
Room type per segment
by Arrival Detail.xlsx
Lead Time & LOS
by Cancellation.xlsx
Cancel volume & revenue lost
MTD: Arrangement, Guest Type, Nationality, Booking, Room Category Arrival Detail: Lead Time = Create→Arrival · LOS = Arrival→Departure · Rate > 0 only Cancellation: Channel · Reason · Lead time to cancel · Room type
Auto-detect month from filename · Supports 1–24 months
📡 Live
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📋 By Arrangement — Package & Room Type
Room nights & revenue per arrangement / package (MTD)
Arrangement
🏷️ Room Category Analysis
Performance per room type — Room Nights, Revenue & ADR (MTD)
Room Category
Room Nights by Category
All available months
ADR by Category
Comparison across types
📊 Segment Mix
Distribution by segment
Detail Segment
Segment
Rooms
Pax
Revenue
ADR
Share
Volume
📈 Trend Room Nights & Revenue
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Multi-Period
🔗 Source of Booking
Active month channel mix
🌍 Top Nationalitas
Room nights by country (top 12)
👥 Travel Agent & OTA
Room nights per guest type (top 10)
💰 ADR by Nationality
Average Daily Rate IDR (min 5 rooms)
ADR Trend
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YoY
🔮 Dynamic Forecast
6-Month Forward Projection
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AI Forecast
🤖 AI Analysis — Gemini + Data PMS Anda
✨ AI Strategic Analysis
gemini-1.5-flash
Click 🔄 Generate AI to start a deep strategic analysis of your data.
📈 Trend Market & Forecast Intelligence
AI
Market trend analysis, seasonality, and demand forecast based on your historical data + Bali market knowledge.
🎯 Promotion Strategy & Revenue Optimization
AI
Specific promo recommendations per channel, nationality, and period — with ROI estimates.
⚡ 90-Day Action Plan
AI
Concrete 90-day action plan: week by week, responsible parties, and measurable KPI targets.
📰 Latest Bali tourism news briefing — generated oleh AI berdasarkan pengetahuan market terkini
Click Generate AI for the latest Bali tourism news briefing.
💡 Data Intelligence
🗺️ Detail Nationalitas
Rooms, Pax, Revenue, ADR by country
📱 Source of Booking
Revenue & ADR by booking channel
⏱️ Lead Time & Length of Stay Analysis
Arrivals (rate>0) only · LOS = Arrival → Departure · Note: total arrivals ≠ Monthly room nights
Arrival Detail
📅 Lead Time Distribution (R/N %)
How far in advance guests book before check-in
🛏️ Length of Stay Distribution (R/N %)
Guest length of stay distribution
📈 Lead Time Trend
Booking window comparison by month
💰 ADR by Lead Time Bucket
Do early bookers pay more?
🔢 Lead Time × Length of Stay Matrix
Room nights (%) per booking window × LOS combination · color = volume
💰 ADR Matrix: Lead Time × LOS
Average ADR per combination — find the pricing sweet spot
📱 Lead Time by Channel
Booking window distribution by OTA/channel
🛏️ Length of Stay by Channel
Which channel brings the longest-staying guests?
💰 ADR by Channel × Lead Time
Which channel books earliest AND pays highest rate?
💰 ADR by Channel × LOS
Which channel stays longer AND pays more per night?
🌍 Lead Time by Nationality
When do guests from each country book?
🛏️ Length of Stay by Nationality
Which nationality stays the longest?
💰 ADR by Nationality × Lead Time
Which market books earliest AND pays highest rate?
💰 ADR by Nationality × LOS
Which market stays longer AND pays more?
🏷️ Lead Time by Room Category
Booking window by room type
🛏️ Length of Stay by Room Category
LOS by room type
💰 ADR by Room Category × Lead Time
Which room type benefits most from early booking?
⭐ Lead Time: VIP vs Regular
VIP vs regular guest booking window pattern
🛏️ Length of Stay: VIP vs Regular
Do VIP guests stay longer?
📈 Daily Arrivals & Departures
Arrivals vs departures per day
🏨 Daily In-House (Estimated)
Rooms occupied per night (from Arrival→Departure range)
💰 Daily ADR
Average room rate of arriving guests per day
⏱️ Daily Avg Lead Time & LOS
How far in advance did arriving guests book? How long did they stay?
📋 Daily Detail Table
💰 ADR by Length of Stay
Long stay vs short stay — who pays more?
📈 ADR Lead Time Trend
Do early bookers always get higher ADR?
📅 Year-over-Year Comparison
YoY
Room Nights · Revenue · ADR · Cancellations · Lead Time per month per year
📊
Upload Your PMS Data
Upload .xlsx files from PMS, or click Demo for a demo. After processing data, click 🤖 AI Analysis for deep insights.
🌍 Nationality × Channel Analysis
Room nights by nationality and booking channel · Source: Arrival Detail (rate>0 only) (rate > 0)
📅 Period:
🌍 Top Nationalities — Room Nights
Room nights by country of origin (rate > 0)
🏢 Top Channels & Travel Agents
Booking volume per channel / travel agent
🍩 Nationality Mix
Room nights share by nationality
💰 ADR by Nationality
Which market pays the highest rate?
📋 All Nationalities — Full Table
🔢 Nationality × Channel Matrix
Room nights per nationality per channel (Top 12 × Top 12) · darker = more bookings
💰 ADR Matrix — Nationality × Channel
Average rate per nationality × channel combination
🌍 Channel Mix by Nationality
Booking channels used by each nationality — one pie per country
💰 ADR by Nationality
Average rate per nationality (min 5 arrivals)
🏢 Nationality Mix by Channel/TA
Guest nationality mix per booking channel — one pie per channel/TA
💰 ADR by Channel/TA
Which channel brings the highest-paying guests?
📊 Revenue by Channel/TA
Total revenue by booking channel
📋 Channel/TA — Tabel Detail
📈 Nationality Trend by Month
Guest volume trend per nationality across months
📊 Channel Trend by Month
Booking volume per channel across months
❌ Cancellation Analysis
📡 Cancellations by Channel
Top channels by cancellation volume
❓ Cancellation Reasons
Why bookings were cancelled
⏱️ Days Before Arrival (Cancellation Lead Time)
How far in advance bookings were cancelled
🛏️ Cancellations by Room Type
Revenue lost per room category
📈 Monthly Cancellation Trend
Volume and revenue lost trend across months
📊 Channel Detail Table
Full breakdown by booking channel
⚙️ Admin Dashboard
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Total Users
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Active Sessions
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Monthly Records
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Weekly Records
👥 User Management
Manage user accounts
#
Username
Name
Hotel
Role
Status
Last Login
Aksi
Loading...
📋 Audit Log
Recent activity
Waktu
User
Aksi
Detail
IP
Loading...
📂
Drop Arrival + Cancellation files
Auto-detects all months from data · 1 file can contain 1 or 13+ months
✈️ Arrival Detail❌ Cancellation
rooms
📊
Monthly Instan
Upload Arrival + Cancellation files to begin analysis
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PERIOD
📊 Performance Overview
Room Nights Trend
Monthly occupied room nights
Revenue & ADR
Monthly revenue (bars) · ADR (line)
🏨 RevPAR & Occupancy
rooms · RevPAR = Total Revenue ÷ (Rooms × Days)
Occupancy Rate
RevPAR Trend
🌍 Nationality Analysis
Top Nationalities
Room nights by country
Nationality Trend
Top 5 countries monthly
Nationality Table
MoM & YoY
📡 Source of Booking
Booking Channels
Channel Trend
Channel Table
MoM & YoY
🍳 By Arrangement
Arrangement Mix
Arrangement Trend
Values shown on bars
🛏️ Room Category Analysis
Category Trend
ADR by Category
Channel Mix per Category
⏱️ Lead Time & LOS
🔀 Nationality × Channel
Top Nationalities
Top Channels
Nationality Trend
Channel Trend
Nat × Channel Matrix
Nationality Detail
MoM & YoY
📅 Year-over-Year Comparison
❌ Cancellation Analysis
By Channel
Cancel Reason
Lead Time to Cancel
By Room Category
Monthly Trend
Channel Detail Table
➕ Add Month
Add new months without re-uploading existing data
Currently loaded
📂
Drop Arrival or Cancellation files
Auto-detects month and type from filename
Add New User
➕ Add Month Data
Upload files for a new month without re-uploading existing data