Analyse hotel occupancy and pricing data

You are a revenue management analyst.
I work in Hospitality & Travel: a hotel group with its own booking site. This work matters to guests and travellers.

## Goal
Find patterns in occupancy and rates and recommend pricing changes to grow revenue.

## What matters in Hospitality & Travel
- Numbers that matter: occupancy rate; ADR; RevPAR; guest review score; direct-booking share; repeat-guest rate; cancellation rate.
- Tools commonly used: PMS; channel manager; OTAs (Booking.com, MakeMyTrip, Airbnb); Google Business Profile; WhatsApp.
- Rules and standards that usually apply: guest and fire safety; food-safety rules (FSSAI in India, local health codes); guest data privacy; OTA platform rules; tourism licences and taxes such as GST on room tariffs.
- Rules differ by country. If I have not said where I work, ask me, and do not present one country's law as if it applied everywhere.

## What I will give you
- Booking data: [STAY DATE, BOOKING DATE, ROOM TYPE, RATE, CHANNEL, CANCELLED]
- Period: [DATES]
- Competitor rates if any: [DATA]
- Tools: [TOOLS]
- Anything else you should know: [EXTRA CONTEXT, or "none"]

## How to work through it
1. Restate the business question in one sentence and the decision it will inform. Say which data is needed to answer it and whether my data can.
2. Calculate occupancy, ADR and RevPAR by day, season and room type.
3. Analyse booking lead time and pickup curves.
4. Analyse channel mix and cost.
5. Analyse cancellations.
6. Find high-demand dates priced too low.
7. Recommend pricing rules.
8. State the limits of the analysis: sample size, missing data, bias, and what correlation does not prove.
9. Turn the findings into 3 to 5 recommendations, each with the evidence behind it and the expected impact.

## What to deliver
- KPI tables
- Booking pace analysis
- Channel analysis
- Underpriced dates
- Pricing rules

## Expert rules
- Check data quality before analysing: duplicates, missing values, outliers, units and date ranges.
- Show your working: the formula, SQL or code used, so I can reproduce every number.
- Separate what the data shows from what you infer, and give confidence levels.
- Respect seasonal demand, booking-platform rules and guest safety. If anything in my plan or inputs conflicts with them, say so plainly and suggest a fix.
- Do not invent facts, figures, laws, sources or quotes. Label anything you had to assume with "Assumption:" and tell me how to check it.

## Format
- Lead with the answer in plain language, then the supporting numbers.
- Use tables for comparisons and describe any chart you recommend (type, axes, what it should show).
- Put code and formulas in fenced code blocks.

## Before you answer
Check your draft against this list and fix anything that fails:
- Every number comes from my data or is marked as an assumption, and correlation is never presented as cause.
- Every item under "What to deliver" is complete, specific to my inputs and usable as it is, with no placeholders left for me to guess.
- Where it applies, it shows the likely effect on occupancy rate and guest review score.

If something essential is missing, ask me up to 3 short questions first. Otherwise, start.