How to monitor seasonal trends and peak travel periods ?

✅ Detect monthly revenue fluctuations
✅ Anticipate peak booking periods by destination
✅ Adjust allotments and promotions based on trends
✅ Prepare sales and ops teams for high-demand months

🚀 Objective: Use KOOB exports and booking reports to monitor seasonality and better prepare for fluctuations in demand.

Export booking data by travel period 🧾

To identify seasonal patterns, you need to export data sorted by the travel dates (not booking dates):

Go to Bookings > Clients' Bookings or My Bookings
Use the Travel Period filter to select a date range
Filter by Hotel or Experience
Click Extract to CSV to download your data

💡 Tip: Use Travel Period (Check-in/Checkout) rather than Booking Period to analyze real customer travel behavior.

Key columns to analyze for seasonality 📊

Column	Description
Check-in / Checkout	Indicates actual travel period
City / Country	Track seasonality by destination
Product Name	Identify seasonal best-sellers (hotel or experience)
Status	Focus on Confirmed bookings only
Number of Guests	Measure volume per period

💡 Example: After sorting the report by check-in month, you discover that bookings for Central Vietnam peak in April and August — ideal months to prepare guides, room allotments, and transfers in advance (suppliers management/logistic).

Group bookings by travel month in Excel 📆

To track monthly performance, add a new column called Travel Month and convert check-in dates to month/year format.

In Excel:

Create a Pivot Table using your booking report
Use the Check-in column as the row label
Right-click on any date in the Pivot → click Group
Select Months (and Years if needed)
In the Values section, use:
- Count of Booking ID → to measure booking volume
- Sum of “Selling Price TO” → to calculate revenue per month

💡 This gives you a clear breakdown of booking volume or revenue per month to detect low and high seasons.

Identify peak periods by destination or product 📍

In your Pivot Table, you can go deeper by cross-referencing:

Rows: Travel Month and Product Name
Or Travel Month and City
Values: Booking Count or Total Revenue

💡 Example: You notice “Luang Prabang Soft Adventure” spikes in December–January. You can use this to schedule more availability or run off-season campaigns for February.

Visualize seasonal patterns with graphs 📈

Use line graphs to illustrate booking trends:

X-Axis: Travel Month
Y-Axis: Number of bookings or revenue
Filter by destination, product, or TO if needed

💡 Example: A revenue graph shows that Siem Reap is strong in Q1 and Q4. You can use that to secure extra hotel inventory ahead of time.

Takeaways

✅ Use “Check-in” dates to analyze real travel behavior
✅ Group bookings by Travel Month to detect peak periods
✅ Use Pivot Tables and charts to visualize monthly trends
✅ Monitor seasonality per destination or product to optimize supply
✅ Plan marketing and operations around high-season insights

FAQ

How can I track peak travel months across destinations?
📅 Group confirmed bookings by “Travel Month” and break them down by “City” or “Country” to see where demand peaks.

Can I use this data to adjust hotel allotments?
📦 Yes! Spotting high season early helps you negotiate more rooms or experiences in advance.

What’s the best way to visualize this data?
📊 Use Excel’s Pivot Charts with months on the X-axis and revenue or volume on the Y-axis.

Can I monitor seasonality for a specific TO?
🔍 Yes, filter your booking export by “Tour Operator Name” before analysis.

📌 Need help? Visit the KOOB Knowledge Base or contact KOOB Support 🚀