The Booking Engine That Could: Handling Custom Pricing and Preferences at Scale

When I began developing the booking engine for Holiday Caravans Direct (HCD), I knew it would need to do more than just store bookings. It had to reflect the way owners actually ran their businesses — with flexible pricing, personal preferences, and non-standard booking patterns.

In other words, the system had to work the way people did — not the other way around.

Beyond Simple Check-In and Check-Out

Most off-the-shelf booking engines assume fixed-day pricing and standard rules. But HCD’s customers — private caravan owners — operated more like micro-businesses. They wanted to:

• Set their own high, medium, and low season pricing

• Define minimum stays during peak times

• Override prices on a day-by-day basis

• Accept both online and manual bookings

That meant I had to design a data model and API that could express complexity without making it feel complex to use.

Split Logic, Better Performance

I separated availability from pricing. This meant users could explore open dates quickly, without pulling pricing details until they were needed. It also meant:

• Pricing logic could be independently maintained and tested

• We could cache availability for speed

• UI could remain responsive without complex front-end calculations

Pricing became a separate service — one that could take into account owner-specific rules, custom rates, and user location (for tax or fee calculations).

Handling Manual Bookings

Manual bookings presented a unique challenge. They didn’t follow the same rules as online ones. Sometimes they were penciled in over the phone, or blocked out for family use. But they still had to:

• Show in the availability calendar

• Block dates from being booked

• Avoid interfering with quote generation

To solve this, I tagged manual bookings with special metadata and treated them as non-quotable. They showed up visually but were excluded from price logic.

Scaling with Preferences

As the platform grew, owners started requesting more:

• Security deposits

• Pet fees

• Short-break pricing

• Seasonal rules across multiple years

Because the system had been built with a flexible engine from the start, we were able to add these features incrementally. Most required no schema changes — just configuration and small logic extensions.

Lessons Learned

A booking engine isn’t just about dates and prices. It’s about reflecting human behavior, business quirks, and edge cases that don’t always make sense on paper.

By building with separation of concerns, layered rules, and override-friendly defaults, I created a system that adapted as the business evolved — not one that fought back against change.

The real success? Owners didn’t have to change how they worked to use the platform. The engine worked the way they did.