Booking Platform Performance · OnStak Use Case

Keep the booking before it times out.

In hospitality, a slow booking page is a lost reservation. When response times crawl and mobile checkouts time out at peak season, revenue walks. Here is how one global hotel group cut booking time in half and stopped the timeouts.

4.2s → 2.1s

booking response time

63% fewer

mobile checkout timeouts

15% → 3%

payment gateway failures

Traveller booking a hotel on a mobile device

Story highlights

  • Booking time halved. Response fell from 4.2s to 2.1s by isolating the JavaScript and page-load issues slowing the booking app.
  • Timeouts down 63%. The mobile checkouts that failed at peak season dropped sharply.
  • Payments made reliable. Gateway failures fell from 15% to 3%, and the NOC saved 100+ troubleshooting hours.

The situation

900+ properties, one booking platform under strain.

The hotel group ran booking across more than 900 properties, and at peak season the platform buckled: slow responses, timed-out mobile checkouts, and payment failures when occupancy was highest. They set out to find what was slowing the booking journey.

The problem

Peak season was where bookings broke.

The busiest weeks were the ones the platform handled worst. Three symptoms stood out.

Slow booking responses

28% of properties reported booking response over 4 seconds.

Mobile checkouts timed out

22% of mobile transactions timed out during peak season.

Payments failed at capacity

10% of payment gateway attempts failed during high occupancy.

What OnStak did

Isolate what slows the booking, node by node.

OnStak tested the booking journey the way a guest experiences it, and traced the slow points to their source.

1

Tested the booking journey

Transaction tests deployed across the booking application.

2

Isolated the front-end drag

JavaScript and page-load issues pinpointed.

3

Traced login issues to the node

Network visibility isolated login problems to specific network nodes.

4

Cleared the path for peak

The fixes held through high-occupancy periods.

What changed

From a platform that buckled at peak to one that holds.

Before

The busiest weeks broke the booking.

  • 28% of properties saw booking response over 4 seconds.
  • 22% of mobile checkouts timed out at peak.
  • 10% of payments failed at high occupancy.
After, with OnStak

Now the booking completes.

  • Booking response 4.2s to 2.1s.
  • Mobile timeouts down 63%.
  • Payment failures 15% to 3%.

The outcome

Anonymized hotel group · 900+ properties

Faster bookings, fewer failures, hours back.

2.1s
Booking response
Down from 4.2s.
63%
Fewer timeouts
Mobile checkout timeouts reduced.
3%
Payment failures
Down from 15%.
100+
NOC hours saved
Troubleshooting time returned.

The idea that holds it together

A booking you keep beats a page you fix.

“At peak season, speed is revenue. Observability turns a slow path into a booking that completes.”

Awais Janjua  /  Chief Technology Officer, OnStak

Built on
Splunk observability platform Synthetic transaction tests JavaScript / page-load analysis Network node isolation Booking application monitoring

Coffee? No Slides

No pitch deck. No 47-page proposal. Just a straight talk about what’s broken and what to fix first.

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