If you’re paying per API call, every extra look costs you real dollars, but it goes way beyond that. Here is how you can calculate the actual cost of each look to optimize your traffic.

Understanding Look to Book Ratio

The Look to Book ratio measures how many search requests (looks) are needed to generate a single confirmed booking. The basic formula is:

$$ \text{Look to Book} = \frac{\text{Number of Searches}}{\text{Number of Bookings}} $$

For example, if a travel platform submits 1,000 hotel searches and receives 50 bookings in return, the Look to Book ratio is:

$$ \frac{1,000}{50} = 20 $$

This means 20 “looks” are required to generate one booking.

When 1 Search Becomes 150 Requests

However, this simple ratio hides a significant portion of the actual cost incurred by suppliers and API providers. Here’s why:

1. Search Requests Are Amplified Internally

Most travel APIs allow a single search request to query hundreds of hotels at once. Therefore, the number of actual hotel lookups is much higher than the number of incoming search requests:

$$ \text{Effective Look to Book} = \\ \frac{ \text{Search Requests} \times \text{Avg. Hotels per Request} }{ \text{Bookings} } $$

If each search request contains 50 hotels, and 1,000 search requests are made, that’s 50,000 hotel lookups—just for 50 bookings.

2. Supplier Fan-Out Multiplies the Load

Behind the scenes, many B2B travel platforms and wholesalers don’t own the hotel data—they aggregate it from multiple suppliers. Each hotel search may fan out to several supplier APIs. A more realistic metric of internal load becomes:

$$ \text{Adjusted Look to Book} = \\ \frac{ \text{Search} \times \text{Hotels} \times \text{Suppliers} }{ \text{Bookings} } $$

Let’s say each hotel query is routed to 3 suppliers:

$$ \frac{1,000 \times 50 \times 3}{50} = 3,000 $$

That’s 3,000 backend supplier requests per booking—a 150x increase from the original ratio.

Why This Matters

  • Infrastructure Costs: Each additional supplier call increases server load, bandwidth usage, and cloud compute costs.
  • Rate Limiting & Throttling: High look-to-book ratios can lead to suppliers throttling your access or charging higher fees.
  • Opportunity Cost: Excessive looking can exhaust shared resources unfairly. Bad performing consumers can deplete your supplier’s quota therefore you cannot sell to better performing consumers.

Rethinking the Metric

Instead of just reporting a simple Look to Book ratio, travel companies should also track:

  • Fan-out factor (supplier load per search)
  • Effective backend look volume
  • Cost per successful booking, including compute and supplier overhead

Conclusion

The Look to Book ratio has long been a trusted benchmark in travel commerce, but its true cost lies beneath the surface. By accounting for the amplification through hotel-level fan-out and supplier-level propagation, travel platforms can better manage infrastructure, negotiate smarter contracts, and design systems that reward efficient traffic—not just high volumes.