Look-to-book ratio and caching: what CTOs should demand from a travel API

1. Why look-to-book becomes your problem

Suppliers carry the cost of every availability request. Airlines, GDSs and bedbanks watch how many searches each partner sends per booking, and partners who search heavily without converting may be asked to review how they search. When you build on someone else's API, you inherit that pressure in two ways: through their pricing (per search, per booking or limits passed on to you) and through their behaviour, because an API that fans every search out to every supplier will burn through your allowance fast.

The usual reaction is to chase a single target number. That rarely helps. Look-to-book depends on vertical mix, market and shopping patterns, so a healthy ratio for hotels in one city looks nothing like flights on a busy domestic route. What matters is whether the API keeps unnecessary looks off the supplier while still returning prices that hold.

2. Caching: fast is easy, honest is hard

Caching is the main lever. Serve repeated or similar searches from a recent cached result and you cut supplier calls and answer faster. The trap is the stale price: the traveller or agent sees one fare, clicks book, and the supplier confirms a different one. Every failed price check costs another look and, worse, trust.

What to demand:

• A clear refresh strategy. Ask how long cached availability lives, what triggers a refresh, and whether that differs by vertical and route.
• Re-verification before booking. The price shown in results should be re-checked with the supplier before the order is created, and a price change should come back as an explicit response, not a vague error.
• Honest labelling of what's cached. Your front end should know whether a price is live or cached so it can handle the gap gracefully.

3. Routing: don't ask every supplier every question

The second lever is where searches go. A naive integration sends each search to every connected supplier and merges the results. A better one ranks suppliers per route by how fast and how reliably they answer, and skips the ones unlikely to return anything useful. Fewer wasted looks, faster results, and the supplier that's having a bad day stops dragging down your whole search.

Pair routing with deduplication. When the same flight or hotel comes back from three sources, the API should merge it into one result with the source shown, not hand your UI three near-identical rows.

4. Idempotency: retries shouldn't cost looks or create duplicates

Travel calls time out. Networks split. Clients retry. Without idempotency keys on write operations, a retried booking call can create a second order, and a confused client may re-run the whole search-price-book sequence. Demand idempotent writes in your travel booking API: the same key returns the same order, so a retry is safe and doesn't add looks or bookings you didn't mean to make.

5. Schema versioning: drift creates silent looks

When a supplier changes its response format, failed parses often look like empty results. Clients retry, users search again, and look-to-book climbs for reasons nobody can see. A unified travel API should use schema versioning for its own schema so your client doesn't break when a supplier changes, and it should absorb schema drift at the edge. For the deeper dive, see self-healing supplier connectivity.

6. Measure it per supplier and per route

You can't manage a ratio you only see as one monthly number. Ask whether the platform reports look-to-book, latency, error rate and conversion per supplier and per route, so routing decisions and supplier negotiations are based on evidence.

7. A short checklist for your next API review

• How are cached prices refreshed, and is every price re-verified before booking?
• Are suppliers ranked per route, or does every search hit every supplier?
• Are equivalent offers deduplicated, with the source shown?
• Are all write calls idempotent?
• Is the client-facing schema versioned, and who absorbs supplier changes?
• Can you see look-to-book per supplier and route?
• Are supplier look-to-book limits passed on to you, and how?

For the wider buyer checklist, see our travel API evaluation checklist. New to the category? Start with what a unified travel API is.

8. How Synapse approaches this

Elkanio Synapse is a unified travel REST API across nine verticals. Distributed caching returns availability quickly, with a refresh strategy that keeps cached prices matched to what the supplier will confirm. Suppliers are ranked per route by live latency and success rate, so search goes where an answer is likely. Results are deduplicated across sources, write calls take idempotency keys, keys have per-key rate limits, and the OpenAPI 3 schema stays stable while supplier changes are absorbed by the agentic self-healing runtime.

Cortex reports look-to-book, latency, error rate and conversion by supplier and route, which feeds back into Synapse routing.

Bring your current search volumes and supplier mix to a demo, and we'll walk through how Synapse would route and cache them.