You cannot improve the offer funnel if you cannot measure it. Telemetry should show what request came in, what was returned, how fast it happened, and whether the traveler converted. Treat the funnel like a product with instrumentation baked in.
Define the funnel stages
- Search received: Request metadata, traveler context, correlation IDs.
- Offers generated: Count, composition, pricing methods used.
- Offers viewed: Which offers reached the UI or partner API response.
- Offer selected and ordered: Conversion events, including reasons when travelers abandon.
Data quality guardrails
Telemetry is only helpful if data is trustworthy. Implement automated checks:
- Schema validation for every event before it leaves the service.
- Sampling of payloads against business rules (e.g., total price matches sum of components).
- Anomaly detection for sudden drops in offer counts or spikes in errors.
- Latency percentiles per dependency (inventory, pricing, ancillaries).
- Error code distribution grouped by partner or channel.
- Offer-to-order conversion by market and fare brand.
- Time to first meaningful interaction after new releases.
Tooling considerations
Adopt centralized logging and metrics platforms. Ensure developers can trace a single request across microservices using consistent correlation IDs. Provide dashboards for operations, but also create self-service notebooks so analysts can explore data without engineering bottlenecks.
With disciplined telemetry and data quality checks, the offer funnel becomes a feedback loop. Teams can prioritize fixes based on measurable impact rather than intuition.