Find the travel revenue leaks before they cost you.
Bicycle watches bookability, supplier health, search-to-book conversion, price movement, and booking-funnel KPIs across the segments that matter. When a number moves, it explains the likely cause and recommends the next action to the team that can fix it.
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- 1Supplier rejecting at confirmation on this carrierhigh
- 2Carrier-tier threshold breached vs 3-hour baselinecontributing
- 3Provider API timeouts spiking on the booking callcontributing
A dashboard shows the drop. Bicycle finishes the investigation and recommends the fix.
Start with a single revenue KPI critical to your business.
Bicycle comes with travel industry intelligence already inside. Pick one Bicycle-recommended KPI and watch it run: the KPI it watches, the causes it checks, the action it recommends to the owner, and what it keeps.
A travel problem not listed here? Book a demo and we will map it.
A dashboard shows the drop. It never finishes the investigation.
Bookability drops. The manual chase begins.
The dashboard shows the decline. The team still checks supply, fares, availability, carrier connectivity, and route patterns by hand, across five tools and four people.
- Revenue team checks top routes
- Supply checks carrier availability
- Product checks search and booking flow
- Analytics pulls city and route cuts
- Ops argues over who owns the fix
Bicycle starts the investigation the moment the KPI moves.
It detects the drop, ranks the affected routes and cities, tests business and technical causes in parallel, attaches the evidence, and routes the issue to the owner with the next step.
- Detect the movement, ranked by impact
- Test business and technical causes together
- Attach the evidence, rule out the rest
- Route the safe action to the owner
- Learn the accepted cause for next time
Trained on the KPIs, patterns, and root causes of travel.
Six capabilities, set up once and run continuously. Business teams move faster, analysts keep governance, everyone trusts the number. Pick one to go deeper.
Multi-factor cause analysis
"What caused this?" turns into a three-day Slack thread across data, product, ops, and engineering, and the answer still arrives without evidence.
What Bicycle does
Open the cause summary. Ranked business and technical causes. The likely driver is named, with confidence and impact.
See the evidence. Logs, deploys, pricing changes, supplier behavior, and search relevance, with the data attached.
Know what was ruled out. The negative findings close the debate before it starts.
What it looks like for your team
Each drop is broken down by provider-error type, route, and revenue-weighted impact, so commercial knows whether it is a carrier, channel, or regional issue.
Capabilities work together in one continuous loop. Detect → Explain → Act → Learn.
Business teams need answers fast. Analysts ensure conclusions are trustworthy.
Same governed intelligence underneath. The travel agent for the teams who own the number, the controls for the team who owns the data.
See what changed, why, and what is safe to do.
The move finds you, ranked by revenue impact, with the cause and the next step attached. No dashboard hunt, no three-day ticket.
Govern the definitions, evidence, and safe actions.
Analysts review first-pass causes instead of rebuilding them. Leaders give the business self-service inside one governed boundary.
The agentic analytics layer on top of your stack.
Your stack stays the system of record. Bicycle turns travel signals into alerts, triage, stories, dashboards, chat, and governed actions on top of it. No rip-and-replace.
Frames the question, orchestrates the investigation, writes the story, recommends the next step. It reasons.
Detects movement, ranks drivers, computes confidence, forecasts. The numbers are calculated, not generated.
And the rest of what you run: booking events · supplier feeds · GDS · pricing systems · payment gateway · Slack
Bicycle runs on top of your existing systems. The travel pack supplies the starting KPIs, causes, stories, and action paths.
How is Bicycle different from what a travel team already runs?
Dashboards are useful for overall booking trends, reporting, executive summaries, and recurring visibility. Bicycle complements dashboards: the dashboard tells you bookings dropped; Bicycle tells you why and what to do next.
| What the tool does after a KPI moves | Dashboards | AI chatbots | Warehouse AI | Bicycle |
|---|---|---|---|---|
| Notices the move without being asked | Only when someone opens the right view. Thresholds fire on the total, not on one route or one supplier. | No. Someone has to suspect the drop and phrase the question first. | Queries can be scheduled on warehouse tables. You build and tune the detection yourself. | Watches bookability, supplier health and booking conversion continuously, down to supplier, carrier, route and city pair. |
| Ranks the likely causes | No. The chart shows the decline. Supply, fares, availability, carrier connectivity and route patterns are still checked by hand, across five tools and four people. | Generates a plausible explanation. Tests no drivers in parallel and rules nothing out. | Writes the query once you decide which metric, which window and which drivers to ask about. | Tests supplier response, fares, carrier confirmation, payment handoff and error patterns in parallel, ranked by booking impact. |
| Shows the evidence, and what it ruled out | The underlying views are there. Assembling them into an explanation is manual. | No lineage attached, so teams quietly re-check the number in a spreadsheet. | The SQL is visible. Supplier and carrier systems outside the warehouse are not. | Definition, lineage, source query and the drivers ruled out, attached to the finding. |
| Recommends the next step, and who owns it | No. At best a link through to another view. | Stops at the answer. Choosing and routing the next step stays with the reader. | A warehouse computes. It does not act. | Recommends the next step to supplier operations or revenue management, with the affected routes, suppliers and estimated booking impact. |
| Keeps the action governed | Read-only, so there is nothing to govern. | Where actions exist at all, they sit outside scope, approval and rollback. | No governed path to Slack, a ticket, or a rollback. | Every action scoped, previewed, approved, reversible and logged. |
Bicycle runs on top of the stack you already report from. Your dashboards, warehouse and BI stay the system of record.
Building it yourself is the fourth option. What the other 90% costs →
Start with one KPI in your travel stack.
Bring one revenue-critical KPI, connect a trusted source, and watch Bicycle turn a prompt plus your data into a travel analytics agent. Zero to a working agent in about 15 minutes.
Grow into the full product when your team is ready.
How does a travel team find out why bookings dropped?
Bicycle watches travel KPIs continuously and catches a drop on one carrier, route or market before the overall number moves. It tests supply, pricing and technical causes together, names the likely one with the evidence attached, and says what it ruled out. Bicycle recommends the next step; supplier ops or commercial approves it.
Search events, booking attempts, confirmations, supplier responses, provider error codes and fares, read from the systems already running your search and booking flow. Bicycle connects to them rather than moving them. One revenue-critical KPI with a trusted source is enough.
Search and booking systems, supplier and route feeds, pricing, payment, error-code and ticketing data, plus the Slack, email and runbook channels your team already works in. Bicycle reads from them and your stack stays the system of record.
Days. The travel pack already models carrier, supplier, route, pseudo-city and city pair as first-class concepts, with detection patterns and cause categories included, so setup is reviewing what Bicycle proposes rather than modelling it from scratch.
You do. When bookability or search-to-book conversion moves, Bicycle recommends the next step to the team that owns it, commercial or supplier ops, with the carrier, the route and the revenue exposure attached. Scoped, previewed and logged before anyone runs it.
Bicycle watches bookability, supplier health, search-to-book conversion, price movement and booking-funnel KPIs. Most travel teams start with the one that fails quietly: supplier bookability, where a single carrier rejecting at confirmation drains bookings well before the average moves.
Test ride Bicycle on a travel KPI.
Bring one KPI that matters. We will show how Bicycle detects the move, explains the cause, and recommends the next step on top of the stack you already run.
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