Find the direct channel revenue leaks before the OTAs capture them.
Bicycle watches direct conversion rate, abandonment, loyalty redemption yield, ancillary attach, rate parity, and revenue per available unit across the routes and properties 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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- 1OTA rate undercut the direct price on the same fare classhigh
- 2Loyalty sign-in errors rising at the payment stepcontributing
- 3Abandonment concentrated at one funnel step on mobilecontributing
A dashboard shows the direct conversion drop. Bicycle finishes the investigation and recommends the fix.
Start with a single revenue KPI critical to your business.
Bicycle comes with direct channel 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 direct channel problem not listed here? Book a demo and we will map it.
A dashboard shows the drop. It never finishes the investigation.
Direct conversion drops for a route. The manual chase begins.
The dashboard shows the decline. The team still checks OTA pricing, abandonment funnels, loyalty sign-in logs, and ancillary data by hand, across five tools and three people.
- Revenue checks OTA rate comparison manually
- Product checks abandonment funnel by step
- IT checks loyalty sign-in error logs
- Analytics pulls route and property cuts
- Teams argue over whether it's pricing or friction
Bicycle starts the investigation the moment direct conversion drops.
It detects the conversion gap, ranks the OTA rate and friction causes, tests pricing and technical factors in parallel, attaches the evidence, and routes the issue to the revenue 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 engine · PMS · loyalty feeds · OTA rate data · ancillary data · Slack
Bicycle runs on top of your existing systems. The direct channel pack supplies the starting KPIs, causes, stories, and action paths.
Start with one KPI in your direct channel stack.
Bring one revenue-critical KPI, connect a trusted source, and watch Bicycle turn a prompt plus your data into a direct channel analytics agent. Zero to a working agent in about 15 minutes.
Grow into the full product when your team is ready.
Test ride Bicycle on a direct channel KPI.
Bring one direct channel or revenue metric 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.
No credit card required