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Errors and failures

The order was placed. The kitchen never saw it.

Bicycle watches every order from the delivery app to the point of sale, and finds where they fail and the main cause.

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Before

An order can fail at several handoffs between the delivery app and the restaurant's POS. Rejections and lost orders look the same in a report, and each handoff has a different owner.

With Bicycle

Spikes in rejections, cancellations and failed deliveries to the POS are detected at the handoff and the store where they happen.

What happens when a KPI moves.

  1. 01

    Detect

    Rejections, cancellations or failed deliveries to the POS spike for one delivery app and store.

  2. 02

    Explain

    The order journey shows where orders are failing and the main cause.

  3. 03

    Act

    Bicycle recommends the next step: engineering patches the issue, merchant success calls the restaurant, or partnerships raise it with the delivery app.

  4. 04

    Learn

    Repeat failures show which integrations to strengthen and which restaurants need help getting set up.

45,000+

restaurant locations watched

Seen at: Urban Piper. Read the case study

Everyone can ask. Data & Analytics controls what gets trusted, published, and acted on.

Runs on
  • Order events
  • Delivery-app interfaces
  • Point-of-sale logs
Used by
  • Program management
  • Site reliability
  • Merchant success

Common questions

How do you find where online orders fail before they reach the POS?
Bicycle treats each order as a sequence of events: created, confirmed by the delivery app, received by your middleware, forwarded to the POS, confirmed by the POS, then fulfilled. Bicycle tracks success and failure at every stage by delivery app, store, region and time window, and classifies each failure as an app-side rejection, a middleware processing failure, a POS delivery failure, a cancellation cascade or an error-rate spike.
Do you need a data warehouse to track order failures between delivery apps and the POS?
No separate warehouse build is needed. Bicycle connects to the event streams you already run, such as Kafka and webhook APIs, and produces the order-journey view from them. Stores, menu items, orders, delivery apps and POS systems, their state changes, and the rhythm of peak hours and daily settlement cycles are already modeled.
Which team handles each kind of order failure?
Bicycle sends each failure to the team that responds to it: site reliability for middleware-side issues, merchant success for restaurant-side patterns and partnerships for systemic delivery-app problems. A flow view shows order volume moving, or failing to move, between stages by delivery app and store, so each team sees its own leakage point before it decides the fix.

More on errors and failures

See it on your own KPI.

Bring one revenue-critical KPI. We'll show how Bicycle detects the movement, explains the cause, and recommends the next step.

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