> ## Documentation Index
> Fetch the complete documentation index at: https://docs.planeconnection.com/llms.txt
> Use this file to discover all available pages before exploring further.

# How to Analyze Route Performance

> Analyze city-pair route frequency, on-time performance, revenue per route, and identify optimization opportunities.

By the end of this guide, you will have analyzed route frequency and on-time performance, identified high-value and underperforming routes, and used route data to inform scheduling decisions.

<Info>
  The Operations module must be enabled for your workspace. You also need the appropriate operations
  permissions. Contact your workspace administrator if you cannot access these features.
</Info>

<Info>
  You need any ops access role. Revenue data on routes requires `accounting.read` permission.
</Info>

## Navigate to Route Profitability

Open the Operations sidebar, click **Analytics**, then click the **Route Profitability** card on the landing page.

**Breadcrumb path:** Ops > Analytics > Route Profitability

## Popular routes

The ranked list shows origin-destination pairs ordered by flight count for the selected period. Each row includes:

| Column         | Description                                      |
| -------------- | ------------------------------------------------ |
| Origin         | Departure airport (ICAO code).                   |
| Destination    | Arrival airport (ICAO code).                     |
| Trip Count     | Number of trip legs flown on this route.         |
| Total Revenue  | Sum of revenue attributed to legs on this route. |
| Total Costs    | Sum of costs for legs on this route.             |
| Avg Block Time | Average block time in hours for this city pair.  |

<Tip>
  High-frequency routes are candidates for standardized trip templates, pre-negotiated FBO rates,
  and contract fuel agreements that reduce per-trip costs.
</Tip>

## On-time performance by route

The OTP chart shows on-time percentage for each route. On-time is defined as departing within 15 minutes of the scheduled departure time. Routes with consistently low OTP warrant investigation:

| Potential cause         | Investigation approach                                       |
| ----------------------- | ------------------------------------------------------------ |
| ATC delays at origin    | Review ATCSCC data for the departure airport.                |
| FBO handling delays     | Check vendor scorecard data for the origin FBO.              |
| Crew positioning issues | Verify crew base locations and positioning leg requirements. |
| Aircraft availability   | Review fleet health and maintenance schedules.               |
| Weather patterns        | Analyze seasonal weather data for the route corridor.        |

## Revenue per route

The revenue chart shows estimated revenue per city pair. Combine this with cost data to compute route-level profitability:

* **High revenue, low cost** -- premium routes to protect and market.
* **High revenue, high cost** -- investigate cost drivers (fuel, positioning, handling).
* **Low revenue, any cost** -- evaluate whether the route serves strategic positioning or relationship purposes.

## Route optimization checklist

<Steps>
  ### Step 1: Identify high-frequency, low-OTP routes

  Sort routes by trip count and filter for OTP below 80%. These routes have the most impact on operational reliability.

  ### Step 2: Analyze deadhead patterns

  Cross-reference with the Fleet Utilization deadhead ratio chart. Routes with high deadhead on the return leg are candidates for empty-leg marketing.

  ### Step 3: Review seasonal trends

  Use the 1 Year date range to identify seasonal demand patterns. Pre-position aircraft at high-demand origin airports during peak seasons.

  ### Step 4: Negotiate FBO rates

  For routes with more than 10 trips per quarter, negotiate contract rates with destination FBOs to reduce handling costs.
</Steps>

## Pipeline analytics

The **Pipeline** sub-tab (**Ops > Analytics > Pipeline**) tracks the sales pipeline from quote to confirmed trip:

| Metric            | What it measures                                  |
| ----------------- | ------------------------------------------------- |
| Quote volume      | Number of quotes issued in the period.            |
| Conversion rate   | Percentage of quotes that become confirmed trips. |
| Revenue forecast  | Projected revenue from pending quotes.            |
| Average deal size | Mean revenue per converted quote.                 |

Use pipeline data to forecast revenue, identify sales bottlenecks, and allocate fleet capacity to meet projected demand.

## Related

<CardGroup cols={2}>
  <Card title="Use Analytics Dashboard" href="/how-to/ops/use-analytics-dashboard">
    Overview of all analytics capabilities.
  </Card>

  <Card title="Analyze Fleet Performance" href="/how-to/ops/analyze-fleet-performance">
    Aircraft utilization and deadhead analysis that complements route data.
  </Card>

  <Card title="Use Charter Marketplace" href="/how-to/ops/use-charter-marketplace">
    Market empty legs identified through route analysis.
  </Card>

  <Card title="Analytics Metrics Reference" href="/reference/analytics-metrics">
    All available metrics, dimensions, and calculation methods.
  </Card>
</CardGroup>