Flights: Summary provides flights insights, such as lookahead window, trip duration, and trip type percentages. Lookahead Analysis leverages data aggregated from searches in Google Flight Search (GFS). See www.google.com/flights.
Introduction
Flights: Summary reports show the following information:
- Lookahead window: when travelers intend to fly
- Trip duration: how long travelers intend to stay
- Trip type: what percentage of searches are one-way vs. return trips
Data is aggregated weekly; each week includes 7 days of data beginning from the search week start date.
The Filters
Set the search week scope
Use the Search Week slider to set the start and end of the period you want to analyze.
Geo Filters
Use the geography filters to constrain results by origin and destination location. The filters include both origin and destination options. Geographies are defined as follows:
- Subcontinent: A large part of a continent, e.g., North America, East Asia, etc.
- Country: Country, e.g., US, Indonesia, France, etc.
- Region: ISO 3166-2 administrative area 1. Usually a large part of a country, e.g., states in the US.
- City: City where the route starts.
Advanced Filters
- Domestic / Int’l: Whether the flight is within a country or between countries.
- Route Cluster: The route cluster shows the distance people are looking to travel:
[1] <500km (incl. X-border).
The distance between origin and destination is less than 500km and within the same country.
[2] Anywhere in the area (EMEA, Americas, or APAC).
Any intercontinental travel that is within a main advertising region.
[3] Anywhere in the country.
Any travel between regions that is still within the same country.
[4] Anywhere in the region/state.
Any city-to-city travel that is still within the same region.
[5] Anywhere in the subcontinent.
Any travel between countries but remaining within the same subcontinent.
[6] Anywhere in the world.
Any travel between subcontinents.
Dashboard Sections
The Flights: Summary dashboard contains the following reports:
Overview
Highlight averages of lookahead window, trip duration, and one-way trips with MoM growth trends.
Average lookahead window
Overall: Average number of days between search date (when users search in GFS) and departure dates (the travel dates users wish to travel).
International: Average lookahead window (days) for international flights (the origin country is not the destination country).
Domestic: Average lookahead window (days) for international flights, (the origin country is also destination country).
Average trip duration
Overall: Average number of days between departure date and return date (trips must not be one way).
International: Average trip duration (days) for international flights, i.e., origin country != destination country.
Domestic: Average trip duration (days) for international flights, i.e., origin country == destination country.
One-way trips
Overall: Percentage of one way trips over all trips.
International: Percentage of international one way trips over all international trips.
Domestic: Percentage of domestic one way trips over all domestic trips.
About the MoM date range:
The month-over-month growth for average lookahead window, trip duration, and one-way trip split is based on the last 28 days before the selected date range, as shown in this example:
|
Start date |
End date |
|
|---|---|---|
|
Selected date range |
1 Jan '20 |
28 Feb '20 |
|
Previous month (-28 days) |
4 Dec ’19 |
31 Jan ‘20 |
For the One-Way Trips summary, this expresses the MoM growth in percentage points (pp).
Lookahead Window
Highlight when users expect to travel in the future by showing the number of days between search date and departure / travel date. Bucketing is useful to identify what type of travels users are looking for, e.g., winter vs summer.
Lookahead Window Trend
Lookahead Window Trend is a line chart showing the number of days between the search and departure dates by search week from Google Flights Search (GFS).
Avg Lookahead: average number of days between search date (when users search in GFS) and departure dates (the travel dates users wish to travel)
International: average lookahead window (days) for international flights (origin country is not the destination country)
Domestic: average lookahead window (days) for international flights (origin country is also the destination country)
Lookahead Window Split
Bar charts show the lookahead window buckets described above as clusters representing the number of days between search and departure dates and the international vs. domestic split during those time buckets.
A table provides this information by "route cluster," a concept that groups the window buckets according to how far the user is willing to travel, for example:
| Lookahead Window | |||||||
|---|---|---|---|---|---|---|---|
| Route Cluster | <= 7 days | 1-2 weeks | 2-4 weeks | 1-3 months | 3-6 months | > 6 months | Total |
|
<500km (includes border crossings) |
23.2% |
11.1% |
31.0% |
24.6% |
6.7% |
3.5% |
100% |
|
Anywhere in the region/state |
23.8% |
12.2% |
31.8% |
23.8% |
5.9% |
2.5% |
100% |
|
Anywhere in the country |
19.4% |
10.6% |
29.9% |
28.2% |
8.6% |
3.3% |
100% |
|
Anywhere in the subcontinent |
14.2% |
8.8% |
26.9% |
30.9% |
12.7% |
6.5% |
100% |
|
Anywhere in the area (EMEA, Americas, or APAC) |
14.0% |
8.8% |
27.0% |
30.2% |
12.8% |
7.1% |
100% |
|
Anywhere in the world |
10.4% |
6.7% |
24.7% |
28.4% |
17.5% |
12.3% |
100% |
Trip Duration (for round trips)
Highlight how long users expect to travel by showing #days between departure date and return date. One way trips are excluded from these calculations.
Trip Duration Trend
The Trip Duration Trend is a line chart showing the number of days between the search departure and return dates in Google Flight Search (GFS).
Average trip duration
Overall: Average number of days between departure date and return date (trips must not be one way).
International: Average trip duration (days) for international flights (origin country is not the destination country).
Domestic: Average trip duration (days) for international flights (origin country is also the destination country).
Trip Duration Split
Bar charts show the lookahead window buckets described above as clusters representing the number of days between round trip search and departure dates and the international vs. domestic split during those time buckets.
A table provides this information by "route cluster," a concept that groups the trip duration buckets according to how far the user is willing to travel:
| Trip Duration | |||||||
|---|---|---|---|---|---|---|---|
| Route Cluster | <= 3 days | 4-7 days | 1-2 weeks | 2-4 weeks | >4 weeks | Total | |
|
<500km (incl. X-border) |
42.4% |
48.1% |
5.1% |
2.7% |
1.7% |
100% |
|
|
Anywhere in the region/state |
48.7% |
42.7% |
5.1% |
2.2% |
1.3% |
100% |
|
|
Anywhere in the country |
36.0% |
51.9% |
8.1% |
2.5% |
1.5% |
100% |
|
|
Anywhere in the subcontinent |
32.1% |
50.5% |
11.9% |
3.6% |
2.0% |
100% |
|
|
Anywhere in the area (EMEA, Americas, or APAC) |
22.8% |
50.5% |
16.5% |
6.6% |
3.6% |
100% |
|
|
Anywhere in the world |
5.6% |
39.9% |
28.9% |
16.8% |
8.7% |
100% |
|
Trip Type
Highlight the percentage of searches for one-way vs. round trip or multi-city trips.
Trip Type Trend
Trip Type Trend is a line chart showing the percentage of one-way versus round trip and multi-city flights by search week:
- Overall: Percentage of one way trips over all trips.
- International: Percentage of international one way trips over all international trips.
- Domestic: Percentage of domestic one way trips over all domestic trips.
This chart also provides a summary of one-way international and one-way domestic month over month (MoM) growth in percentage points (pp).
Trip Type Split
Trip Type Split consists of bar charts showing the overall breakdown between one-way vs. return/multi-city, for domestic and international searches:
- One-way: Indexed GFS volume of one-way flights.
- Return and Multi-city: Indexed GFS volume of return flights, e.g. Jakarta-Dublin-Jakarta, and the indexed GFS volume of multi-city flights, e.g., Jakarta-Dublin-New York.
Similarly to Trip Duration Split, this section includes a table summarizing the one-way versus return/multi-city by route cluster.