- Allow users to search for properties by commute time
- Incorporate travel times into the filtering and ranking of search results
- Enrich each result with the individual user's travel time
- Increase conversions by showing more relevant search results
- Capture user commute preferences to build a richer profile for relevant notifications and alerts
300% increase in conversions- More relevant results for users
- Reduced agent churn with higher quality leads
Ben Amos
Senior Product Manager at Zoopla
“With TravelTime, we help users much earlier in their property search journey, providing a more personalised discovery process based on what they need to be near, how long they want to travel, and by what transport mode.”
| Request type | POST |
| Host | api.traveltimeapp.com |
| Endpoint | /v4/time-filter/fast |
| Authentication | Application-Id Api-Key |
{
"locations": [
{
"id": "User Search Location",
"coords": {
"lat": 54.2389,
"lng": -0.3975
}
},
{
"id": "Listing 1",
"coords": {
"lat": 54.2442,
"lng": -0.4075
}
},
{
"id": "Listing 2",
"coords": {
"lat": 54.2483,
"lng": -0.4349
}
},
.
.
.
{
"id": "Listing 100,000",
"coords": {
"lat": 53.9923,
"lng": -0.5134
}
}
],
"arrival_searches": {
"many_to_one": [
{
"id": "Commute Time Search",
"arrival_location_id": "User Search Location",
"departure_location_ids": [
"Listing 1",
"Listing 2",
.
.
.
"Listing 100,000"
],
"transportation": {
"type": "public_transport"
},
"travel_time": 3600,
"arrival_time_period": "weekday_morning",
"properties": [
"travel_time"
]
}
]
}
}
locations - an array containing the IDs and lat-long coordinates of the user's search location and all of the property listings. This can include up to 100,000 listings, but could be pre-filtered using other search parameters if desired
many_to_one - travel times are calculated departing from each listing and traveling to the user's search location
arrival_time_period - weekday_morning reflects the typical travel times for a morning commute
travel_time - used to filter the reachable listings based on the user's chosen commute time (up to 3 hours)
transportation - taken from the user's chosen transport mode, typically Driving / Public_Transport / Walking / Cycling
properties - the data point(s) to be calculated for each listing - typically just travel_time, but distance can also be used if required
{
"results": [
{
"search_id": "Commute Time Search",
"locations": [
{
"id": "Listing 1",
"properties": {
"travel_time": 482
}
},
{
"id": "Listing 2",
"properties": {
"travel_time": 1853
}
}
.
.
.
],
"unreachable": [
"Listing 100,000"
]
}
]
}
locations - Reachable listings based on the user's commute search parameters.
unreachable - Unreachable listings outside of the user's commute search parameters
npm i traveltime-apiThis package comes with TypeScript support.
Before starting, the package needs to be configured with your account's application ID and Key, which can be found in the TravelTime Developer Portal Dashboard. To create an instance - you will need to create new TravelTimeClient class object with credentials you got from dashboard.
import { TravelTimeClient } from 'traveltime-api';
const travelTimeClient = new TravelTimeClient({
apiKey: 'YOUR_APP_KEY',
applicationId: 'YOUR_APP_ID',
});
travelTimeClient.timeFilterFast({
"locations": [
{
"id": "User Search Location",
"coords": {
"lat": 54.2389,
"lng": -0.3975
}
},
{
"id": "Listing 1",
"coords": {
"lat": 54.2442,
"lng": -0.4075
}
},
{
"id": "Listing 2",
"coords": {
"lat": 54.2483,
"lng": -0.4349
}
},
.
.
.
{
"id": "Listing 100,000",
"coords": {
"lat": 53.9923,
"lng": -0.5134
}
}
],
"arrival_searches": {
"one_to_many": [
{
"id": "Commute Time Search",
"departure_location_id": "User Search Location",
"arrival_location_ids": [
"Listing 1",
"Listing 2",
"Listing 3",
.
.
.
"Listing 100,000"
],
"transportation": {
"type": "public_transport"
},
"travel_time": 3600,
"arrival_time_period": "weekday_morning",
"properties": [
"travel_time"
]
}
]
}
}).then((data) => console.log(data))
.catch((e) => console.error(e));
Install Travel Time Python SDK in a virtualenv using pip. virtualenv is a tool to create isolated Python environments.
virtualenv allows to install Travel Time Python SDK without needing system install permissions, and without clashing with the installed system dependencies.
pip3 install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install traveltimepypip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install traveltimepyIn order to authenticate with Travel Time API, you will have to supply the Application Id and Api Key.
- app_id: str - Application Id
- api_key: str - Api Key
- limit_per_host: int - Number of simultaneous connections to one host.
- rate_limit: int - Number of searches which can be made in a time window.
- time_window: int - Duration, in seconds, of the time period in which to limit the rate.
- retry_attempts: int - Number of retries for failed requests.
- host: str - TravelTime host, default value is api.traveltimeapp.com.
- timeout: int - Maximum session time until timeout. Default value is 300 (5 minutes).
from traveltimepy import TravelTimeSdk
sdk = TravelTimeSdk(app_id="YOUR_APP_ID", api_key="YOUR_APP_KEY")
import asyncio
from traveltimepy import Location, Coordinates, Transportation, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("YOUR_APP_ID", "YOUR_APP_KEY")
locations = [
Location(id="User Search Location", coords=Coordinates(lat=54.2389, lng=-0.3975)),
Location(id="Listing 1", coords=Coordinates(lat=54.2442, lng=-0.4075)),
Location(id="Listing 2", coords=Coordinates(lat=54.2483, lng=-0.4349)),
Location(id="Listing 3", coords=Coordinates(lat=53.9923, lng=-0.3134)),
.
.
.
Location(id="Listing 100,000", coords=Coordinates(lat=53.9923, lng=-0.4134))
]
results = await sdk.time_filter_fast_async(
locations=locations,
search_ids={
"User Search Location": [
"Listing 1",
"Listing 2",
"Listing 3",
.
.
.
"Listing 100,000"
],
},
transportation=Transportation(type="public_transport"),
travel_time=3600,
)
print(results)
asyncio.run(main())
What is the performance like?
The Travel Time Matrix Fast endpoint can calculate 100,000 travel times in under 150ms.
How accurate is your data?
How reliable is the service?
Where do you have coverage?
How much will this cost?
We never charge based on usage. Instead we offer unlimited usage licences for a fixed monthly fee. The only thing you need to decide is the maximum Requests Per Minute (RPM) you need.
Can I test out the endpoint for myself?