- Allow users to search for properties by commute time
- Display their commutable area as a polygon on the map
- Filter reachable properties using this polygon
- 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-map/fast |
| Authentication | Application-Id Api-Key |
{
"arrival_searches": {
"many_to_one":[
{
"id": "Commute Time Search",
"coords": {
"lat": 51.1234,
"lng": -0.1984
},
"arrival_time_period": "weekday_morning",
"travel_time": 3600,
"transportation": {
"type": "driving"
}
}
]
}
}
many_to_one - captures the area that the user could travel from to arrive at their chosen location (e.g a morning commute to the office)
coords - lat-long coordinates of the user's search location - their address can be converted to lat-long coordinates using the TravelTime geocoding endpoint
arrival_time_period - weekday_morning reflects the typical travel times for a morning commute
travel_time - taken from 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
{
"results": [
{
"search_id": "Commute Time Search",
"shapes": [
{
"shell": [
{
"lat": 51.272484,
"lng": -0.964971
},
{
"lat": 51.272484,
"lng": -0.9634258
},
{
"lat": 51.271996,
"lng": -0.9626532
},
{
"lat": 51.271015,
"lng": -0.9626532
},
{
"lat": 51.269054,
"lng": -0.95956284
},
.
.
.
.
.
{
"lat": 51.51646,
"lng": -0.75791556
},
{
"lat": 51.51646,
"lng": -0.75637037
}
],
"holes": []
}
],
"properties": {}
}
]
}
{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "MultiPolygon",
"coordinates": [
[
[
[
-0.964970980072394,
51.27248479181435
],
[
-0.96342579042539,
51.27248479181435
],
[
-0.962653195601888,
51.2719948773738
],
[
-0.962653195601888,
51.2710150484927
],
.
.
.
.
.
[
-0.7579155673738569,
51.516462183208205
],
[
-0.7563703777268529,
51.516462183208205
]
]
]
]
},
"properties": {
"search_id": "Commute Time Search"
}
}
]
}
- level_of_detail - decrease this to improve performance of the application, or increase it to show more granular polygons
- polygons_filter - by default, the isochrone returned can be a multi-polygon, with disconnected 'islands' that are reachable but not attached to the main shape. Use this parameter to reduce the number of individual polygons
- no_holes - by default, the isochrone returned can have unreachable areas surrounded by a reachable area. Use this parameter to fill in these holes
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.timeMapFast({
"arrival_searches": {
"many_to_one":[
{
"id": "Commute Time Search",
"coords": {
"lat": 51.1234,
"lng": -0.1984
},
"arrival_time_period": "weekday_morning",
"travel_time": 3600,
"transportation": {
"type": "driving"
}
}
]
}
}).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 Coordinates, Transportation, TravelTimeSdk
async def main():
sdk = TravelTimeSdk("7092cee5", "3cdef325b69bda71401228df7dc4015b")
results = await sdk.time_map_fast_async(
coordinates=[Coordinates(lat=51.1234, lng=-0.1984)],
transportation=Transportation(type="driving+ferry"),
travel_time=3600
)
print(results)
asyncio.run(main())
What is the performance like?
The average response time for an isochrone is 105ms.
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?