Enrich your analysis & forecasting

Make your forecasts and operations more accurate by integrating event impact data directly into your BI tool of choice. PredictHQ's API access point options range from a granular event API to an API with prebuilt features to build models faster.

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Integrate with these and more

Pick your API

What are your business needs?

Depending on what you are looking for, we'll make sure we get you set up with the right API to start getting value out of PredictHQ's event data and intelligence as soon as possible.

Event API

Access to individual event data

Events vary in type, size, location, duration and impact. We aggregate and verify millions of events so data science teams have enough high-quality data to identify correlation between demand spikes and events, unlocking new opportunities.
More on the event API Event API technical docs
PythonCurl
import requests
response = requests.get(
    url="https://api.predicthq.com/v1/events/",
    headers={
      "Authorization": "Bearer $ACCESS_TOKEN",
      "Accept": "application/json"
    },
    params={
        "id": "e5c55724e854289204"
    }
)
print(response.json())
Features API

Save time with prebuilt intelligence and features

With the Features API, there's no need to build complex data handling systems or build features on your own. We handle the post processing work so you can focus on enabling your teams to extract value from event data rapidly. You can insert directly into your forecasting models.
More on the features API Features API technical docs
PythonCurl
import requests
data = {
    "active": {
        "gte": "2019-11-28",
        "lte": "2019-11-29"
    },
    "location": {
        "place_id": [
            5224323,
            5811704,
            4887398
        ]
    },
    "phq_attendance_conferences": {
        "stats": [
            "min",
            "max"
        ]
    },
    "phq_attendance_sports": True,
    "phq_attendance_concerts": True,
    "phq_rank_public_holidays": True
}
response = requests.post(
    url="https://api.predicthq.com/v1/features",
    headers={
      "Authorization": "Bearer $ACCESS_TOKEN",
      "Accept": "application/json"
    },
    json=data
)
print(response.json())
Demand Surge API

Easily identify Demand Surges

Events frequently cluster, creating a larger impact. Demand surges are caused by many events occurring during the same time period and within a specific location. Use this API to get value immediately without having to think about all the events powering an upcoming surge.
More on the demand surge API
PythonCurlRaw
import requests

response = requests.get(
    url="https://api.predicthq.com/v1/demand-surge/",
    headers={
      "Authorization": "Bearer $ACCESS_TOKEN",
      "Accept": "application/json"
    },
    params={
        "date_from": "2021-05-12",
        "date_to": "2021-08-10",
        "min_surge_intensity": "m",
        "location.place_id": "2643743"
    }
)

print(response.json())
Live TV Events API

Access to historical and predicted viewership data

Better predict surges in demand caused by televised events such as sports. Filter by city or county to access relevant data rather than by broad designated market areas (DMAs) used by other providers. Access to county-level viewership data enables you to confidently forecast at a more granular level, such as for individual stores if you're a quick-service restaurant or grocery store.
More on live tv events
Live TV Events API technical docs
Walk through the Data with Data Scientist Andrew Walker
Walk through the Data with Data Scientist Andrew Walker

Watch video (14:37)

PythonCurl
import requests

response = requests.get(
    url="https://api.predicthq.com/v1/broadcasts/",
    headers={
        "Accept": "application/json",
        "Authorization": "Bearer $ACCESS_TOKEN"
    },
    params={
        "location.place_id": "5368381,5391832",
        "start.gte": "2020-11-01",
        "start.lte": "2020-11-30",
        "start.tz": "America/Los_Angeles"
    }
)

print(response.json())
Forecast ready Features

Regardless of the API you choose, get up and running quickly

We've created Jupyter notebooks on how to integrate our 19 (and counting) event categories into your models to help your Data Science teams get up and running quickly. It includes guides to using our APIs and data with common Data Science tools and libraries in Python.
Check out our Jupyter Notebooks
Jupyter Notebook Screenshots

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Customer Stories

Demand intelligence gets results

Our customers include leading companies across retail, transport, accommodation and financial service sectors. They use our intelligent event data for labor optimization, demand forecasting, dynamic pricing, supply chain optimization and more.
Explore use casesMore customer stories
Thomas Joseph
Thomas Joseph
Head of Data Science, 
Legion
Don't underestimate how much effort it takes to work with event data... Being able to rely on a company whose sole purpose is to remove the ambiguity of event data has been game-changing for us.
Read Legion’s Story

You can’t prepare for what you don’t see coming

Harness the power of demand intelligence

Knowing the impact of demand causal factors like events will transform your business. The American Society of Hematology has a $45M estimated economic impact — and that's only one event in one city.

  • 0
    data points enriching
  • 0
    events across
  • 0
    cities, accessed via
    1 API

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