Improve Predictive Analytics Modeling

Train your predictive analytics models with demand intelligence to better anticipate demand anomalies and prepare before they occur.
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The Challenge

Most analytics models don’t factor in all demand causal factors — like the impact of events

Real-world event data is always changing, difficult to standardize, and often messy with duplicate events and spam. So predictive analytics models usually don’t account for these demand causal factors. Instead, data science teams have to manually pull this information separately.

Our Solution

Train your predictive analytics models with demand intelligence

Demand intelligence identifies demand catalysts so teams within a business can prepare for future demand fluctuations. Technical teams can train their models with the event APIto get a more accurate depcition of forecasts. Business managers can set up event event notificationsto get instantly notified of when impactful events are taking place.

01

Centralize

Centralize and aggregate historical event data.
02

Correlate

Identify correlation between your historical transaction data and events.
03

Train

Train predictive analytics models to improve forecasting precision.
01

Centralize and aggregate

Uncover demand causal factors that drive fluctuations

PredictHQ idnetifies the aggregate impact of historical events. You can gain access to millions of events from hundreds of data sources into a single API.

More on Aggregate event impact
02

Correlate to discover what drives demand

Identify the relationship between your historical transactional data and the impact of events to establish correlation. This process can take teams months to understand and pinpoint but PredictHQ has transformed that process down to minutes.

How we correlateCorrelation Docs
PythonCurl
import requests

response = requests.get(
  url="https://api.predicthq.com/v1/events/",
  headers={
    "Authorization": "Bearer $ACCESS_TOKEN",
    "Accept": "application/json"
  },
  params={
    "label": "f1",
    "country": "MC",
    "q": "Grand Prix",
    "category": "sports"
  }
)

print(response.json())
03

Train predictive analytics models with our data

Demand intelligence can be seamlessly integrated into your models once correlation is established. You’ll be able to identify the event categories that impact your business the most and train your models to better predict future demand.

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Customer Stories

PredictHQ improves predictive analytics strategies

Learn how customers are integrating demand intelligence into their forecasting models and seeing value.
Customer Stories
Thomas Joseph
Head of Data Science, 
Legion
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

Optimizing prediction based on your industry

Your analytics strategy will define your success and save your team time. Here’s how businesses can use PredictHQ as breakthrough context to update their models.
  • Retail

    Gain insights from demand intelligence to know when foot traffic spikes will occur in the future.

  • Aviation

    Factor in intelligent event data to stay ahead of the booking curve.

  • Accommodation

    Identify demand fluctuations that will impact room availability before they occur.

  • Transportation

    Anticipate demand surges long before they happen with intelligent event data.

    How else can I use PredictHQ?

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