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Use cases for Automated Time Series?

Use cases for Automated Time Series?

We have automated time series on our roadmap and would appreciate some example use cases. We know AutoTS can be useful for making predictions in retail sales, housing prices, and equipment failure. Can you elaborate on these, and identify some additional use cases?

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6 Replies

@Davydov - Looks like you had this question in a few different places. I see @Clifton provided a great reponse over here.

Hi! Could you please tell me where I can find the full list of Time series forecasting methods that Datarobot has?

Problem: A FinTech uses AdWords (e.g. good car loan, minimal interest loan etc) to attract new loan applications. However, they could find it hard to know which AdWords are driving sales, or what should be optimal bid price for each AdWord. 

Solution: Using daily activity data for each AdWord (e.g. impressions, clicks) and sales, you can use DataRobot to find the associations between AdWord activities and sales. For example, it can find delays between customers seeing an advertisement and then subsequently making a purchase.



>>Marketing - Predicting Google AdWords bid prices, marketing attribution

might you have an example of this that you can please share?

Great examples thanks!
DataRobot Alumni

Additional TS use cases below:

  • Aviation - Predict frequent flyer points balance, demand for flights
  • Energy - Predicting electricity demand
  • Entertainment - Predict visitor number
  • Finance / Oil&Gas - Predict commodity values
  • Healthcare - Predict the outbreak of a disease (e.g., Zika), patient health trajectory (5 years out), emergency / patient visits
  • Insurance - Predicting the number of contracts and claims over time
  • Investments - Predicting unemployment rates, market indices, stock or market volatility
  • Manufacturing - Predicting production output, sensor values outside limits, machine failure
  • Marketing - Predicting Google AdWords bid prices, marketing attribution
  • Restaurants - Sales prediction per restaurant
  • Retail - Sales prediction per product/store
  • Telco - Predict cell (or service) usage, capacity planning
  • Utility - Demand prediction (gas/electric)