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Predictive Analytics, Getting Started

Dec 15

Written by: Angela Waner
12/15/2011 11:50 AM 

StatSoft, like many companies, asks customers to complete a "satisfaction survey." One customer mentioned me by name in a recent survey. They said "PM Angela Waner was great!!" Positive feedback is always nice to receive. It made me smile.

The customer, an insurance company, purchased predictive analytics software with services for "Getting Started With Predictive Analytics." This type of project is fairly common right now. It seems like everyone is interested in using predictive analytics.

 

 

Quick definitions...  
  Forecasting uses data from the past to discover trends that may be true for the future. For example, your sales revenue ($$$) is an input variable into the "forecast analysis" for next month's sales. This works with a system that has consistent trends over time (time series data).
   
  Predicting uses any potentially relative data as input variables for the analysis; internal sales variables, economic numbers, demographics, top 500 stock prices, road construction projects, frequent buyer club data, etc. For example, your sales revenue ($$$) is an output variable (predictor).

 

During the sale process, we worked with the customer in generating a "Statement of Work" that described the services and the project's objectives. All of our "Getting Started With..." packages can be thought of as a bucket of hours. They include a combination of statistical consulting, training, custom development, and software installation services.

The work for the insurance company was split between:

  • 10% - custom installation
  • 25% - training
  • 65% - consulting (predictive/statistical)

We provided:

  • custom installation for client/server environment
  • documentation on the installation steps
  • training for IT on the installation process
  • onsite and web training on STATISTICA (buttonology)
  • data mining consulting for a specific data set and problem
  • "workshop based" training based on the completed consulting project
    • students walked through the steps used to generate the results and why different options were or were not used

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