InsightIQ Blog

Customer Analytic Visualization

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Jun 14 2010

Customer Analytics in many environments provides significant competitive advantages, which culminates in minimizing waste / costs while maximizing revenue.  Many times one of the largest barriers in analytic adoption is the lack of understanding of the analytic outputs, which hinders the proper strategic application of the analytics - both short-term and long-term.

Questions that must be answered before properly applying the analytic assets include:

  • What are the model scores and what do they represent?
  • What are the segments and what are the inputs into each segment? 
  • How are the models and segmentations related? 
  • How can we overlay other customer data (tenure, demographics, geography, etc.) with the models and segments? 
  • What are the segment and universe sizes?    

These questions and others are typically difficult to answer, in proper business terms, without significant cross education between the data, analytic and business teams.

I have found that a customer visualization solution is one of the best ways used to translate the analytic assets into simple business terms and we at Quaero use a solution called ValueWatcher.  We ‘score’ the customer base periodically with all models and segmentations, layer in additional customer data, and load all the data into the solution.

Beyond its use as a vehicle to cross-educate the analytic and business teams, ValeWatcher, and other customer visualization tools, provides additional advantages including:

  • An enabler for the business to dynamically profile segments of their customer base.
  • A means to visualize the value of the customers as a whole, as well as segments of the customer base. 

The example below includes both a profitability model and customer experience score on the Heatmap.

ValueWatcher

ValueWatcher

If you are interested in learning more about ValueWatcher and/or Customer Analytics, please feel free to send me a note or post a comment.

 

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