CATEGORY: nullam-sed

  • Customer segmentation – RFM technique

    June 11, 2015 | Author SpringML

    The RFM customer segmentation model is a simple way to segment customers.  The resulting segments are easy to understand and helps marketers target campaigns better.  R, F, and M stand for (from Wikipeida): Recency – How recently did the customer purchase? Frequency – How often do they purchase? Monetary Value… [Read More.]

  • Customer segmentation – combining RFM and predictive algorithms

    June 10, 2015 | Author SpringML

    The Recency-Frequency-Monetary value segmentation has been around for a while now and provides a pretty simple but effective way to segment customers.  An RFM model can be used in conjunction with certain predictive models to gain even further insight into customer behavior.  In this post we’ll discuss three predictive models… [Read More.]

  • AzureML model for customer segmentation

    May 31, 2015 | Author SpringML

    As mentioned previously, we are approaching the customer segmentation problem holistically with a view to provide an end to end solution.  This end to end solution comprises of three components. Data preparation and enrichment. Any complex enterprise landscape comprises of multiple systems, each performing a specific function.  There could in fact be… [Read More.]

  • Customer segmentation – RFM technique on big data using Google Cloud Dataflow

    May 31, 2015 | Author SpringML

    We are quickly becoming big fans of Google Cloud Dataflow.  See our previous posts on this topic here and here.  We are excited to continue using this product and creating analytics solutions for our customers.  In this post we are going to describe how RFM technique can be applied on… [Read More.]

  • Customer segmentation

    May 31, 2015 | Author SpringML

    Consumers, customers, clients or users.  Call them what you will, but businesses exist and grow only when they can serve them well and attract more of them.  While there are several business strategies that one employs, one key methodology is to group or segment similar customers based on past purchasing… [Read More.]