Tuesday, July 26, 2005

The Story




The Story of QF-CRM. How it has been discovered.



Companies Executives always try to make the best possible strategic decisions for maximizing their results. Many factors transform this goal in a really challenging exercise, and when it is related to sales and growth strategy, we touch at the most sensitive point. In our marketing background, we had the opportunity to wonder about questions like:

  • What are the best markets to target now?
  • How much should I invest and when?
  • What will be the return on investment?
  • Which prospects should I address first to optimize the results?

These simple questions are very often very difficult to answer even for the best skilled executive. Our customer’s VP Europe was faced to this situation. We wondered about the fact that if we ware able to use past records of our customer, and some advance statistics and strategy tools, we should be able to help him efficiently.

Our past experience with integrated marketing and scoring methods where largely unsatisfactory in term of targeting, but we were thinking more about a quantitative based approach rather than a pure strategic and traditional portfolio analysis approach.

We then embarked into this adventure of acting as a strategic advisor for our customer.

Of course, our first approach consisted to use the traditional strategic tools that we generally use, i.e. Portfolio analysis, Micro and Macro environment analysis, etc ….

Using this approach was a good start, but the results where not as accurate as we wanted. Furthermore, we discovered that a traditional portfolio analysis based on very few dimensions and variables was somehow a too simplified approach.

We then decided to use some advanced statistics techniques to go further. We used the same mind frame than a portfolio analysis, but with much more dimensions taken into account, much more variables than growth, market penetration and performance. It is worthy of note that some of the variables used where metric, and some where non metric. We end up with about 20 variables compiled from a very broad scope of data:

  • Past CRM records
  • Market records
  • Financial records

During the process of doing it, we made a breakthrough discovery that led to discover a methodology (that we will call the QF-CRM methodology for Quantitative Factor Customer Record Methodology).

We hope that this (short) story make it easier for you to understand the background of the QF-CRM methodology, the very reason of this blog.

 
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