Optimal staffing levels depend on service demand, which is volatile. The problem is complicated by the cost of not meeting service, which can vary by call type. In this article, we'll look at and play with a live monte-carlo simulation of staffing levels in a payment collections department.

Insurance companies (and many other types of businesses) send out large numbers of quotations to prospective customers, and success hinges on encouraging a large proportion of these customers to accept these offers as soon as possible. This article describes an approach we have been thinking about for doing just that.

Response Curves and ROMI

Posted 2013-09-27 15:21 under marketing, data, optimization

When seeing MarketPulse in action, many people have asked me about how response curves work, and what they really mean. In this article, I'll show you a few examples of marketing response curves, and explain how they relate to the real world, and how they reflect the Return on Marketing Investment (ROMI) for different campaigns.

Many businesses send targetted special offers to their customers. Doing this in an optimal way is hard, but valuable. Here is an animated demo that illustrates some ideas around how to optimize the targetting of offers, combining both mathematical optimization techniques (computationally expensive) and rules of thumb (quicker but less precise).

We have developed and applied an effective method of measuring marketing spend effectiveness, which has helped clients identify which marketing activities are and are not working. It requires very little data, and can be accessed over the web.

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