Jacob N George Global Director - Analytics & Research
Jacob is an experienced consultant and business leader with a record of success in enabling automotive manufacturers and suppliers improve their Quality and Customer...
Conceptually this is a simple three-step process. However, in practice, there are nuances and best practices that help make this process add more value to a marketing and communication strategy.
We would love to hear about your experiences with segmentation and also share what Endeavor has learned through many years in this field.
Intuitively, most managers and analysts know that patient and customer segmentation is critical to drawing out insights from preferences and behaviors. After all every customer has different tastes and expectations. Given that it is impractical to treat each customer differently and, also that one needs a way to cater to new customers, it is helpful to group customers into segments and tune practices to their segment’s preferences. This helps with overall patient recruitment, experience and retention. However, before leaping into the process of customer segmentation, it is valuable to think about segmentation in three steps.
One of the most common statistical tests to compare segments and groups is the t-test to compare the means of two groups, which can also be used when not all the population parameters are known. A Z-test is also useful to determine if two populations’ means are different provided the variances are known and the sample sizes are large. ANOVA (Analysis of Variance) techniques can be used to analyze the difference between the means of more than two groups, or the impact of one or more factors by comparing the means of different samples.
There are a multitude of other analysis techniques, but most of the time, if the data sources and typing have been carried out well, the differences between segments should leap out with simple observations, and subsequently be confirmed with the above statistical tests.
The three steps above are more intuitive when analyzing with fewer factors and specific instances (e.g., how should a hospital design service to better serve a minority population by understanding what they prefer in doctor-patient interactions). However, this approach can get more complex when many factors and multi-dimensional experiences are involved (e.g., designing an overall healthcare system to cater to many different customers from awareness to experience to retention).
Nevertheless, the marketing managers’ jobs are made easier by focusing on these three aspects: selecting the right data sources, using the right classification tools and performing the best differentiator analyses. This will aid in insight generation and action planning for marketing.