Having just written a post about how vague the word analytics is, I see Ann All’s post Banks Using Analytics to Boost Customer Retention. What’s interesting about Ann’s post is not that she makes it clear what kind of analytics she is discussing but that almost any of the various kinds of analytics can and do help in customer retention:
- Reporting, dashboards, OLAP
Unless the retention of customers is a metric that is tracked, measured and analyzed (using analytics), it won’t improve
- Customer service applications using analytics as a core component
Making the customer treatment/retention analytically enhanced requires thinking of customer treatment applications as analytic applications.
- Segmentation, churn models, retention offer
Using established analytic techniques to analyze customer behavior and come up with detailed segmentation models as well as propensity models for offer acceptance and risk models for churn are essential to turn all that data into real actions that count.
- Analytic workbenches to work the data
Most banks have LOTS of data in LOTS of systems so they will need to adopt analytic tools to manipulate the data and understand it using those analytic techniques
- Executable analytics in decision services
So that every interaction with the customer reflects the retention plan as embodied in the analytic models.
So just because the definition is variable, does not mean you can ignore it.