Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
I have the honour of curating the last of this year’s topic-specific Top Blog Collections. The blogs in my collection all focus on the customer, as we all should(!).
I have been lucky enough to work with and for various customer facing financial services organisations over the years. One of the benefits of this experience is the chance to compare and contrast how these organisations operate. Based on some of these observations, I have sketched out a generalised framework that describes the key functional actions of the modern customer-facing organisation. Meet the 3-I Raven*.
Ever wondered how to calculate the best mix of actions in order to achieve the desired result within budget? You might have a pretty good idea of what mix has worked well in the past, but how much rigour goes into that process? Wouldn’t you like a mathematical approach that eliminates the guesswork?
As a Marketer or Customer Engagement professional, imagine the cost-savings if you knew who in your database or lead list were likely to be the most profitable customers or most likely to respond? Would you bother mailing a list of a million contacts if you knew that only 100,000 of those contacts were worth targeting and very likely to respond? Innovation is not necessarily the invention of something new, but be the result of finding a new use for an existing product, service, methodology or practice. Take the use of predictive scoring in Marketing. Scoring is no longer only about identifying credit-worthy customers, but is now being used by marketers to identify "target-worthy" leads or customers.
The amount of data now available to us is overwhelming: every two days we create as much information as we did from the beginning of time until 2003. As a Marketer, the challenge is determining what data is useful and how to turn it into marketing wisdom that leads to customer retention and growth. Considering that it costs 5 times as much to on-board a customer than it is to retain one, companies would do well to leverage their data to develop and drive retention strategies. In this post, I look at 3 ways data can be used to build and drive customer retention strategies that result in reduced churn rates and open new avenues for meaningful engagement with target markets.