Proactively manage Customer Churn - in Real Time

They say Change is the only constant in life. Having been reduced to a cliche (being quoted by every other guy), it is still an eternal truth. Hence, it is but natural that all businesses should expect their Customers to also look for change, and consequently, Customer Churn should be an equally prevalent truth that you cannot wish away.

True. But the question is - how much is tolerable? What can your organization do to slow down the churn rate? What is customer churn doing to your business? Are you even aware of exactly what is your Customer Churn rate?

Unfortunately, the above questions - though most critical from a business standpoint - go unanswered in most business situations. If you want to do something about retaining your customers, thereby augmenting your growth journey of acquiring new ones, then its time you took a hard look at the numbers applicable to your business.

Managing Churn traditionally:
Having said that, I still come across a few organizations who are doing precisely that. They have sophisticated systems, data warehouses and business intelligence tools that not only tell them broadly how are they doing on customer retention front; but also slice and dice the numbers and generate 'customers most likely to churn' report. This way the business leaders expect to take preventive steps and retain those 'high risk' customers.

Obviously this step comes at a much later stage in your business evolution - the earlier steps being customer identification, segmentation, customer need categorization, customer satisfaction indices, developing parameters & metrics to generate trends on satisfaction, and only then building the early warning systems that signal the 'likelihood' of customers at risk, should the appropriate trends show a deterioriating business relationship in one or more dimensions.

Managing Churn dynamically:
However, given the rapidity with which the scenarios are changing; focused activities by competitors to grab your share of the pie; and the quantum leap in the enormous number of customer transactions that take a phenomenal time if bulk processed for all customers; the frequency of generating the 'at risk' report usually lags behind and the opportunity to take structured preventive steps gives way to the 'fire fighting mode' of saving customer situations.

This is where the pioneers in their respective industries have begun to move towards 'real time predictive analytics'; solutions that allow most appropriate handling of customer interactions taking into consideration the 'propensity to churn factor' right there, in real time, for one interaction at a time.

Say I am a frequent flier of ABC Airlines, and have not flown with them for more than a month, but I have called in a couple of times in the period to enquire about schedules & fares, and I have still failed to make any bookings; then ABC Airlines MUST treat me a bit differently and innovatively when I call in the next time, in 'real time'. And they will be able to do so if they invest in the right analytical tools. Technically similar to the cross-sell / up-sell routine, the power of retaining me in real time will give significantly higher returns to the company's bottom line.

This will be much more powerful than sending out an email 'post haste', after two months, politely pointing out that of late they did not have the opportunity to welcome me aboard.

And if they are able to leverage the predictive analytics in real time, then they would have experienced the power of the change axiom - I would not be an 'at risk' customer, for a change !!

Tags: