Home Consumer Value Solutions How Big Data Analytics is Ushering in Next Generation Operations and Business Support Systems

Know your customer. The customer knows more than you.

When it comes to customer experience management, this is, perhaps, the first (and, arguably, the only) rule of thumb. And why not? In a fiercely competitive space characterized by wafer-thin margins and rapid customer churn, telecom operators need all the help they can get. Technologically, of course. Little wonder, then, that these players have taken this approach very seriously. So much so that while attempting to be “always on”, customers are bombarded with multiple deals at the best prices (of course). What makes this exercise interesting is that all these deals are deemed a perfect fit for each customer. In other words, personalized offers in real-time.

But are they, really? Personally, I am of the opinion that having too many choices is what creates challenges in the first place. As a customer, it is just too simplistic to get carried away by an entire plethora of choices. Ironically, being able to choose from this clutter is meant to declutter the minds of customers.

So, what’s missing? Operators, are you providing these options to your customers in time, on time and at the right time? In other words, are you able to capture the moment of truth when the customer is about to make a decision? Or are you just spamming their mobile handset with a whole lot of junk communication?

Now, how does one ensure this, without tracking a customer’s every move? Operators, is sending communication in real-time, whilst offering and collecting feedback and (if necessary) changing your course altogether the order of the day? If so, merely coming up with a solution (in real-time, pun intended) that exercises ones intellect isn’t the answer. What would be infinitely more helpful is a framework that can understand the existing environment on its own, suggest viable outcomes and course corrections. And this is where analytics steps in. The order of the day is an analytics-based algorithmic framework. This can be applied to all of an operator’s systems and processes-right from everyday operations to transactional and capability building.

All well and good, but how does one execute this? Well, for all intents and purposes, analytics would constitute the underlying framework. A self-learning, analytics-based algorithm, it would comply with all existing rulesets and be capable of making forward-looking decisions. Not just that, it would be capable of testing each possible outcome before presenting the most viable of the lot. Wheels within wheels. One algorithm to test another.

The basic principle of this entire exercise is simple. Any data set being examined will yield some outcome or the other, without exception. The key in analytics-driven frameworks isn’t about how smart the algorithm is but how fast it enables one to test the outcomes, by implementing it in an external environment. The actual results are expected to optimize the entire process.

Now, to narrow down the scope. What can analytics do for specific aspects of an operator’s system, namely, billing and transactions, customer relationship management, order provisioning and fulfillment, et all. A lot, actually, all of which is necessary.

Here’s why. Today’s telecom operators are fast waking up to the fact that the transition from a communications service provider to a digital services provider is the norm, not the exception. Easier said than done, of course, since more often than not, these players have to contend with siloed legacy systems. Now, to keep competition at bay, operators are more than aware that the trick is offering a differentiated customer experience. Naturally, then, analytics steps in to save the day.

The basic, underlying idea is to make the operations and business support systems (OSS/BSS) more relevant. This can be achieved by wrapping each component of the OSS/BSS stack in an analytics-driven algorithm framework. The result? Generation of real-time actionable insights, faster deployment of personalized products and creation of viable engagement models that would keep the customer coming back for more.

Sounds like a win-win, doesn’t it? Let’s not forget though, the customer will always know more than you!

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