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customer experience management

Penning blogs on customer experience management (CXM) can get tricky after a while. The bottom-line of each piece is simple-a sound CXM strategy can make or break a business.Here’s the interesting bit, though. Equally important factors in the CXM game are the tools of the trade one opts for. There are, without a doubt, a plethora of options to choose from. But which strikes (or is likely to strike) the right note?

Permit me to point out, though, CXM isn’t a “one size fits all” solution. What may work for one customer may not apply universally. In the context of this blog, though, let’s focus on artificial intelligence (AI) and how it ensures customer experience monetization.

Permit me to start by restating-AI is not a generic solution. One simply cannot just implement AI-there are larger implications. While there is, indeed, a large amount of hoopla around AI, let’s not forget, there’s no field tested and proven solution for AI. Every solution, every use case that’s been built so far can only be improved, not replicated. If one chooses the latter over the former, well, they’ve merely limited the possibilities. Therein lies the nub of the argument-the field is yours to prove and implement.

AI and CXM: A Multi-Faceted Equation

There may be a million ways to address this point (and why not, don’t forget, all data provides some outcome!). A very straightforward approach would be thus-AI enables companies to ensure real-time decisioning. How? Well, the data is on hand. Customers haven’t really changed their patterns, except every decision is usually made “in the moment”. And apart from the fact, of course, that the sheer number of decisions has increased dramatically.

So, AI, in a nutshell, enables companies to inject predictability with a fair degree of accuracy whilst dealing with customers. The idea is to see if the likely short term future outcomes of a customer’s actions come to the fore.

AI-Based Use Cases That May Turn the Tide for Operators

As I mentioned before, countless use cases for AI (and indeed, any technology) exist. And are only becoming more intelligent, with the domain shifting constantly. Within the scope of the CXM domain, though, two primary use cases must be focused on, if one is serious about retaining customers, of course.


Leveraging AI Intelligently

This is, to be honest, a bit misleading. Here’s how-the very idea of introducing AI in the CXM domain is to enable operators to compliment the customer’s expectations. To be where the customer is. And so on, of course.

Now, that a clear set of priorities has been defined, the next step is to create a roadmap of how to intelligently leverage AI. Perhaps something on these lines..?


What’s crucial to remember is that AI is directional. Don’t mistake it for “artificial execution”-it can only do so much. It cannot address a challenge. It may offer a leaner, meaner structure for problem solving but one’s still got to execute the same, for best results!

On a parting note, permit me to put it simply, yet succinctly. Focus on breaking the clutter. Focus on customer retention and making the brand. Focus on AI as a tool in your arsenal, not the arsenal itself. For, isn’t the bottom-line providing an unforgettable customer experience?

May 3, 2019 0 comment
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The customer is always right. No longer just part of Marketing 101, the axiom holds more sinister implications for retailers. Especially today, where being “always-on” isn’t just a phrase-it is a business norm!

Permit me to elaborate-today’s customers are an increasingly sceptical lot, a fact that isn’t helped by disruptive forces like mobile devices and social media. Today, the bottom-line, no, necessity is shifting from passive to active brand engagement. And why not? The number of customer touch points is increasingly exponentially. It is thus only logical that brands ought to be where their customers are.

So, coming to the crux of this piece-big data analytics can help retailers achieve this. And lots more. Why? Well, retailers typically have access to a significant volume of data. Generated across the supply chain and at diverse customer touch-points, this data is further multiplied via digital customers and social media channels.

However, retailers will do well to remember that merely aggregating a vast amount of structured and unstructured data isn’t likely to translate into healthy bottom-lines. The idea is to extract actionable insights from the data pile. Of course, this is just the tip of the iceberg. Let’s break down the argument.




How Big Data Analytics is the Ticket

Uncovering Actionable Customer Insights

Big data analytics enables retailers to uncover a mine of information pertaining to a customer’s behaviour and usage patterns. This further enables them to push contextual, relevant and personalized offerings in a timely manner and at any point in the customer’s journey.

This process is usually based on where that customer stands from a behavioral point-of-view. By examining certain factors, such as the amount of time the customer has spent on the network, usage patterns, etc, the retailer can reach out to the customer via an SMS (or other ways) that highlights the latest offerings they can avail of. Moreover, by deploying big data, all of the retailer’s data is turned into actionable and behavioral insights. These are further used to ensure that the appropriate treatment (in terms of marketing) is applied to each customer at the right time. Essentially, big data helps the retailer to “plot” events on a timeline for each customer, which are then analysed and familiar patterns are highlighted, in order to predict the customer’s behaviour.

Ensuring Retailer Loyalty

Big data analytics can be leveraged to examine a retailer’s behaviour. Thereafter, personalized offers and incentivization schemes can be developed, to ensure enhanced and improved retailer loyalty.

Enhancing Channel Productivity

A “top-down” approach is usually adopted, with regard to the sales channel. This implies that targets are identified at the operator’s level and are expected to be absorbed by the channel’s various elements across the organization. However, region-wise analysis of past performance and trends can improve the accuracy of predicting future sales potential and help the operator set channel targets accordingly. The bottom-line is an optimally utilized sales channel, with relevant targets and adequate incentives.

Before one gets carried away, though, it is important to remember that big data analytics isn’t the panacea to all retail-related evils. It will, however, play a significant role in helping brands keep pace with their customers. After all, the customer is always right. It is just a question of pushing the right buttons to ensure the customer stays. Isn’t that the whole point, after all?

August 17, 2017 0 comment
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To incessantly state that mobile money has caught (and held) the imagination of the global payments space is unnecessary. Let’s just jump right in-GSMA’s 2015 State of the Industry Report: Mobile Money revealed that 271 mobile money services were available in 93 countries, as of December 2015. For the same period, 411 million registered mobile money accounts existed globally. To drive home the point further, the report stated that mobile money has done more to extend the reach of financial services in the last decade than traditional “bricks and mortar” banking has in the last century. Duly noted.

This phenomenal success wasn’t achieved overnight, obviously. Quite the contrary in fact-mobile money went through an interesting evolution before it even found a place under the payments sun, so to speak. Here’s how-in the early days, the biggest challenge before mobile money operators was getting their customers enthused about the product. Of course, getting them onboard was altogether a different ballgame. Since then, the ecosystem itself has undergone several permutations and combinations. Even now, the industry is going through a state of flux-what with the fast growing adoption of digital payments and the rising importance of “contextuality” and better user experience.

Equally fluid, then, are the challenges facing mobile money operators. Today, every operator who wants to stay in the game is focusing on minimizing customer churn and ensuring frequent and optimal service usage. So, this, in a nutshell, is where customer experience management (CXM) comes to the rescue.

Traditionally, ensuring consistency and ease of interaction are the first rules of any operator’s CXM handbook. It becomes trickier with services like mobile money-which have, hitherto, never been subject to the rules (or world) of CXM.

Which brings me to the crux of this blog-a multi-pronged CXM strategy for mobile money would do wonders for customer retention and service uptake. Easier said than done, of course, especially since there are no forerunners (none that hit home, at least) in this space. The need of the hour, therefore, is a tool or solution that would help operators leverage their mobile money services to the fullest-not to mention, fill the existing white space!

Permit me to add my two cents. In this case, a CXM tool or solution ought to be a one-stop shop for all things mobile money. It should ideally perform multiple functions that include (but obviously aren’t limited to) educating customers about the service, offering rewards “frills” to customers that stay put, enhancing engagement levels, growing the existing mobile money ecosystem, et all.

It doesn’t end there, of course. Analytics ought to function at the heart of the solution, which, needless to say, would help mobile money operators move several steps closer to what their customers really want.

In short, there is very little doubt that CXM (if leveraged properly) is poised to replicate its success in this space. But, what ought the first steps to achieving this be?

Watch this space for more.

February 23, 2017 0 comment
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There’s no escaping it-customer experience management (CXM) is what makes or breaks a brand. This is especially true today, since telecom operators live in precarious times, with falling average revenue per user and wafer-thin profit margins. To top it all, customers are just itching to jump ship at the first sight of trouble-i.e.-bad customer service. Let’s look at a few analyst statistics in this regard:

  • By 2020, customer experience will overtake price and product as the key brand differentiator-Walker
  • 68 per cent of customers say that they’ve switched service providers owing to poor customer experience-Accenture
  • 95 per cent of dissatisfied customers tell others about their bad experience-Zendesk
  • Customers who experience a positive social customer care experiences are nearly three times more likely to recommend a brand-Harvard Business Review

In other words, operators, please sit up and take notice! A sound CXM roadmap is the secret ingredient that gives your business extra bite. And here are a few more statistics to prove it:

  • According to American Express, one happy customer can equal as many as nine referrals for your business.
  • Maximizing satisfaction with customer journeys has the potential not only to increase customer satisfaction by 20 per cent but also to lift revenue by up to 15 per cent while lowering the cost of serving customers by as much as 20 per cent-McKinsey
  • Customer experience leaders have more than a 16 per cent advantage over competitors in willingness to buy, reluctance to switch brands, and likelihood to recommend – Temkin Group

Now the tricky bit-where do operators start? Well, it’s a two-fold step, really, that begins with proactively tracking down what customers (actually) want. This, in turn, will (hopefully) throw up actionable insights into the challenges related to ensuring customer satisfaction. Chalking out a CXM strategy is merely the most obvious result of the above plan.

So, what makes a customer tick? While there is no single appropriate response to this question, I would like to offer up analytics as a viable option. Here’s why-the age of data is upon us. We collect copious amounts (some analysts say an estimated 2.5 quintillion bytes) about individuals, places, processes, et all, every day. This data comes from multiple sources, such as sensors used to gather climate-related information, posts on social media sites, digital pictures and videos, purchase transaction records, cell phone GPS signals, the list is endless.

Here’s the catch, though. While there is little doubt that the intelligence of our systems is responsible for facilitating this growth, the volume of structured and unstructured data being collected isn’t necessarily valuable on its own. To gain actionable insights, an operator ought to know what to do with this data, how to leverage it to the fullest.

This is where analytics steps in. Before jumping the gun, however, operators ought to be aware of the essential elements of using analytics successfully:

  • Aggregate data from multiple sources. Let’s face it, a multi-tiered approach is essential to gain a 360 degree view of the customer journey. Operators, think Facebook, think Twitter and all the social media platforms out there today. The customer uses these mediums to broadcast their views on every brand. The trick, therefore, is to integrate analytical tools from CEM into social media monitoring to identify customer behavioural patterns. The result? Proactive engagement at every stage of the customer lifecycle!
  • Utilize existing CRM system data: This essentially ensures that data is centralized, accessible and can be used to gain a holistic picture of the customer. Operators need not waste precious time in collecting the same data over and over again.
  • Examine unstructured data: Going forward, data volumes are only going to increase substantially. The idea, therefore, is to adopt an all-encompassing approach, which may have to include complex data mining practises. If carried out proactively, companies can gain a competitive edge and unearth previous unevaluated customer data links.

There’s another catch-operators, please note, analytics isn’t a “one size fits all” strategy. Choose your best fit. Interestingly, the evolution of analytics itself took place over multiple stages. According to industry analysts, in the past, all available data was scrutinized using descriptive analytics, which looks at the reasons behind past success or failure. An example is the results a business gets from the web server through Google Analytics tools. The outcomes help understand what actually happened in the past and validate if a promotional campaign was successful or not based on basic parameters like page views.

The next step (and with the advent of big data) is predictive analytics, which focuses on the question: “What is probably going to happen in the future?” An interesting example of an application is in producing the credit score. Credit score helps financial institutions decide the probability of a customer paying credit bills on time.

Next up is prescriptive analytics, which goes beyond future outcomes to answer the question: “What is the able action?” Interestingly, analytics are taken a step further, with the advent of highly intelligent cognitive systems. Instead of needing to be programmed, they use natural language processing and machine learning algorithms to help make key decisions using huge volumes of fast-moving big data.

Please note dear readers that these four categories of analytics should ideally co-exist. There is no question of one outweighing the other, in terms of benefits, etc; they’re all different, with their own merits. Do remember, though, that all are equally necessary to obtain a complete and clear picture of what a customer actually wants by using all of the available information and data.

I’d like to conclude with a caveat which is that analytics is only as good or as bad as the implementation of the requisite action plan. For analytics to be successfully leveraged, the operator ought to be guided to the actionable tasks which can be implemented. If not, the company runs the risk of “analysis paralysis”, which doesn’t leave any room for any quantifiable outcome. In the end, the numbers say it all!

July 4, 2016 0 comment
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Technology has evolved, as has managed services.In fact, it would be a bit of an understatement to say that it has undergone several permutations and combinations over the years.

Shall we briefly step back in time? The good folks over at BlackPoint IT Services have provided a concise timeline-in the 1990s, managed services was, in a nutshell, a crisis-based, break/fix service. Deemed unpredictable, it relied on reactive support. Moreover, providers mostly used ad-hoc tools and had little or no documentation handy. At the time, most managed services contracts were billed on a “time and materials” basis and presented an unpredictable expense for businesses.

Perhaps most importantly, at the time, every service offered by any managed service provider entailed a service level agreement (SLA). Simply put, this meant a team of experts were always on-hand to resolve any network-related issue. The bad news was that if SLAs were breached, a percentage of the managed services providers’ monies was cut. Net, net, the managed service provider’s role largely entailed end-to-end management of the client’s telecom network and reduction of cost through sharing of monitoring resources, etc.

Now on to the early 2000s! Things hadn’t changed to a very great degree back then, managed services moved towards scheduled visits, where technicians would log reviews and fix any issue a customer may face. Moreover, servers started to be hosted in co-locations and a flat-fee structure was introduced with testing and measurement billing. And, key performance indicators (KPI) came to the fore, which in turn introduced the concept of “service management”, as opposed to “network management”. In other words, this meant end-to-end performance of every telecom service would be measured and monitored proactively to ensure the service performs at the highest possible level. So, basically, as opposed to ensuring the network is up and running in the first phase, a managed service provider would focus on ensuring each and every service wasn’t merely functioning at optimal levels, but at certain pre-defined levels.

For the sake of greater clarity, the best example of this is the 99.9999 per cent service uptime. This, as we all know, is amongst the most common service level KPIs. Other KPIs,of course, include change request management within a specified period of time, reduction of time taken to launch a new service launch by a certain percentage from the current time, etc.

Permit me to add a final word to this section-during this time, managed services still merely provided single-day visibility without any preventive or proactive maintenance.

So, where does the managed services domain stand today? Well, managed services, as we know it now, is able to utilize many more robust tools such as spam, compliance and security management (just to name a few). Indeed, every company is currently operating in hybrid environments, supported by managed monitoring alerts and remedial tools. Given today’s cut-throat competitive environment, it isn’t surprising that ensuring managed business continuity is now considered the bottom line for any business.

Now, permit me to introduce an interesting angle. Today, a managed service provider isn’t just that-a managed service provider. Their role has expanded to functioning as a “managed services partner” for the operators they service. Simply put, certain pain-points faced by an operator-i.e.-revenue enhancement and ensuring an enhanced customer experience (just to name a few) become the bottom line for not just the operator but the managed service provider as well.

So, why this paradigm shift? Well, operators today are faced with a plethora of challenges-saturated voice revenues, wafer-thin margins and cut-throat competition. In this scenario, they are, needless to say, seeking methods to enhance value and benefits to their business. Therefore, as per industry analysts, typically, a business model that is not only based on financial savings, but also on creating sustainable business differentiation is the key. Why? To stand apart from the competition, of course!

Net, net, it all boils down to customer experience. Now, customer experience is a tricky area to navigate. In a nutshell, the idea is to create differentiated experiences at the different touch-points the customer chooses to interact with the operator at. Needless to say, a sound customer experience strategy offers the operator multiple benefits-namely enhanced customer satisfaction, reduced churn, incremental sales, etc. And this is just the tip of the iceberg.

So, what role can managed service providers play? Well, managing customer experience across multiple touch-points is a very tall order for any company. After all, all the elements involved, from advertising campaigns to post-purchase support play a very important role and must be treated with caution. This is where managed services come in. Industry analysts are of the firm opinion that the experience-centric managed services model focuses on customer expectations and demands. Thus, aligning service delivery in accordance with these requirements is, needless to say, a must. The experience-centric managed services model aligns service delivery with the operator’s strategic and business objectives, securing a customer experience centric operation that proactively drives business innovation.

Amdocs has presented a few interesting thoughts in this regard. First off, improving customer experience through managed services starts with mapping the customer experience related processes, the underlying systems, integration touch points, and the measurable impact on the end customer.

Now, here’s where it gets a bit tricky-translating the aforementioned factors into tangible KPIs and service level targets that the managed services provider can be held accountable for.

In a nutshell, this can be achieved via these key steps; identifying desired business outcomes, identifying customer experience impacts and operational goals, building KPI models, defining performance targets and commitment periods, developing service level improvement and optimization plans and monitoring, measuring, and reviewing.

And, what will these steps achieve for the operators? Well, for one thing (and this IS the bottomline, really) customers can expect increased reliability, improved quality, enhanced choice and accelerated innovation and time-to-market.

In a nutshell, this is by no means an exhaustive account on the link between managed services and enhanced customer experience. I would like to summarize, though, by saying that today, customer loyalty is at the top of every operator’s priority list. Therefore, placing a premium on a consistent continually improving customer experience at every touch point isn’t a giant leap. Managed services can help (amongst other things) ensure accountability at every stage of the customer’s lifecycle. Remember, though, (and this may just be my next blog), choose the right partner! It makes all the difference!

March 22, 2016 0 comment
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Without a doubt, the rapid growth of the global telecommunications space seems perfect on paper. Sample this-according to data released by GSMA Intelligence, the total number of mobile connections (including Machine-To-Machine) worldwide stood at 7,747,629,404 (and counting!) while the number of unique mobile subscribers stood at 3,819,504,999 (still counting), both as of the first quarter of 2016. Meanwhile, revenue per year (for financial year 2014) stood at a staggering $1.06 trillion, a 1.99 per cent year-on-year growth.

That, in a nutshell, represents the overall (extremely rosy) picture. Now, let’s examine a few parameters more closely, beginning with a trend that has somewhat recently reared its head and thrown the old order into a tizzy. I allude, of course, to the number of SIM cards per unique subscriber, which has been growing steadily every quarter. Again, as per GSMA Intelligence, in the fourth quarter of 2014, each unique subscriber across the world had 1.80 SIM cards. This number fell to 1.79 from the first to the fourth quarter of 2015, to reach 1.80 once again in the first quarter of 2016. Going forward, the firm has predicted that this number will remain steady, at least until the second quarter of this year. Thereafter, it is expected to rise to 1.81 in the third quarter of this year, where it will remain until the fourth quarter of 2017. (Actually, it is expected to remain at this number beyond this period as well but that would mean going well-beyond this blog’s frame of reference. So, let’s put it on the back burner for the present).

Next up, let’s look at the minutes of use (MoU) per connection worldwide. Now, this parameter has showed an interesting, if somewhat skewed trend. In the fourth quarter of 2014, it stood at 287 and then marginally dropped to 286 in the first quarter of 2015. It then spiked to 292 in the second quarter of 2015. Likewise, the average revenue per user (ARPU) per subscriber displayed similar attributes. It stood at $20.25 in the fourth quarter of 2014 and then continued to marginally decline. In the first quarter of 2015, it fell to $19.76, rose somewhat to $19.95 in the second quarter of 2015 and then reached $19.98 in the third quarter. Then came the fall-specifically to $19.82 in the fourth quarter of 2015 to $19.58 in the first quarter of 2016. And finally, perhaps an operator’s biggest nightmare-churn rates. Though GSMA Intelligence remains relatively tight-lipped on the subject, they have mentioned that churn rates stood at 3.22 per cent in the fourth quarter of 2014. After that, well, it’s anybody’s guess, really, but I reckon the number would be roughly in the same range, give or take.


Now to throw a spanner into the works. The idea of bombarding you with data wasn’t to provide a ready reckoner of the inside workings of the global telecom sector (though that never hurts!) It was merely done to point out that the telecom space is a bit of a paradox, really. Why I stated that the sector is performing well on paper is that while there is little doubt that operators are raking it in, let’s not ignore the fact that parameters like SIM usage, ARPU, MoU and churn rates have a different (and perhaps less pleasant) story to tell.

The very existence of the multiple SIM card trend, for instance, is testimony to this. If we examine the trend at the grass-root level, it boils down to this-industry experts agree that the prime motivation for using multiple SIM cards is to take advantage of inherent price differentials across competing operators in domestic cellular and roaming scenarios. Breaking this theory down further, needless to say, this is most prevalent in emerging markets, where customers are typically more price sensitive. So, obviously, the most lucrative opportunities for price arbitrage are because of on-net and off-net pricing.

The bottomline is this: operators, please sit up and take notice, a customer may be registered on your network but may not be using your services at all! In other words, you may have the number to boast of but the fact is that a part of your revenue is being “leaked” onto your rival’s network, by virtue of the customer using multiple SIM cards!

What’s an operator to do in this situation? Well, one way to go is to pull out the big guns to maximize the share of spend across a single individual’s multiple cellular accounts. This approach will serve to plug any revenue leaks. The inherent problem with this approach, though, is that price no longer holds the pride of place with which competition can be kept at bay. Well, to a fair extent, at least. This brings us to the other (and, in my opinion, the far more interesting way) to hold onto the customer.

Operators, a viable way to keep customers hooked onto your network is to build the right value propositions to mitigate the practice of holding multiple SIM cards. How? By focusing on providing a fair mix of the all-important elements of quality of experience and services, coupled with the services bouquet itself.

Easier said than done, of course. Which brings us to the crux of the piece-what role can customer experience management (CXM) play to help? Well, first things first-telecom operators, please move away from offering limited products and services through limited channels. The first rule of understanding what CXM can do for your business is developing more sophisticated and personalized offerings, which ought to be delivered and serviced through multiple channels. This will help assure the customer your brand is omnipresent and is willing to lend an ear to what they have to say.

Next, let’s dwell on the importance of a multi-channel CXM strategy. The keywords to focus on are these-consistency and ease of interaction. There is (and as customers ourselves, I am sure you will agree) nothing more frustrating than having to having to wait for minutes (yes, really) to contact a customer care representative, or having to contact the same company for the same query over and over again. You just lost a viable customer, dear operators! Not all is lost, though; just ensure you’re listening to your customer very carefully. Once you get a sense of what they need, it’ll be easier to anticipate their demands the next time around. Now THAT is CXM at its best!

Of course, it doesn’t end there. Besides the assurance that your brand is “always-on”, the availability of real-time services is a brand’s trump card. Today’s customer expects, no, demands, a brand to deliver convenient and immediate services. And, naturally, this brings us to the importance of self-service. Simply put- enable your customers to carry out transactions like purchase additional data, pay bills, update contact details, or their plans or handsets-immediately of course-and enjoy the benefits of having implemented a win-win proposition-i.e.-customer stickiness, reduced cost and churn, increased sales and reduced usage of call centres.

To sum up, this is by no means an exhaustive list of the best ways to leverage CXM. Indeed, it isn’t even the tip of the iceberg. Though, while we’re on this note, may I please add that by all means, go ahead and leverage CXM the way best suited to your business requirements. Don’t forget, though, pointers like those given in this blog are mere theory-you will need a long-term strategy that is clearly defined and well-researched. Add to that a focus on the customer’s journey (in an end-to-end manner, of course) and you’re good to go!

February 17, 2016 0 comment
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