When Analytics Is the Answer Are You Asking the Right Questions?

Depending upon what you read, who you follow, the Business Intelligence and Analytics (BI&A) market is valued anywhere from $16.9 billion in 2016, to $41.5 billion through 2018, and expected to exceed $60 billion by 2025. It’s a huge, growing, global market fueled by ongoing innovation and seemingly endless opportunity. But why now? Why is the market potential so huge? What is making analytics the new in-crowd?

Analytics as defined by Deloitte Analytics in their report titled The Analytics Advantage: We’re Just Getting Started, is the practice of using data to manage information and performance, and has been around for at least 30 years, guiding cause and effect scenarios in almost every industry, any size business.

Until recently, analytics in business communications has been known as reporting. It has been buried in individual communications applications throughout the enterprise. To find out how successful an outbound dialing campaign was, run an outbound dialing report. To determine how many customers opt out of the IVR after 6 p.m. on a weekday, run an IVR report. To determine the quality of all the video conference calls employees hosted last month, run a video report. To determine any security issues in the network, run a report. All of these various reports are separate and typically require different skillsets to run them.

While these reports are full of all the intelligence ever needed about that one specific application, if you want a view of what happened across an entire omnichannel, multitouch journey (voice, self-service IVR, social, email, SMS, online, in-store) during a specific time period, someone will have to manually source, compile and sort all of that data for each separate touch point first. In other words, if you need the information on Tuesday, it will not be compiled, analyzed and put into a consumable format until Friday at best; most likely it will be Monday evening. And this is 2016.

As recently as last year, investing in the right analytics application finally became a priority for any size business, not a nice-to-have. In fact, Gartner reports that by 2018 more than half of large organizations globally will compete based on advanced analytics and proprietary algorithms. By 2020 predictive and prescriptive analytics will attract 40% of enterprises’ net new investments in business intelligence and analytics. Yet, only 50% of the chief analytics officers will have gotten it right.

Meaning, the rush to deploy analytics is overshadowing having a clear understanding of exactly what the business wants to accomplish with analytics. First understanding what the business is trying to accomplish determines which vendor and which analytics application are best needed to meet the objectives.

In my experience, most businesses that are making analytics an urgent investment are doing so because they want to be better positioned to (1) compete more successfully and (2) grow their business to increase revenue potential. In manufacturing for example, analytics becomes an urgent investment when companies need to analyze their processes and operations. Process data is not just for tracking purposes, it’s also for improving operations. When operations can be improved upon, business can improve.

In business communications, we look at two distinct groups: internal employees and external customers/partners. The first question analytics helps us address is: Are these groups getting what they want when they want it? The second question is if they are not getting what they want, when they want it, how can we fix it?

When they are getting what they want when they want it, then internally individual and team productivity should be up, processes and operations should be streaming along and efficient. Overall company performance should be at its peak. Externally, customers/partners should be happy and loyal. It’s about the experience—employee experience and customer/partner experience—people have when they interact with the company. It really is that simple. But getting there is not so simple, which is why analytics is needed.

Ironically the need for analytics is more visible in established companies. Companies that are established have typically passed the hurdles that most start-ups face: running out of funding, being squeezed out of the market by the competition, disappearing signs of growth, unable to pivot for survival in an unstable economy, etc. An established company can be a couple years new or 100 years old. Established companies typically have an enterprise infrastructure that has evolved over time into a complex system of un-integrated silos of solutions. Some of the solutions have been consistently upgraded while others have been barely maintained, yet others have been completely abandoned and need to have all the data migrated to somewhere accessible. Most established companies need to undergo a full transformation to be current and enable the company to utilize analytics effectively in order to compete.

Digitization of the Enterprise and Analytics

One of the most talked about transformations today, is digital transformation. With the digitization of the enterprise, the expectation and realization is that everything can be integrated and made to run faster and more efficiently. Once the enterprise is digitized, there is no longer a need to have separate reporting functions for each communication. Those reporting functions buried inside each application will be able to feed the right information and right events into the single, enterprise-wide analytics application. Aristotle said it best, “the whole is greater than the sum of its parts.” In our case, the holistic view is considerably more valuable than compiling a bunch of individual reports.

With a single analytics application it becomes much easier to have a single view into the entire journey—of customer data, partner data, employee data, process data, etc., no matter the channel(s), external or internal medium(s), system(s) or platform(s). Rather all data will feed into what’s called a data lake, which aggregates raw data in multiple formats. From the lake, the data then gets sourced into the four analytics buckets: descriptive, diagnostic, predictive and prescriptive insight.

  • Descriptive Analytics uses data aggregation and data mining to answer the question: ‘what has happened?’

  • Diagnostic Analytics is defined as a look at past performance to determine what happened and why. It answers the question: ‘why did it happen?’

  • Predictive Analytics is the ability to look at current trends within the business and project into the future what to expect based on those trends. Or, it can analyze data with a particular goal in mind and provide the probability of attaining that goal under current conditions. It answers the question: ‘what could happen?’

  • Prescriptive Analytics is defined as the ability to advise a variety of future actions and guide the user toward a solution. It answers the question: ‘what’s next and why?’

Each bucket of data can be further sourced to learn the journey and gain insight into how successful was the experience with the business during any event or action. Finally, a single view of everything is possible.

Internet of Things and Analytics

Gartner predicts that by 2020 there will be 25 billion Internet-connected things that will produce close to $2 trillion of economic benefit globally. Such a sizeable impact deserves a mention, especially since the value of connecting something to the Internet is to have the data generated by the connected unit consistently analyzed.

From an enterprise perspective, the leading verticals utilizing Internet of Things (IoT) are manufacturing and utilities. In 2015, it was estimated that the manufacturing sector has close to 307 million units considered IoT and the utilities sector had about 300 million IoT units. The retail sector is not far behind.

The IoT is actually the enabler of the Internet of Everything. These are not interchangeable concepts. While the IoT is units connected to the Internet, whether those units are cars, smart meters, or manufacturing sensors, the Internet of Everything (IoE) is the technology connection. The IoE provides the security, software-defined networking, unified communications, analytics, application-aware networking, database federation and mobile experience. The digitization of the enterprise is the foundation for IoE which is why digitization is so important for companies to stay competitive.

Fourth Industrial Revolution

Just as steam and mechanical production changed the world in the First Industry Revolution, then electricity and mass production changed it again in the Second Industrial Revolution, and IT and automated production changed it again in the Third Industrial Revolution, continuing to technologically innovate is again changing the world. As we continue to innovate—continue to improve technology—changing the world becomes not only more noticeable but also more realistic.

When we talk about the Fourth Industrial Revolution, the World Economic Forum describes it as: a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. What we’re talking about is the power of technology to change how we interact with each other, how we interact with objects, how objects interact with each other, how we work, how we play, how we grow as individuals and as a civilization. Answering how is the role of analytics.

The improvements we’re making with technology are very focused on making everything and everyone smarter. To become smarter requires ongoing analysis inside the technology itself and outside the technology constantly examining the environment around it, how we interact with it and react to it.

Why is analytics the new in-crowd? The ability to apply analytics to anything and everything in the enterprise is at the core of the Fourth Industrial Revolution. Analytics is now at a point where it can be the brain of the enterprise which is why it needs to be thought of separately, as its own application. Analytics allows human beings to be smarter, act faster, evolve and grow. Analytics is something that can be controlled to automatically make everything around us better.

Getting there is a journey. Like every journey the outcome is better with a destination in mind—getting stakeholders what they want when they want it. For a number of reasons described above, analytics has a very important role in enabling business to progress, compete and succeed. Whether you are a Bayesian or a connectionist—though both equally important and interesting–what matters most when investing in analytics is first to understand your business, its needs and its challenges.

Related Articles:

Avaya Predictions for 2017 Services Trends: Top Focus is on Smart Customer-Centric Engagement

Recently, we asked six Avaya services experts to help us reflect on the past year and to peer ahead into 2017. Our panel:

  • Richard English, Managing Director, Avaya Professional Services
  • Camille Lewis, Product Management Director, Avaya Client Services
  • Barbara Sidari, Customer Engagement and Executive Cadence, Avaya Client Services
  • Thomas Brennan, Vice President of global support services, private cloud and managed services delivery
  • Michael Sale, Director Online Engagement, Avaya Client Services
  • Dan Pratt, Senior Director, Business Transformation and Strategy, Avaya Client Services

According to our six experts, our predictions for these 2016 trends proved to be spot on—and they will continue to be a force in 2017:

  • Use of hybrid/private cloud

    will continue to dominate for large enterprises until public cloud providers can demonstrate that compliance to privacy/security regulations such as HIPAA can be achieved. However, Public Cloud is quickly becoming a flexible and effective delivery model for the midmarket.

  • A flexible delivery model

    to achieve growth in modular steps that helps IT maximize ROI and support rapid business scaling has been, and will continue to be, extremely successful. Taking some of the burden off the enterprise enables IT managers to focus on more strategic corporate initiatives.

  • The need for person-to-person human touch

    will continue to rise. It will become critical in 2017 as unassisted support and self-healing systems grow smarter in identifying trends and problems before they happen and engage in machine-to-machine maintenance for resolution. The use of video will be more widely used, providing personalization and higher customer satisfaction.

The panel thinks that 2017 will mean an increasing focus on smart customer centric engagement when it comes to service. In 2017, it’s all about using analytics and even smarter technology to increase customer satisfaction (CSAT) scores, loyalty and revenue—and to achieve a better return on investment.

The Avaya panel sees these three trends emerging in 2017:

  • Transforming legacy systems and increased customer use of omnichannel will streamline the customer journey to increase customer satisfaction, loyalty and revenue.

    For example, many retailers will transform their Contact Centers into profit centers. The shopping experience for their customers starts on the mobile device or web-based applications—retailers want it to end with an order placed. The customer will experience a seamless transition from mobile to voice (or to web chat or video) without having to repeat who they are and what they want to purchase. The agent will already know the value of the customer to their company and will provide a personalized shopping experience.

  • Analytics, Internet of Things (IoT), and big data will enhance the experience of the Customer Journey.

    The predictive and preemptive active workflow will match people to people, machine to machine, as preferred by the customer for maximum satisfaction and profit. For instance, service vendors will use data captured from customer service requests, alarms, outage history, and project volume to identify risks and take appropriate actions to proactively mitigate issues. Utility companies can leverage web-based applications to proactively communicate to customers the status of affected service areas via maps on smart phones, reducing the burden of customers calling the service center to report an outage. Similarly alarm companies will analyze alarms and preemptively fix them before the consumer arrives home.

  • Demand for holistic application service management will grow as siloed and disparate cloud applications shift focus from managing assets in the field to delivering on business processes.

    Enterprises will need a dashboard that provides a single pane view by business process vs CPU performance. The workforce needs to be trained to leverage all the data in a way that includes human touch.

The year 2017 promises to be very exciting as service transforms and demonstrates its value by preemptively fixing issues before they become problems. It is imperative that knowing the customer and providing what they want, as well as the human touch, will become ever more critical in a big data world. After all, it’s all about the customer experience!

What do you see emerging in 2017? Drop me a note at sithomso@avaya.com

Leveraging Big Data to Fine Tune Customer Experiences

Whether you realize it or not, big data is at the heart of practically everything we do today. Billboard companies, for example, are now leveraging eye tracking and traffic pattern analysis to gauge interest among drivers. Chances are one of those drivers owns a 4G-enabled vehicle that can track such things as performance and maintenance history. That person can also now record and analyze their utility usage via smart home solutions—anywhere, anytime. On a more critical level, doctors can now record and analyze patients’ heartbeats and breathing patterns to develop life-saving predictive algorithms.

In today’s smart, digital world, big data has opened the floodgates to never-before-seen possibilities. It has the power to course-correct potentially devastating outcomes, and it’s become a necessity for continually refining the customer experience. If you ask us, though, the best customer experiences today are supported by customer journey analytics.

The Need for Customer Journey Analytics

Customer journey analytics is a process that requires tracking and analyzing the way customers use a combination of available channels to interact with an organization. These channels range from human interaction (like speaking with a contact center agent) to fully automated interactions to assisted service (like live chat and co-browsing).

The need for customer journey analytics is simple: data solutions of the past simply won’t meet the next-generation customer needs of today and the future. Consider that just 10 years ago, channels like Web chat and social media were in their infancy (Facebook had only been around for two years). At the same time, the world’s first smartphone had only been on the market for one year. A lot has happened to transform the customer experience in a very short amount of time. As companies move forward in today’s age of rapid tech innovation, they must be armed with the right data strategy.

As mentioned, customers today use a vast number of channels and devices to interact with the brands they love. Each channel and device offers its own set of diverse scenarios for linking to other channels and devices, making no two customer experiences the same. Companies must be able to understand customers’ actions on any given channel or device in order to infer insights and create anticipatory engagement at the individual account level. For instance, why did one customer choose to purchase a product in a retail store verses online? Or, why did a customer end a live chat session before his or her inquiry was handled?

This level of understanding requires a comprehensive view of the data gathered from all channels and interactions that proceeded the moment in question. Customer journey analytics is a process designed to provide this comprehensive view and deliver deep benefits organization-wide—so much so that 60% of all large organizations are expected to develop customer journey mapping capabilities by 2018, according to Gartner.

Making Customer Journey Analytics Work for You

Companies need a data-driven customer approach to survive—and it needs to be effective to thrive. Many companies, however, struggle with taking their customer data and turning it into actionable results. In fact, a 2015 study conducted by PwC found that 43% of companies obtain little tangible benefit from their data, while 23% derive no benefit whatsoever.

To effectively apply your data, you must first determine what you wish to achieve with your data in the first place. In other words, what key objectives do you hope to achieve or improve upon by using big data (or specifically, customer journey analytics)?

Not sure? Here are four core initiatives to start you on a path to maximize your customer journey analysis efforts:

  1. Enable self-service.

    Self-service options—especially mobile—are rapidly increasing in popularity. Just consider that in 2015, Apple users downloaded over 51,000 mobile apps per minute. Also last year, 90% of customers used their smartphones in stores to make price comparisons, research specific products, and check online reviews.

    In today’s mobile-first world, businesses should leverage customer journey analytics to develop a sophisticated and integrated mobile experience—one that seamlessly integrates self service into their mobile app via visual, in-app self-service options. Conversely, this experience should offer customers callback options (either immediate or scheduled), as well as mobile chat (automated or agent-assisted) and video service. In addition to offering a stellar mobile UX, businesses should ensure backend capabilities that intelligently route customers to agents based on available context in order to drive relevant, meaningful interactions.

  2. Improve resource matching. We live in a world today where cars can park themselves and doctors can 3D print new organs, yet we still struggle with routing callers to the right subject matter experts. The time for next-generation routing is now, and it all starts with improved resource matching—specifically, attribute-based matching. This means matching customers with agents based on rich context, business KPIs, and organizational goals across all work items, channels, and resources to drive segmentation, increase prioritization, and determine the best course of action per customer.

    This also means choosing the right resources for each customer, regardless of where the resources reside within the organization. The right subject matter expert, for example, could be a contact center agent, a supervisor in your billing department, or your VP of sales. Customer journey analytics provides a 360-degree view of available resources organization-wide to support this level of attribute-based matching.

  3. Increase agent awareness. Not only is it important to collect the right information, but it must also be presented in a way that is visually understandable and easily accessible for agents. Imagine, for example, an agent being able to see where a customer has been on the company’s website over the last month, as well as that person’s live chat interactions last week. Imagine an agent being able to quickly see that a customer sent an email two days ago regarding a recent bill, or reached out via SMS because the company’s mobile app wasn’t working properly. Imagine if agents could gain this 360-degree, comprehensive view all in just one or two clicks of a mouse.

    Data is continuously generated in different ways, and is consumed by different people across different processes and applications. Having the right information at the right time empowers agents to focus on customers’ needs without having to ask for the same information multiple times (which, as we all know, is one of today’s greatest customer frustrations).

  4. Ensure continuous improvement.

    When it comes to big data, businesses can’t manage what they can’t measure. Therefore, it’s important that companies measure their data both in real-time and historically to help improve systems, processes, and applications over time. This is what will enable them to consistently deliver on key business objectives, operate within budget, and maximize every customer experience. Here are four key technologies for ensuring continuous improvement:

    • A data collector that can collect, standardize and normalize raw data across any data source so it can be used for enterprise-wide reporting and analytics.
    • A processing engine that can correlate, translate, calculate and publish normalized data into meaningful business measures.
    • A visual presentation platform that provides unified, real-time and historical reporting and analytics dashboards that can be used to visualize, analyze and explore key business measures.
    • Predictive analytics to discover new trends, apply changes based on insights, and continuously improve applications, workflows, self service and routing decisions.

So, how can you succeed with these four objectives to fine tune your customer experiences? That’s an entirely new discussion—however, we can tell you this: invest in a customer engagement platform that:

  • Provides a single view of customer interactions across all systems
  • Allows you to add data sources quickly
  • Can correlate data across both real-time and historical systems
  • Boasts an open and extensible reporting and analytics framework

Experience is everything. Learn How Avaya Oceana Works.

Personalizing the CX Requires Blood, Sweat, Time and Passion

Research undeniably proves that personalization is key for delivering amazing customer experiences. (After all, companies can’t provide just one customer experience—rather, they need to provide ongoing experiences that adapt and evolve as technology and customer needs change.) For example, a recent study found that nearly one third of customers desire higher levels of personalization when shopping. At the same time, 96% of businesses believe that personalization is what influences key purchasing decisions and inspires and strengthens customer loyalty. Personalization done right means customers are with you for the long haul.

Customers are hungry for more personalized experiences, and businesses understand the benefits in providing them. So why is it that 20% of companies have no plans to improve their personalization efforts?

As a consumer, I find this sort of inaction unacceptable. As a business leader, I’m perplexed why any company wouldn’t immediately begin to make the shift. The experiences a company offers its customers are its best chance at substantial differentiation. Differentiation means growth. More importantly, differentiation means survival. Organizations need to make customer experiences more personalized, and they have no time to waste. But this isn’t a simple undertaking. Personalization is more than just a buzzword. It’s a mentality, a company culture, a lifetime commitment. Above all, it’s something that’s expected by consumers today and generations to come.

What is a Personalized Customer Experience?

To deliver the personalization that customers desire, businesses must first understand what this really means. Personalization can be summed up into two words: contextual and predictive. Customers must be served in such a way that companies already know who they’re dealing with and how they want to be treated.

Let me give you a personal example to illustrate this. Anyone who knows me knows I love fashion, and I have a favorite retailer. Based on my shopping history and engagement with that brand, the company knows what size I am, what my color palates are, and what styles most appeal to me. They have every piece of relevant information about me to ensure my experiences are contextual and meaningful. So much so that the company can anticipate what products I’d like and dislike. For instance, they know to never suggest to me products from St. John (Vince, on the other hand, I’ll go all out for!).

By having this relevant information at the right time and by leveraging it the right way, companies can quickly create a contextual experience that’s tailored to their customers’ personalities. At the same time, they’ll be able to increase the amount of revenue they generate. In fact, according to the abovementioned study, nearly 60% of customers who have experienced personalization say it’s a notable impact on their purchasing. In my case, this is great for that favorite retailer (and perhaps not so great for my husband!).

The Only Way to Deliver True Personalization: Are You Ready?

The key to delivering this level of personalization is to find the most relevant information about each customer and use it to service them in a way that’s relevant to them.

How can businesses find this relevant information? Think of all of the data that exists about you on the web. Every action and transaction you’ve ever made lives online somewhere as part of your digital footprint. The information is out there. Companies need to be able to mine this information in such a way that it makes the customer feel special and attended to. But this can lead to a big problem: having too much information.

This is where the blood, sweat and tears happen. I wish there was a simple way to resolve this issue, but there isn’t. The only way to effectively work through this is to identify how large your customers’ digital footprints are and sift through that data to find what’s most relevant to them. The goal is to build customer profiles that reflect each individual’s preferences, behaviors and habits. After all, what every customer considers relevant is unique to them as an individual.

The good news is that there are technologies available to help minimize this grueling process. For example:

A customer engagement solution: But not just any solution. You need a platform that is truly multi-touch, enabling you to easily create, innovate, optimize and future-proof customer experiences. You must find a top-shelf platform with a proven ability to generate customer loyalty, retention, and repeat spending at the individual consumer level. Here are a few tips for finding your best solution—invest in a software-based platform that:

  • Supports easy drag-and-drop visual workflow capabilities
  • Supports multiple customer devices and operating systems
  • Identifies and preserves contextual data from every customer touch point to enrich all future interactions

Analytics: Again, not just any solution will do. You need a platform that will provide a powerful, contextual visualization of the customer journey across all touch points, enabling employees to make real-time decisions that will drive positive business outcomes. My tip for finding your best analytics solution: make sure the platform is truly integrated and that there are no silos. This integration enables businesses to flexibly collect, process, and analyze data across all real-time and historical systems to provide rich data visualization. To learn more about the power of a leading analytics solution, I encourage you to read this blog recently written by Avaya’s David Chavez. In it, he brilliantly breaks down how Avaya’s cloud-based analytics software platform, Fanalytics, transforms fan experiences at smart stadiums.

The goal is to know your customers so well that you can anticipate what they’ll want. If customers don’t know what they want, the contextual visualization you’ll have of them will show suggestions to make. As Steve Jobs once said, “A lot of times, people don’t know what they want until you show it to them.”

Two Things That Must Go Hand in Hand

Leaders in personalization understand the critical role that both technology and personal commitment play in driving success. On one hand, advanced technology helps breakdown silos, streamline the user experience, and personalize the customer’s journey across every touch point in their interaction.

At the same time, the way that companies actually use this information is just as important for coming out on top. We must care about our customers. We must be passionate about helping them. We must be their biggest advocates in order for them to become ours.

At the end of the day, customer experiences will always be human experiences. Personalization isn’t something that can be bought. It’s a belief that’s promoted and enacted organization-wide. Companies that have the right technology, supported by this belief, will go far.