Big Data. Everyone is talking about it. Many companies have it. Few are able to manage it. This includes brands that house most of their data in the contact center in the form of customer data and are not able to harness the full potential it presents. Through the consolidation of data from multiple departments, the establishment of a clear goal and the employment of intelligent analytics, companies are able to transform a customer’s experience. The consumer can instantly be elevated from an anonymous customer to a unique individual, and companies will be able to speak to each and every one as if he or she were an old friend. Predictive analytics enables companies to more accurately foresee future needs, interests and trends, as well as identify potential trouble areas before an isolated incident escalates into an issue, but perhaps most importantly, predictive analytics ensures companies have the ability to optimize each customer’s experience by integrating this data into their Customer Experience Management (CEM) program.

Big Data Analytics gives companies an edge on customer demands in order to better sell to them, but more importantly how to better speak with them and form true, reciprocal relationships. For companies – at least any company that I have any interest in dealing with – it isn’t just about making a sale, but rather securing a customer for life and building brand loyalty through quality of the product/service and the value of the company itself. In order to survive in today’s competitive marketplace, it is rarely enough to have a great product/service; customers expect to have a great experience with a brand along with their experience with the product/service. In order to ensure the best customer experience possible, companies must utilize every asset and resource at their disposal and that is why Big Data Analytics has become mission critical.

What Is Big Data? Where Did It Come From?

Enormous amounts of data have been available for decades, but we moved into the “Big Data” arena just within the past few years. The catalyst for this shift came in the form of the Mobile Revolution that roughly began with the launch of the first iPhone in 2007. Smartphones, however, were just the beginning of this new wireless world we live in. This is made evident by IDC’s prediction that tablets will outsell personal computers in the fourth quarter of 2013 and Gartner’s prediction that tablet shipments will increase by 53 percent in 2013 as desktop and laptop shipments decline by 11 percent.

Mobile devices have enabled users to bank, shop and communicate on social channels anytime and anywhere. These actions are all producing enormous amounts of data. While consumers hit the streets with their mobile devices, they were also blowing up the social media airwaves. Consumers have now created their own digital profiles through their purchases and interactions on platforms such as Facebook, Twitter and even product review or customer service sites.

This constant usage has produced enormous amounts of data for companies to mine, store and analyze. The Internet has provided the environment for consumers to serve up their buying habits and behaviors on a platter to companies that used to spend countless dollars on market research projects to uncover even less information than is now readily available for the taking…if only retailers could figure out how to sort through all of the digital noise.

The Mobile and Social Revolutions, however, were not the only contributors to the increase of available data. The mass adoption of the cloud or Infrastructure-as-a-Service has made access to vast amounts of computing resources flexible and affordable. Furthermore, the on-demand nature of the cloud and services offered through the cloud have brought the opportunity for Big Data analysis to businesses of all sizes. In a sense, the cloud led to the commoditization of Big Data.

Prior to the introduction of the cloud, businesses were reliant upon IT departments to store, manage and access data. This put an enormous strain on already fully tapped IT resources. The cloud, however, has significantly alleviated the dependence upon IT managers. Previously, this precious information was housed in physical datacenters that were managed by IT departments, but through the cloud, almost anyone within a company can be granted access to the data.

We Have Big Data! Now What?

It is no secret that a large portion of the Big Data available is made so through social media where consumers voluntarily provide the information most companies are desperate to get their hands on. Consumers today are active on multiple channels, which has led to a need for contact centers that are capable of handling multichannel environments, including and especially social. According to Pew Research Center’s Internet & American Life Project, the number of online U.S. adults who use social media sites climbed from eight percent to 72 percent since 2005. This number indicates that social media monitoring will only become more important as more and more adults become active on social channels and continue to provide invaluable data for companies.

Since its discovery there has been a great deal of focus placed on gathering data on anything and everything. In fact, perhaps too much emphasis has been put upon the collection of data and not enough on what to actually do with it once retrieved. More troubling is that often each department – marketing, sales, human resources, customer service, etc. – are all operating within individual silos and failing to share information throughout the company, leaving the data fragmented and only painting partial pictures of their current and potential customers.

One of the most valuable aspects of Big Data is the opportunity to develop a greater understanding of your customers, their preferences and buying habits. All too often companies are drowning in their own data and are unable to draw any substantial conclusions from the vast chasm. It takes more than merely cooperation and sharing between departments in order to achieve this holistic view into a customer. Companies need to approach their available data with a plan and strategy in order to ensure they are extracting the information needed to meet and exceed the expectations of their customers and would-be customers.

By using an analytical approach to the data, valuable customer insights can easily be achieved. It is important to note that while examining historical data is important, it is not sufficient when hoping to forecast trends or develop an understanding of customers as individuals. Data must be analyzed in real-time in order to help reduce churn and attrition, allowing companies to correct an issue before a customer is lost, as well as provide a better view into what is happening in any given market in current time.

What Does This Mean for Customer Experience?

Everyone knows that data analytics can be used to ensure the most frequently purchased clothing sizes are carried in the right store locations and online shoppers can enjoy having items recommended at checkout, but how else can Big Data be used to improve a customer’s experience?

In order to maximize all of the data a company is able to collect about customers, that data must be shared from departments companywide. This means Human Resources, Finance, Marketing, Sales and Customer Service joining forces to compile a more complete image of customers, employees, partners and the market as a whole. It is through this holistic view that companies can begin correlating data to determine more accurate predictions and assessments of the industry.

What several companies fail to realize is that perhaps the most valuable information relative to customer behavior comes from their customer service representatives. A company’s customer service department is ground level with customers, receiving uncensored feedback and resolving issues. By linking this data with that in operational, financial and constituency sources, companies are able to determine what is truly important to a customer. By understanding a customer’s unique needs a company will be able to provide a better customer experience through products and services the customer truly wants, when they want them and how they want them.

As previously mentioned, this data is often kept in individual silos, making it a challenge to integrate it and correlate findings. However, with the more widespread adoption of the cloud, it is becoming more and more feasible for companies to share data. Integrating data is also possible with the advent of Software-as-a-Service options that enable all departments to work in the same system to track their data. Previously each department would often work in their own systems, making integration nearly impossible, but now there are customer relationship management software packages that function for each department.

Customer loyalty is critical to businesses sustainability and growth, and, therefore, should be a top priority for companies. Building customer lifetime value can become the driving force behind business decisions with integrated data. To ensure customer loyalty, companies have taken to implementing processes that enable the understanding and management of a customer’s interactions with their brand and a customer’s perceptions of a brand and/or company. These programs have come to be known as Customer Experience Management. Solid CEM programs are dependent upon the customer insights gained from thorough and accurate data analytics, which includes feedback from customers, social media, online forums and emails to the company, whether that be customer service, sales, marketing, etc. Compiling this data allows the company to link customer actions/feedback to customer loyalty and ensure that appropriate resources are allocated to improve customer experiences, which leads to greater customer lifetime value.

Through a deeper understanding of each individual customer, companies are able to build more honest relationships, and thanks to social media, what was once a monologue from company to market has become a 1:1 conversation between customers and brands online. Initially, social channels may have sparked fear in companies because of the potential forum for public complaints or negative reviews. However, as more and more companies embrace social channels as part of their standard communication package – both proactive and reactive – they are coming to realize what a valuable tool it really is for expanding their CEM programs. While customer service agents are building real-time relationships with customers, they are also gathering invaluable data on which products work and those that don’t, as well as what types of products or services they would like to see made available. They are able to track frequently asked questions or comments and enter them into the universal system, making the data available to product development, marketing, finance, etc. Ultimately, this data will be integrated with the data accumulated by every department so it can be analyzed and utilized by all.

Big Data Analytics and Customer Experience Management Moving Forward

There is certainly a lot of data available for analysis, but nearly every company struggles with how to organize it all. In order to understand the data, it is imperative that companies begin with asking the right questions. What do they want to learn from the data? This single question will help shape how the data should be approached and lead to more in-depth questions. They must then look to integrate all of their disjointed data into a single program. The easiest way to ensure all data is shared is with a cloud-based software that allows each department to input and access critical information. This small change will enable companies to ensure that they have everything from the right number of customer service agents staffed at the right time to the right products on the shelves. More importantly, companies will be able to improve every customer experience by developing a greater understanding of who their customers are as individuals and not just as a demographic.