SOCAP International

Leveraging Big Data: 5 Steps to Getting It Right

Using an intelligent customer experience management program will not only improve customer relationships, but also significantly improve your bottom line.

Big Data has certainly been the most buzzed-about term across industries for the past year. But what exactly is Big Data? Well, let me put it this way, according to IBM, we create 2.5 quintillion (yes, that’s right, quintillion) bytes of data a day. On top of that, 90 percent of the world’s data has been created in the last two years. This data comes from millions of sources—posts to socialmedia sites, digital pictures, videos, purchase transactions, emails, call center records, online reviews and cell phone GPS signals, to name a few. All of this data—anything that can be captured and stored—is referred to as Big Data.

To say that organizations are drowning in data is an understatement. But we are living in a time when Big Data can be leveraged to significantly benefit business. It’s not exclusive to certain industries or verticals, but rather something that can be harnessed and used to any organization’s benefit if it is tied to powerful analytics. In addition, when combined with sophisticated and intelligent analysis, Big Data can help organizations better relate to, engage with and understand their customers. With a deeper understanding of the data they have and the analytic tools and strategies available, organizations can develop an intelligent customer experience management program that will not only improve customer relationships, but also significantly improve their bottom line. Here are five steps to leveraging Big Data and creating successful CEM programs.

Step 1: Know thy data. Before any initiative takes place, you need to identify the data you have, define it within the organization and put it into context. Ask yourself: Does your organization have big volumes of customer data? Are you actively using social media to engage with customers? Do you use surveys or other sources to gauge marketing or sales efforts? The answers to these questions are probably yes, and this data is probably being compiled faster than ever. The phrase, “Know thyself,” is steeped in wisdom, and can be applied here. Know thy data—because if you don’t, you’ll never be able to leverage the benefits it can offer.

Step 2: Categorize structured and unstructured data. With structured data, you can measure the who, what and where. This includes data such as transactions, clicks, GPS tracking and real-time physical sensors. Unstructured data needs interpretation, and the what and why behind it is not as easily discernable. This comes from sources like photos, videos and voice.

Here is a real-world case from one of the world’s largest retailers, which we’ll refer to as Company X in the interest of anonymity. Company X handles more than 1 million customer transactions every hour, which are imported into databases estimated to contain more than 2.5 petabytes of data. Company X analyzes patterns in clicks and transactions occurring in stores as a gauge for its Big Data analysis. This is structured data.

Company X’s call centers have more than 500 agents and an average of 50 calls per agent per day. If you do the math, this leave the company with 175,000 call-detail records each week and 9.1 million per year. These records are unstructured data because the information is free-flow text of notes from discussions occurring over the phone. Unstructured data is textheavy, raw and not uniformly organized like structured data.

The challenge with Big Data analysis is combining structured and unstructured data into one analyzable format to form a holistic understanding of the customer.

What it all comes down to is that unstructured data can be hard to analyze. And, wouldn’t you know, for most companies, the majority of their data is unstructured. According to Forrester, 85 percent of enterprise data is unstructured. The challenge with Big Data analysis is combining structured and unstructured data into one analyzable format to form a holistic understanding of the customer. So how was Company X able to analyze both its structured and unstructured data? It did so by partnering with a CEM partner experienced in sentiment and text analysis.

Step 3: Bring on a CEM partner. Whether you are a Fortune 500 company or a smaller organization, the next step is to partner with a CEM vendor. Why wouldn’t you do it in-house? Well, for companies of any size, this type of project is time-intensive and, if done manually, inefficient, inconsistent and costly. To do this right, your organization needs to adopt intelligent technology from a company that lives, eats and breathes customer experience. The right vendor will do the legwork for you and act as a trusted partner to help your organization figure out how to best leverage Big Data and drive end-to-end customer engagement. As you begin to choose a CEM partner, it’s important that your organization creates a checklist for what an ideal vendor would look like. Your vendor should be able to:

Deliver multi-source listening and sophisticated analytics: This goes back to structured and unstructured data. Can the vendor help your organization intelligently “listen” to data in any format and in any language? Regardless of how the customer is communicating (through email, survey, social media or the contact center), a vendor’s technology must enable you to holistically listen and understand what is being said. Does it have sophisticated analytical capabilities that let you both report the aggregate, while also diving into the data at a granular level? Does it give you an accurate and detailed understanding of sentiment? And does it have customizable and scalable reporting so that when you do uncover insights they are easy to share and understand across the enterprise?

Know thy data— because if you don’t, you’ll never be able to leverage the benefits that it can offer.

Infuse CEM into your organization’s DNA: Your vendor should not only help you efficiently and intelligently analyze the data, but also help you act on and operationalize the customer insight across the entire organization. This type of Big Data project can only truly be successful if it allows for a customer-experience centric enterprise. Have proven, successful, real-world experience: Make sure you demand references, look for success stories in the media or ask your peers at other organizations. A good partner will have proven successes in its back pocket. Be sure to practice caution during your vendor selection process. Many vendors say they do CEM, but do not have experience in the space. Make sure they offer proactive, innovative ideas—specific to your unique business—of how your organization can benefit from this initiative and realize measurable value.

Step 4: Embark on analysis and put it to good use—for your customers and your business. Now that you are working with a CEM vendor, what’s next? Well, the next step is working with a CEM partner to remove spam and find the most actionable and powerful insights on which to take action—it’s finding the small gems within Big Data. This is where it gets good, folks. With sophisticated analytics, you can now get a better understanding of sentiment and customer influence.

Once you’ve gleaned actionable insight, you can then route it to the appropriate internal stakeholders (I’m talking about people across departments or even geographies). Customer feedback doesn’t have to be just for the customer experience team. When sharing insights with relevant stakeholders across the enterprise, you bolster cross-departmental collaboration to resolve complex business problems. And because you have access to real-time, actionable customer feedback, you are also able to conduct real-time customer engagement and response. Promoting proactive interactions with customers will ensure that issues are resolved faster, while creating more meaningful relationships with the customer.

Step 5: Get started … go, go, go! Getting started with using Big Data to improve customer experience is no easy task, but one that is well worth the effort. The possibilities are endless with Big Data, especially when it comes to changing the way your company thinks about and responds to customer experience. In today’s highly competitive business environment, you need the right tools and the right partners to help you stay ahead. Leveraging Big Data for customer experience and having the right CEM partner to guide you through the process is a ticket for success. Now what are you waiting for? Your customers are talking, so start listening and acting.

Pippine_MelissaMelissa Pippine, vice president of marketing at Clarabridge, is responsible for overall corporate and product marketing strategy, planning and execution. She and her teams have launched new products, including Clarabridge Collaborate Engage, elevating Clarabridge to the leading provider of customer experience management solutions. Prior to joining Clarabridge, she spent 10 years at American Management Systems (AMS), later CACI in project and product management, implementing and overseeing the design, development and testing of enterprise-wide procurement and reporting software.