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Analysts have been talking and writing about a “360 degree” view of the customer for years. Our own benchmark research intovr_customer_analytics_05_dissatisfaction_with_customer_analytics_updated customer relationship management shows that only37 percent of organizations are able to produce analysis and reports that yield such a comprehensive view. Other research into next-generation customer analytics reveals that the main issue in this area for nearly two-thirds (63%) of organizations is data availability. To make the situation worse, customer-related data is getting ever more numerous and complex. A principal reason for this growth is the number of communication channels consumers now use to engage with organizations and the type of data these channels produce. It includes call recordings, text messages, email, social media posts, customer feedback surveys, chat scripts and event data such as videos that users download. All of these types of data are unstructured , which makes them harder for conventional analytics tools to access and analyze.

Clarabridge is an established vendor of analytics that over the last few years has focused on helping companies deal with such data. Its portfolio of products is called Clarabridge CX Suite that includes CX Analytics, CX Social and CX Survey. The products capture data from a variety of sources; a big data platform provides the core tools to analyze large volumes of ventanaresearch_technologyinnovationawards_winner2016_whitestructured and unstructured data; analytics tools execute specific types of analysis; and a set of tools enables organizations to take action based on the results of the analysis. The focus on social media engagement with CX Social was recognized with a 2016 Ventana Research Technology Innovation Award.

Clarabridge offers three sets of tools to capture specific categories of data. One captures data from multiple types of surveys such as post-call surveys, NPS surveys, Web-based surveys and employee surveys. A second captures social feedback from Facebook, Twitter, LinkedIn and other platforms. The other set captures interaction and related customer data from email, chat scripts, contact center agents’ notes, voice recordings, CRM data and other sources. Clarabridge calls these tools the “listening layer” because they enable organizations to capture data from these customer-related sources and connect it to a specific customer.

The big data platform and analytics tools are what the company calls its “analyze” layer. An advanced text analytics tool uses natural-language processing and other techniques to extract insights from unstructured text data. It allows users to set up rules to categorize interactions based on words or phrases they include, to derive caller sentiment at a more detailed level than I have seen in other products, and to spot trends. This layer also includes tools that allow users to create their own analysis, using any of the data captured at the listening layer. I especially like the ability to produce customer journey maps that focus on the customer life cycle, as they search for products, acquire products, use products and seek support – in other words, from marketing through sales and service, rather than on channel use, which many other products focus on.

The “act” layer I find to be the most important. It is divided into proactive support of front-line operations and business optimization. In principle these halves provide similar capabilities to put outputs from the analyze layer to use. In terms of front-line operations this goes beyond visualizing the information in different ways for different uses to recommend actions to, for example, contact center agents. From a business optimization perspective, it also goes beyond visualizing the information in different forms to show analysis across multiple data sources, role-based dashboards, side-by-side comparison of information and root-cause analysis. In conjunction these features allow organizations to make use of the insights they gain from using analytics beyond just producing pretty charts.

Clarabridge is cognizant that many advanced analytics tools are not easy for many business people to use. It therefore provides extensive support services that range from setting up access to data sources, customer segmentation and journey mapping; setting up topics, themes and categorization rules; interpreting emotion and sentiment analysis; using root cause analysis; customizing reports and analysis; redesigning interaction processes; to using the outputs to design a customer engagement strategy. Added together these services extend from help in overcoming the initial hurdles of using the tools properly to helping organizations get full business value from the products. These services and the product set provide a firm foundation and an ongoing process for improving business performance.

Our research into next-generation contact centers in the cloud shows that customer vr_ngccc_01_customer_self_service_will_increase_updatedexperience (CX) has become the true business differentiator: 70 percent of participants said that it is the primary way they expect to compete for customers. I believe a comprehensive view of customers that makes use of all available data, their business journeys and the business impact of customer engagement are essential components are starting a CX initiative and gaining maximum business benefit from it. So I recommend that organizations wanting to maximize the value of their customers assess how Clarabridge can help those efforts.

Regards,

Richard Snow

VP & Research Director Customer Engagement

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During a recent briefing with NGData, I was initially put off by excessive “marketing speak.” The team began by describing its product, Lily Enterprise, as a “customer experience operating system.” Being used to having operating systems run entire computers, I wasn’t sure what this meant. This term was followed by a statement that NGData’s products help companies transition from being “B2C to C2B,” that is, to put the customer first, an idea that has been around for several years but in my experience few companies achieve. One of the biggest challenges in this regard is that most companies are organized into business groups, and each business group typically has its own processes, systems and metrics, a situation that makes it hard to have a single view of the customer and take actions based on the same customer view, and which lends itself to focusing on internal goals, not the customer. As an example, our research into next-generation customer engagement shows three key impediments to delivering exceptional customer experiences: systems that are not integrated (for 49% of organizations), communication channels managed as silos (47%) and customers receiving inconsistent responses at different touch points. The root cause of all these is data – customer data. Organizations have multiple systems that generate customer data, in multiple forms: for example, structured data in CRM and ERP systems, voice recordings, text data from multiple sources (letters, email, Web scripts, text messages, chat scripts and social media posts), video and event data such as a customer downloading a film. With so much data in vr_ngce_15_supporting_multiple_channels_updatedso many formats, it is hard for companies to generate a single, “360 degree” view of the customer that can be shared across the whole organization.

As the briefing continued, I learned that Lily that we recognized with a Technology Innovation Award in 2014 helps address the issue of dispersed customer data. Overall its product architecture has three levels. First, there are tools to ingest data from any source, including internal business and technology systems, third-party systems and publically available sources. Second, there are tools to produce reports and analysis based on that data, and to derive metrics using the data. These tools utilize big data management and analysis tools to process very large volumes of data in any format. At the top level, the company offers tools that use the outputs of the second layer as inputs for various uses – for example, to provide contact center agents with information about callers, to create personalized email or letters, to provide personalized responses to social media posts or as input to self-service systems such as Q&A on the corporate website or a mobile app. Such actions can occur through multiple channels of engagement, assisted or self-service, ensuring that responses at any touch point are based on the same up-to-date information – this is a fundamental requirement of omnichannel customer service. This three-stage approach – data, insight and action – is why NGData describes its products as an operating system rather than just a performance management or analytics system.

However, this terminology detracts from what for me it its biggest differentiator – what the company calls “customer DNA metrics.” Discussion is common about the need for a 360-degree view that contains all information about a customer – be it marketing, sales, service, financial, interactions, behavioral, lifestyle, value, preferences or risk; in short, everything that anyone in the organization might need to know about a customer. Lily Enterprise allows organizations to define as many metrics about a customer as they like and to create the rules to derive these metrics from specified data. The system collects the data, derives the metrics and groups them into defined categories, such as risk level, propensity to buy or frequency of calls. It then presents the categories and scores in a highly visual way, as shown in this video. This view can be shared with anyone in the organization, helping to ensure that everyone has the same view and takes actions based on the customer’s profile rather than from an inward-looking perspective; thus it becomes a C2B company, putting the customer first.

I often argue that consumers expect experiences that are EPIC – Easy, Personalized, In context and Consistent. I fail to see how organizations can deliver on these expectations unless they have a complete view of the customer that everyone, and all self-service systems, works from. There are other products that produce a view of the customer, but none of them in my experience is as complete as those produced by Lily, and the “customer DNA” appears to be unique. I therefore recommend that organizations that want to become fully customer-centric assess how NGData can help, bearing in mind that such a 360-degree view is the starting point and that most organizations will need to use it to change processes and employee training if they are to become a true C2B company.

Regards,

Richard J. Snow

VP & Research Director, Customer

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