You are currently browsing the tag archive for the ‘Contact Center Analytics’ tag.

Robotics is nothing new to some aspects of manufacturing and the IT industry, but it is relatively new in the customer experience (CX) market. The term often conjures up images of little gray machines taking over tasks previously handled by humans – machines making cars, programmed vacuum cleaners and the like. In the CX space, however, we are not talking about machines but about software that can automate routine tasks. For the time being, I don’t believe robots will take over the contact center and replace human agents. Indeed our recent research into next-generation contact centers in the cloud strongly suggests the opposite. It shows that the telephone is still the top channel of communication and that almost two-thirds (62%) of organizations expect call volumes to rise over the next 24 months. Thus agents will continue to handle large volumes of interactions, which may become more complex.

This complexity, plus demanding consumer expectations, requires organizations to handle interactions efficiently and capably or risk losing customers and/or business opportunities. This opens up the opportunity for organizations to take advantage of robotic process automation. NICE, a longtime contact center systems vendor, has offered real-time process automation since 2001, and it recently launched a new product in this market. It now has three products in this space – desktop analytics, desktop automation and its latest, robotic process automation. NICE Desktop Analytics captures information about what agents, or other designated users, do on their desktop, including systems they access, information they look up, data they enter, information they give callers, and systems they update after finishing calls. The analytics enables organizations to track the four basic components of a call – identifying the caller, identifying the caller’s issue, providing a response and completing any required after call work. The analytics component thus can identify best practices for interaction handling and agent performance, and recommend changes to processes or coaching and training.

NICE Real-Time Decisioning helps organizations improve interaction-handling processes. It can, for example, take an account code or calling number and automatically present the customer’s data to the person handling the interaction. This set can include demographic data, financial data, marketing, sales or service data, and an interaction history. It can then take data entered by the person handling the interaction to look up other relevant information; for example, if the caller is asking about a product this information can be automatically popped onto the desktop. The system includes rules and algorithms that suggest what the person should do next to ensure the best outcome of the interaction. The system can also complete some basic after-call work such as updating other systems. This is where robotic automation comes into play.

Either by using analytics or by observation, users can identify processes to be automated. NICE Robotic Automation includes tools for users to map the process, and then develop “robots” – software that includes algorithms and is driven by rules and data – that can automate the process; for example, the software can populate name and address changes across multiple systems, complete claims forms, initiate customer onboarding or send personalized messages. The tools use point-and-click techniques, so robots can be developed by business users with minimal assistance from IT. A robot can be initiated because it detects a trigger (data received) or is kicked off by what NICE calls the  “robot controller,” a person designated to manage the operation of robots It then runs in a virtual environment until the process is complete, when it either picks up another task or is terminated. The system is highly scalable: The number of robots can be scaled up or down to match the number of tasks to be carried out. The product also includes multiple security options that program robots to comply with specified regulations.

At one point in my career I worked for a partner at a management consultancy who was famed for saying, “Software makes bad processes go wrong more quickly.” This is often true, and NICE’s process automation is about achieving the exact opposite – creating smart processes that run more efficiently and delivery better outcomes for customers, agents and businesses. In relation to the four components of call handling mentioned above, it can immediate identify the customer, capture the issue, guide the agent how best to resolve the issue and then reduce or eliminate after-call work. In doing this it can also reduce data entry errors, make agents’ jobs easier, improve the customer experience, help ensure that more interactions are completed successfully, and achieve something all contact center managers I know have at the top of their to-do lists – reduce average call-handling times.

vr_ngce_research_01_impetus_for_improving_engagement_updatedOur research into next-generation customer engagement shows that these capabilities align with the top objectives organizations are focused on as they try to improve customer engagement: improve the customer experience (76%), customer service (70%) and business processes (54%), become more competitive (46%) and reduce operating costs (43%).  NICE’s process automation products have the potential to impact all of these, so I recommend that companies assess how it can help in their efforts to become more efficient and effective. Does it mean robots will take over the contact center? I think not, but it can make processes run faster and smoother and free up employees to focus more on the customer.

Regards,

Richard Snow

VP & Research Director Customer Engagement

Follow Me on Twitter  and Connect with me on LinkedIn

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

Follow Me on Twitter and Connect with me on LinkedIn

RSS Richard Snow’s Analyst Perspectives at Ventana Research

  • An error has occurred; the feed is probably down. Try again later.

Twitter Updates

Stats

  • 68,568 hits
%d bloggers like this: