Customer Interaction Analytics TM. A 360 Approach for Analyzing the Voice of the Customer Across Multiple Communications Channels

Transcription

1 Customer Interaction Analytics TM A 360 Approach for Analyzing the Voice of the Customer Across Multiple Communications Channels

2 Table of Contents The New Voice of the Customer... 2 Customer Interaction Analytics Defined... 3 Sources of Customer Interaction Data... 3 Cornerstones of Customer Interaction Analytics... 4 Solution Capabilities... 5 Linking Interactions Across Channels... 5 Collecting Data... 5 Joining Data... 5 Creating a Unified View... 6 Detecting Trends and Providing Early Warnings... 7 Using Customer Behavior Indicators to Surface Trends... 7 Performing Deep-dive Analysis... 9 Categorizing Interactions... 9 Using TellMeWhy to Uncover Root Cause Using Sentiment Scoring to Quantify the Voice of the Customer Detecting Emotion Taking Action on Customer Intelligence...12 Pinpointing Cost/Satisfaction Drivers via Scorecards Providing Focused Quality Through Quality Monitoring Using Data Analytics to Perform Quantitative Trending Analysis Leveraging Customer Feedback Surveys Using Reports and Visualization Customer Interaction Analytics in Action...17 Product Development Operations Customer Care Customer Retention Marketing Unauthorized use, duplication, or modification of this document in whole or in part without the written consent of Verint Systems Inc. is strictly prohibited. By providing this document, Verint Systems Inc. is not making any representations regarding the correctness or completeness of its contents and reserves the right to alter this document at any time without notice. Features listed in this document are subject to change. Please contact Verint for current product features and specifications. All marks referenced herein with the or TM symbol are registered trademarks or trademarks of Verint Systems Inc. or its subsidiaries. All rights reserved. All other marks are trademarks of their respective owners Verint Systems Inc. All rights reserved worldwide.

3 Business Process Analysis Executives Conclusion...19 Unauthorized use, duplication, or modification of this document in whole or in part without the written consent of Verint Systems Inc. is strictly prohibited. By providing this document, Verint Systems Inc. is not making any representations regarding the correctness or completeness of its contents and reserves the right to alter this document at any time without notice. Features listed in this document are subject to change. Please contact Verint for current product features and specifications. All marks referenced herein with the or TM symbol are registered trademarks or trademarks of Verint Systems Inc. or its subsidiaries. All rights reserved. All other marks are trademarks of their respective owners Verint Systems Inc. All rights reserved worldwide.

4 Introduction Your customers have more ways than ever before to communicate with you. In addition to traditional phone calls, they can use chat, , and even text messages to reach your organization when they have a problem or need assistance with products and services. Moreover, customers can also use social media and review sites on the Web to share their experiences involving your company. This dramatic expansion in communication channels has left many organizations with the need to rethink the processes, technology, and overarching strategy for their customer service operations. This paper introduces and explores Customer Interaction Analytics TM a portfolio of Verint solutions to help businesses stay ahead of the buzz while turning the voice of the customer into opportunities to enhance customer loyalty and revenue. About Verint Witness Actionable Solutions Verint Witness Actionable Solutions, part of Verint Systems Inc. (NASDAQ: VRNT), is the leader in enterprise workforce optimization software and services. Its solutions are designed to help organizations capture customer intelligence, uncover business trends, discover the root cause of employee and customer behavior, and optimize the customer experience. From contact centers to remote office, branch and back-office operations, its award-winning, next-generation Impact 360 Workforce Optimization suite is the industry s most unified solution set featuring quality monitoring and recording, workforce management, Customer Interaction Analytics (speech analytics, text analytics, data analytics, and customer feedback surveys), performance management, elearning, and coaching. Impact 360 helps improve the entire customer service delivery network, powering the right decisions to help ensure service excellence and transform organizations into customer-centric enterprises. Page 1

5 The New Voice of the Customer Today s customers have an unprecedented number of ways with which to communicate with and about your organization, including the telephone, chat, , and even text messages. In fact, consumers now have so many channels of direct communication, businesses are struggling to keep up with them. These channels are easy to use, which poses a new set of customer service challenges. In the past, if customers were unhappy, they might tell a few friends, who might tell a few of their friends. While undesirable, the negative message would generally spread only so far. Today, however, if customers are unhappy, they can easily tell millions of other people. Clearly, organizations need to find a way to stay ahead of the buzz. Some companies are beginning to establish their cross-channel customer interaction strategies. But to thrive in the age of social media, it s not enough to simply monitor social media activity. Companies need to begin to mine these new channels, as well as existing ones, for actionable information and opportunities for customer engagement. In fact, many viral public relations nightmares might be avoided if companies analyzed what their customers told them and took corrective action before customers went public with their dissatisfaction. Detecting customer sentiment and leveraging your customer base as a focus group for enterprise business intelligence can be a powerful competitive advantage, since customer satisfaction can add significantly to the bottom line. After examining the customer bases of more than 100 companies, Forrester Research found that customer experience leaders held an advantage of 14 percentage points over customer experience laggards in all three key areas of customer behavior: willingness to buy more, reluctance to switch, and likelihood to recommend. For large hotels, Forrester projected that annual revenue gains from even a modest improvement of the customer experience could reach $311 million. * Some of the best ideas for new product features may come from identifying an increase in number of questions or comments coming directly from customers. A root cause of intense customer dissatisfaction may be caused by a new policy. A small set of power users may discover a product defect before news about it explodes across the Web. These are just a few examples of the type of early warning signs and root cause analyses that can be conducted when companies begin to mine customer interactions across multiple channels. Where do you begin? How do you mine voice and text channels to detect trends before they become issues? And how do you drive the information to the right people in your enterprise at the right time so they can act on the emerging trends? Customer Interaction Analytics offers a solution. * Customer Experience Boosts Revenue, Bruce Temkin, Forrester Research, June 22, Page 2

6 Customer Interaction Analytics Defined Customer Interaction Analytics is a strategy that links together multiple channels of customer interactions such as phone, text, and customer feedback surveys to provide an aggregated, unified view of customer service, experiences, and opinions across both direct and indirect customer communications channels. Enterprises can use this data to detect trends, understand customer sentiment, and easily inject consumer preferences into day-to-day business operations to enhance decision making, improve operational performance, and increase customer satisfaction. Sources of Customer Interaction Data The sources of customer interaction data are vast. Interactions can come from internal (i.e., companysolicited) and/or external (i.e., consumer-generated) feedback sources. Much of this data perhaps 80 to 85 percent is unstructured, meaning that it lacks a defined, standard structure that would enable simple quantification. The illustration below provides examples of customer interactions containing structured vs. unstructured data: Unstructured Voice Calls s Chat Focus Groups Blogs Social Media Word of Mouth Internal (Direct) External (Public) Customer Surveys Agent Disposition Quality Scores Online Ratings 3 rd Party Market Research Structured Figure 1 - Types of Customer Interactions Each of the two dimensions shown above structured/unstructured and internal/external provides its own set of challenges and benefits, including: Page 3

7 Internal - Unstructured Interactions Provide immediate, unbiased feedback from customers about your company. Offer great depth of insight, due to free-form nature of conversations. Traditionally more difficult to analyze due to unstructured nature of the data. Can provide early warning signs of significant service issues before they go viral. External - Unstructured Interactions Provide unbiased dialog between customers about your company. May have impact on other customers and even your competitors. May be difficult to distinguish real customer insight, from non-relevant noise. Traditionally more difficult to understand full context of the interaction. External - Structured Interactions Provide quantifiable measures of overall customer ratings. Offer wide scope, but can be less actionable because it is harder to identify root cause without the full context. Supported by mature analysis methods. Most useful for benchmarking and future planning. Internal - Structured Interactions Typically provide quantitative analysis on key internal metrics. Can help answer specific questions, but can miss important new emerging trends. Drive operational decisions. The balance between structured and unstructured sources is rapidly shifting to a significant increase in unstructured data sources. These have traditionally been harder to mine and quantify, but are very rich in information and customer insight. This leaves the analyst who wishes to create a complete picture of customer interactions the daunting task of making sense of disparate data sources and formats. Cornerstones of Customer Interaction Analytics Customer Interaction Analytics solutions can solve the disparate data problem by collecting and linking customer interactions across the types of interactions outlined above. The result is a set of aggregated data that can then be analyzed to provide deeper insight for informed decision making. For example, Verint s Customer Interaction Analytics TM portfolio can combine and analyze customer data from direct (phone calls, chat, ) and indirect sources (social media) to deliver a unified view of the customer experience even down to the individual customer level. At the enterprise level, this multichannel analytics solution can deliver insights useful for fixing broken processes, identifying issues and opportunities, gaining competitive advantage, driving down costs, and more. Capitalizing on the unified functionality with the Verint Impact 360 Workforce Optimization suite, Verint Customer Interaction Analytics incorporates four cornerstone analytics solutions that focus on different interaction channels: Page 4

8 Impact 360 Speech Analytics Mines recorded interactions to surface the intelligence essential for building effective cost containment and customer service strategies. Impact 360 Text Analytics Uses natural language processing to analyze customer communications from a variety of internal and external text sources, including chat, , social media, and more. Impact 360 Data Analytics Leverages the structured data associated with recorded calls, including quality evaluation scores, to reveal specific scenarios that can help or hurt overall contact center performance. Impact 360 Customer Feedback Uses context-sensitive, dynamic customer surveys to capture information across different channels of contact. Can be used with Impact 360 Speech Analytics and Impact 360 Text Analytics to combine unstructured and structured data into the analysis. Native integrations with the Impact 360 Workforce Optimization suite enable Verint Customer Interaction Analytics to take advantage of Impact 360 s workforce performance tools, such as dashboards, scorecards, quality monitoring, and business process analytics functionality. This can enable a seamless workflow that delivers the data to the people best equipped to tackle a problem, leverage data, or stem negative sentiment before it becomes public outcry. Solution Capabilities Verint Customer Interaction Analytics provides a broad range of capabilities for delivering a 360 view of customer service, experiences, and opinions across direct and indirect communication channels. These capabilities are described below. Linking Interactions Across Channels Often, the most challenging aspect of deploying a Customer Interaction Analytics strategy is actually linking the channels together to provide a unified voice of the customer. Most customer feedback sources do not come from a single provider, nor have they been architected according to a unified standard of reporting. This makes it hard to tie these channels together. Collecting Data Data collection is the first step in the process. Internal data such as phone calls, chat and messages, coupled with structured CTI and CRM data can be accessed through coordination with the appropriate owners within the organization. However, when the content to be accessed resides outside the firewall, Web data services can help with accessing, cleansing, and loading of Web information into the Verint Customer Interaction Analytics solution. Joining Data Once interactions have been collected, they are merged via a Customer Data Joiner TM, which unifies them through the structured data typically associated with each. This can include identifying information, as well as additional details from other internal applications or data warehouses. For example, an address from a Web form may identify the individual providing feedback as a gold-level customer. The Customer Data Joiner draws connections among the channels customers use to communicate with your business, providing a unified view of what they are expressing. Page 5

9 Figure 2 Unifying Different Communication Channels via the Customer Data Joiner Creating a Unified View Once interactions are collected and linked, Verint Customer Interaction Analytics can provide a comprehensive view of the customer experience across channels at both the individual and enterprise levels via Customer Interaction Summaries. For example, summaries can be generated for each individual customer to track the various channels he or she has used to communicate with your company. From a service perspective, this can be particularly useful, since customers tend to expect that you are aware of every interaction they have had with your business, regardless of channel. Page 6

10 Figure 3 - Customer Interaction Summary Using the Customer Interaction Summary, an analyst or service representative who is reviewing a customer s experience can access all the touch points for that customer. This can facilitate better, more tailored service while providing more useful feedback for the organization. Detecting Trends and Providing Early Warnings Verint Customer Interaction Analytics can be especially useful as an early warning system to help businesses detect and address emerging trends, before they erupt into postings on the Web. This can have far-reaching benefits, not only from a customer relations standpoint, but also from a legal and economic perspective. Once a trend is discovered, Customer Interaction Analytics can also serve as a tool that provides deep root cause insight from customers into defined topics of interest. Using Customer Behavior Indicators to Surface Trends Verint Customer Interaction Analytics uses Customer Behavior Indicators TM as the primary feature for detecting potential issues. Customer Behavior Indicators are designed to proactively report on significant customer activity based on automated trend analysis of term, phrase, and category activity over multiple time periods. If a particular word, phrase or category is being used more or less often across a single or multiple channels in a statistically significant manner, it is automatically flagged. Customer Behavior Indicators are especially powerful because the user does not need to know in advance what to search for the Verint solution can surface the trend automatically. It can examine hundreds of thousands of terms and phrase combinations across all customer interaction channels, right out of the box, with keyword definitions required. Customer Behavior Indicators can identify a trend that is happening internally but has the potential to go viral externally. In the example below, a financial institution has experienced a dramatic increase in the use of the phrase new fees following the introduction of a new fee policy. Customer Behavior Indicators Page 7

11 can automatically detect this spike in usage without any guidance from the user and display it with other top-trending words and phrases in easy-to-read chart. Figure 4 Trend Detection in Phone Calls The screenshot shows that usage of the term new fees in recorded calls has increased in the past week, pushing this term to the top of the Customer Behavior Indicators chart for calls. Customer Behavior Indicators can be used with communication channels other than the phone, including social media channels. In the screenshot below, we see that a similar term, ridiculous fees, is trending upward in blogs that this company is tracking. Figure 5 Trend Detection in Blogs Page 8

12 This rising trend is probably related to the same fees that were identified via phone calls a strong indication that the trend is starting to surface externally. With this level of insight, the company has a chance to address the issue before the buzz grows stronger, perhaps by issuing talking points for agents to explain the fees, by posting a notice on the Web site or other self- service channels, and responding directly via social media. Performing Deep-dive Analysis Customer Interaction Analytics can also be used for deep-dive analysis into specific topics or business issues that are identified in advance. Analysts can categorize interactions across channels to create focus groups on demand and leverage natural language processing, root cause analysis, sentiment scoring, and emotion detection to obtain rich insight into key business problems. For example, a product manager can categorize all interactions about a new product across phone calls, s, chat sessions, Web reviews, blog posts, and tweets to assess what consumers think about it. He or she could mine for sentiment and key issues before, during, and after the launch. Marketing could analyze customer interactions at the time of product launch to assess performance across launch platforms and the effectiveness of marketing and public relations campaigns, adapting them as necessary. Following the launch, Customer Service could access interactions to determine customer response and key areas of customer feedback. Later, research and development teams could mine interactions for product enhancement ideas. Categorizing Interactions The first step in deep-dive analysis is to categorize the interactions. The Verint solution uses wizard-like tools to provide guidance in classifying interactions across the multiple communications channels. Interactions are assigned to Figure 6 - Categorizing Processed Interactions one or more defined (and continually refined) business categories based on their content. Category definitions combine the same types of keyword and phrase combinations that can be used in interactive searches. The result is a rich analytics database that can continually and automatically classify contacts into a series of categories related to specific business drivers, such as first-contact resolution, customer retention, complaints, Web site and self- service issues, competitive intelligence, and product suggestions all of which can be accessed with a single mouse click. Without the solution, this level of analytic output might require armies of trained analysts to individually listen to hundreds of thousands of calls and s. Page 9

13 Using TellMeWhy to Uncover Root Cause When a set of calls pertaining to a specific issue (such as repeat calls) has been found, it is often impractical or impossible to listen to each call individually. Verint Customer Interaction Analytics can use the TellMeWhy TM functionality within Impact 360 Speech Analytics to automatically analyze a set of categorized interactions and surface underlying issues such as unclear policies or delays in the back office without these specific sub-issues and root causes being defined in advance. Using patented audio indexing and categorization technologies, the speech analytics solution creates a Complete Semantic Index of recorded calls. The Complete Semantic Index can process up to 100 percent of customer interactions and fully index every identifiable word and phrase. By indexing the content and context of each interaction, it can process, retain, and mine the entire content of processed interactions, not just the keywords and phrases that users know to search for. In the dynamic contact center environment, continual categorization and mining of interactions across multiple communications channels plays a pivotal role in surfacing emerging issues and root causes. TellMeWhy analysis is based upon the entire content and context of a call, as opposed to simply counting a very small sample of pre-defined keywords. It can compare any subset of interactions of interest to the entire population of processed calls to determine root cause. For example, when analyzing repeat calls, TellMeWhy can automatically identify a subset within that category containing specific words, such as new account and welcome kit. This might indicate that new customers who are waiting to receive a welcome kit in the mail before using their accounts are not receiving the materials within the specified time frame. Although this is a back-office issue, the contact center is impacted by the broken process, nonetheless. Armed with this knowledge, the center can change agent scripts as necessary while providing information to the appropriate departments within the enterprise to reduce repeat calls and increase customer satisfaction. Other root cause findings typically address business issues, such as long calls, customer retention, and vendor management. Management can determine the underlying causes of each of these particular issues, then make informed choices. Root cause is dynamic: One week, the root cause for customer dissatisfaction might be technicians not arriving as scheduled; the next week, it might be inappropriate up-sell attempts. Verint Customer Interaction Analytics reflects this by continually updating the root cause suggestions based on the latest customer interactions within the system. Verint Customer Interaction Analytics also includes Advanced Context Visualization tools that assist in developing focused categories by visually guiding the user to terms that are associated with the actual category meaning, while avoiding other terms that may introduce irrelevant calls and decrease category accuracy. The solution can automatically surface and present the correlated terms and phrases for any search or category based on the actual content of the calls, without the need to know in advance how agents and customers express themselves. Since a single word or phrase can be used in many different contexts, it is critical to be able to visualize them before executing a search or applying the TellMeWhy functionality. In the following example, when searching for calls regarding a new self-service Web site, the Context Visualization tool has automatically surfaced that agents and customers discuss the site in several different ways: complaints about password problems; requests for help in placing orders, or calls in which agents educate customers on use of the self- service channels. Each group of terms defines a distinct context in which the Web site is being discussed, enabling Impact 360 to instantly drill down to the specific and focused set of calls. At that point, users can leverage TellMeWhy to surface, for example, the drivers of password- related calls about the Web site, or consult the drillable charts to identify agents who are not educating customers sufficiently on the self-service channels. Page 10

14 Figure 7 - Advanced Visualization and Root Cause Tools Using Sentiment Scoring to Quantify the Voice of the Customer Impact 360 Text Analytics categorizes and mines text interactions as they take place using Natural Language Processing. The processing engine understands the syntax and context of all the elements of the text, such as parts of speech, facts, and linguistic clauses and relationships. This exhaustive approach creates a foundation to help ensure the resulting analysis is comprehensive and accurate. Going further, Impact 360 Text Analytics performs advanced sentiment scoring for tremendous insight into attitudes expressed in customer feedback. Sentiment Scoring automatically understands negation, conditional sentiment, and other linguistic nuances to provide an accurate context. It can even allow tuning of sentiment to account for concepts specific to an organization or industry. For instance, thin may be a positive attribute for cell phones, but a negative for linens in a hotel. The following example depicts how Impact 360 Text Analytics can extract positive and negative sentiments from a customer review of an experience at a hotel. Page 11

15 Figure 8 - Detecting Customer Sentiment Across Categories Detecting Emotion Impact 360 Speech Analytics can identify emotional interactions and segments within telephone calls, helping organizations track the issues that most affect customer satisfaction. Emotional calls are detected based on a combination of linguistic and acoustic elements, to account for the various ways customers express emotion. Figure 9 - Detecting Emotion in Phone Calls Taking Action on Customer Intelligence The insight provided from Verint Customer Interaction Analytics especially when integrated into a company s existing business intelligence and data-warehousing infrastructures can offer significant benefit to practically every department across the enterprise. This intelligence is most powerful when it is delivered to the people in the organization who are best equipped to act on it. Through integration with the Impact 360 Workforce Optimization suite, the solutions can make analytics data available across the platform to create a workflow to drive information to the right people, at the right time. This unified approach helps enables enterprise decision making. Pinpointing Cost/Satisfaction Drivers via Scorecards Impact 360 allows enables management to drill down on agent performance via easy-to-use scorecards that compare customer service groups and individuals against their peers in any content category built within the analytics solutions. For example, combining scorecards for cost drivers (such as average handle time and first-contact resolution) with speech analytics-driven key performance indicators (such as customer-requested escalations and compliment calls) can help analysts balance cost drivers and customer satisfaction drivers. In a single scorecard, users can compare their group performance with that of their peer group, or even each agent s performance with his or her peers, based on actual call content. The following example shows a performance management scorecard containing Customer Interaction Analytics categories as metrics. Page 12

16 Figure 10 - Customer Interaction Analytics Categories in a Performance Management Scorecard Providing Focused Quality Through Quality Monitoring The integration of Verint Customer Interaction Analytics with the Impact 360 Workforce Optimization suite extends traditional quality monitoring with analytics, yielding focused quality insights. For example, quality supervisors may issue a query to search directly for calls related to specific business issues that have been categorized by Impact 360 Speech Analytics. Alternatively, they may set up the Impact 360 Quality Monitoring Smart Inbox to deliver calls of interest for evaluation based on speech categorization results. This functionality eliminates the need to manually conduct searches by setting a quota of calls per speech analytics category to be delivered to a supervisor or business analyst on a regular basis. Impact 360 Speech Analytics categories can also help identify areas of development for individual agents. Once an area is identified, supervisors can monitor, evaluate, coach, leverage best-practice interactions, review agent desktop screen activity, or schedule reports that map categories to other metadata or quality results, such as total quality scores per business issue all from a Web-based portal. Users can instantly open a contact of interest in Impact 360 and leverage a fully integrated workflow to evaluate a call, flag it for a marketing specialist, forward or download it to be shared with other stakeholders in the organization, convert it into a best-practice clip for agent training, and more. For example, calls showing agent inexperience with a new product can be forwarded to contact center supervisors, so that agents can receive the coaching they need. Contacts revealing significant customer dissatisfaction with new pricing can be forwarded to product managers and customer retention specialists for rapid action. A view of the agent desktop screens is also available while playing back calls. This often adds significant insight into the potential process or training enhancements required. Page 13

17 Figure 11 - Supervisor Inbox Populated by Calls Tagged by Impact 360 Speech Analytics Using Data Analytics to Perform Quantitative Trending Analysis The Verint Customer Interaction Analytics portfolio includes Impact 360 Data Analytics, which leverages Verint s patent-protected data mining technology to explain contact center metrics by surfacing call scenarios that are impacting overall performance. Impact 360 Data Analytics leverages data associated with calls to build relationships between data and metrics that determine the root cause of performance. The solution mines call attributes, as well as the context categories identified by Impact 360 Speech Analytics, to uncover hidden trends and surface scenarios that impact these call types. This information can pinpoint positive and negative trends and areas of improvement. For example, a business may know that customers are leaving, but not understand why. Impact 360 Data Analytics can mine customer retention calls detected by Impact 360 Speech Analytics to identify and suggest the root cause of customer churn. This might show, for example, that mid-month calls mentioning competitors are 30 percent more likely to be customer retention calls, increasing the overall rate of customer churn by 0.7 percent. Alternatively, the solution may show that billing-related calls received early in the month are 20 percent more likely to be customer retention calls, increasing overall churn rate by nearly one percent. Without the analysis capabilities of the solution, these significant correlations and trends might not otherwise be uncovered. Leveraging Customer Feedback Surveys Verint s Impact 360 Customer Feedback solution provides highly reliable, scalable, and flexible functionality for conducting post-call IVR and post-contact Web/ surveys. Installed on site (behind company firewalls using internal security policies) it directly interacts with existing telephony and company networks to provide efficient capture and analysis of customer feedback. Impact 360 Customer Feedback provides intelligent, dynamic surveys that can be tailored to engage customers with timely, relevant, and context-based questions. This approach can drive higher response and completion rates while capturing accurate, actionable data. Page 14

18 Customers are presented with one of several language-specific surveys based on the transaction they ve just completed. As they interact with the survey, their responses are used to determine which questions to ask next. Information captured by Impact 360 Customer Feedback is available in real time for analytical reporting, alerts, and workflow. Reports are delivered through an entirely Web-based interface with intuitive controls and drill-down capabilities. Access to data is controlled by the hierarchy scope assigned to the user, to help ensure that users can access data that is relevant to their positions, without exposing data from other parts of the business. Figure 12 Impact 360 Customer Feedback Overview Report Impact 360 Customer Feedback can be merged with applications that mine unstructured data, such as Impact 360 Speech Analytics and Impact 360 Text Analytics, to introduce free-form voice and text comments into survey analysis. For example, an organization can use Impact 360 Speech Analytics to mine the root cause of dissatisfaction for customers who rate the company poorly on a post-call customer feedback survey. Using Reports and Visualization Impact 360 can deliver role-specific reports and visualizations to hundreds or even thousands of business users through the existing business intelligence platform, or through embedded standard reports. At any given moment, users can quickly spot emerging issues, accolades, or experiences that are relevant and actionable. Page 15

19 Impact 360 provides a rich set of tools and charts to make critical business intelligence readily available in a visual format. These views can distribute any specific call set by every data type tagged by the system. Viewing this data can provide insights before users even begin to search for contacts. Each time a user performs a search, the results are visually displayed both in a prioritized list and as a set of selectable graphical views. These visualization features can make searching for relevant information simple. Figure 13 Drill-down Charts For example, when looking into the key issues that drive long calls, users may click on the Repeat Calls category bar and find that an unusual number of repeat calls were taken on a specific date. After clicking the bar, they receive a prioritized list of long calls related specifically on that date, enabling them to examine if anything unique occurred and increased the number of repeat calls. In addition, Impact 360 can enable comprehensive analysis in conjunction with other data sources, such as CTI, CRM, and data captured from agent desktops. The presence of this structured type of metadata, such as the number of transfers or customer identification, can help define multiple filters per category. Going further, Impact 360 can associate interactions with specific individuals via agent or customer identifiers, customer profiles, account numbers, or ANI, thus offering a focused subset of interactions. By correlating structured data with the unstructured content of an interaction, the solution can automatically mine for interactions pertaining to business issues, such as customers at risk of churn, or customers with interest in new product offerings. Once a set of significant interactions is identified in Impact 360, users can take immediate action and leverage the intelligence derived from these interactions by creating an instant report. These reports can reflect business issues or performance trends, helping organizations prepare for change. Figure 14 shows a sentiment analysis report highlighting positive, neutral, and negative customer sentiments in top textual interactions. Page 16

20 Figure 14 Sample Sentiment Analysis Report Customer Interaction Analytics in Action The following sample scenarios illustrate how organizations can use Verint Customer Interaction Analytics to achieve critical business objectives and separate themselves from competitors. Product Development Verint Customer Interaction Analytics can enable a company to develop and manage better products, and target the right customer segments with feature enhancements by surfacing insight on product usage, functionality, and customer needs. This can be surfaced through calls, social chatter, or both. For example, early warning signs of product defects can be addressed quickly, which might help avert or reduce the scale of product recalls. A Verint customer--an electronics manufacturer uses analytics data to provide its product development teams with input from real customers talking about their actual experience with products. Page 17

21 Operations Verint Customer Interaction Analytics data can be imported into performance management scorecards to enable management to track performance in a format that easily identifies variations across time periods or business units/individuals. For example, a communications provider used Verint analytics to determine that its back-office processes were taking longer than initially communicated to customers, which led to millions of dollars in repeat calls, as well as customer dissatisfaction. Armed with this information, the company took corrective action and saved millions while increasing customer satisfaction by 30 percent. Customer Care Verint Customer Interaction Analytics data can be merged with quality monitoring functionality to provide a focused quality initiative. Instead of randomly sampling interactions for supervisor review, a large insurance company is using Verint analytics to drive interactions that fit a categorization profile to supervisors for analysis. Customer Retention Verint Customer Interaction Analytics can be used to increase customer retention by detecting customers at risk, as well as the root cause of defections. For example, a leading payment processing firm has used the solution to identify at risk customers and rank them by dollar value, saving over 2,000 accounts and $6 million in revenue in the first year alone. Marketing Verint Customer Interaction Analytics can identify new emerging opportunities and threats. For example, a large insurance company deploying the solution discovered usage of the term clunkers began increasing dramatically one weekend as customers started to take advantage of the Car Allowance Rebate System. Popularly known as Cash for Clunkers, this 2009 U.S. government scrappage program provided residents with an economic incentive to trade in fuel-inefficient vehicles. The company leveraged this insight to develop targeted marketing campaigns and schedule its workforce during the program period, taking advantage of a $350 million potential annual insurance opportunity. Business Process Analysis Verint Customer Interaction Analytics data can be used by business process analysts as another data source in the studies they typically conduct. For example, a large home mortgage company employs a Service Experience Team to constantly examine business processes associated with customer care. Using Verint analytics, this team quickly found hundreds of thousands of dollars in process improvement from analyzing customer interactions around topics such as billing, taxes, and other common topics. In one key finding, the company determined that the root cause of long phone calls were questions about complicated tax codes that required that agents put customers on hold to do research. By identifying the five key questions via Impact 360 Speech Analytics and providing a quick FAQ for agents, the company was able to reduce average handle time on these calls significantly. Executives Executives can leverage Customer Interaction Analytics via dashboards to understand customer sentiment and how it changes over time, which issues are important to customers, customer loyalty, customer experience, and more. Integration with Impact 360 Workforce Optimization enables Verint Page 18

22 Customer Interaction Analytics to flag and alert executives and analysts across the organization when relevant findings occur. Conclusion Today s organizations are increasingly challenged to collect and act upon the wealth of information derived through their customer communications channels. The complexities of multichannel customer service operations, coupled with traditional enterprise resources that are often unequipped to analyze , chat, social media channels, and Web forums, make the need for multichannel even more pronounced. Verint s Customer Interaction Analytics portfolio can help forward-looking organizations gain an aggregated, unified view of customer service, experiences, and opinions across both direct and indirect customer communications channels. Its pre-built workforce optimization business integrations can enable organizations to capture, analyze, and act quickly to advance their service operations and customer experiences. Page 19