(This article originally appeared in the August 2010 issue of CUSTOMER INTER@CTION Solutions)
Contact centers face a tough crowd: customers and executives who are watching their wallets as the economy struggles to expand. Performance analytics solutions can help win them over indirectly and directly, by providing invaluable and timely information to help cut expenses, increase agent effectiveness and output, retain customers, and attract others through referrals (especially via social media), and save sales and grow revenues.
Customer Interaction Solutions contacted a select group of performance analytics professionals to get their insights into the role these solutions play. We asked them questions on:
· General trends and drivers
· Impacts from wireless and social media use as well as speech and text analytics
· New features added to performance analytics solutions and benefits, and
· Solution costs.
The following are comments from these industry thought leaders.
Ron Hildebrandt, Founder and Senior Vice President of Marketing
There is an emerging need and interest Enkata sees on the part of customers to build a comprehensive analytics plan for the contact center that includes performance analytics and speech, text, and desktop analytics. Speech and text analytics will continue to receive a great deal of attention, but confusion arises as to the role they play in operational performance versus voice of the customer or customer sentiment insights. Performance analytics that correlates data from multiple sources will continue to drive KPI and operational improvements. An emerging new category, desktop analytics, will provide an additional, net new data set for performance improvements tied to desktop efficiencies and skills.
There does seem to be a renewed emphasis on understanding and improving the customer experience. But as always, cost and ROI are key drivers in any decision. We see three trends:
1. Companies need a total view of the customer experience that crosses all channels, including voice and Web self-service and live assistance models.
2. First call resolution (FCR) is emerging as the metric of choice to improve the customer experience (customer satisfaction) while reducing costs by eliminating repeat calls.
3. There continues to be growing deployment and reliance on analytics applications that provide insights into the customer experience, but that also correlate data to outcomes with an operational impact on agent performance, processes and continuous improvement
There’s clearly a growing use of performance analytics to understand the total customer experience and, particularly, the self-service experience and, as importantly, the experience when moving from self-service to live assistance and visa versa. Unlike speech or text analytics, performance analytics can correlate data from multiple sources, including voice and Web self-service applications. This total view supports operational changes across channels and across the self-service/live assistance experience and identifies where breakdowns in customer service occur – systems, processes, or human resources?
Ironically, self-service applications have placed higher demands on agent skills and performance by virtue of the higher saturation of the complex, more challenging calls they now support. Higher skill requirements place added demands and dependencies on quality monitoring processes and agent development programs such as coaching, training, and self-improvement.
Both of these techniques, speech and text analytics, combined still only provide a limited view of the customer experience focused on voice of the customer issues and customer sentiment. Speech and text analytics are restricted to specific channels, which is why there is a need for integration of speech for voice channels and text for e-mail and chat.
The integration of data from multiple sources and these multiple analytics applications is a demanding, new requirement to create a total view of the customer experience. Those applications, such as performance analytics that can consolidate data from multiple enterprise and channel sources and distill information from 100 percent of calls, will likely emerge as the core analytics platforms moving forward. --
The most important development is the emergence of a new category of performance analytics, desktop analytics. This capability monitors agent desktop activity much in the same way that call recording monitors agent and customer voice calls for quality purposes.
In the case of desktop analytics, the goal is to understand agent behaviors when using the desktop, including application usage, navigation efficiencies, compliance issues, workflow efficiencies, for the purpose of identifying areas for coaching and improvement and for identifying best practices for broader application.
This is a new and exciting area for performance analytics. Today, contact center managers have zero visibility into how agents perform using desktop tools and practices. It is a huge opportunity to dramatically impact average handle times and reduce costs. Enkata’s research and feedback from customers indicates that 20 percent to 30 percent of call time is wasted performing non-productive desktop tasks. Consistently, contact center managers ranked inefficient use of knowledge management systems as their highest priority to understand and improve.
High costs in the past were primarily associated with implementation costs due to data source integration requirements. A major new development in this area has been the ability to capture much of the customer transaction data directly from an agent’s desktop. In the past, the requirement was to pull data from multiple, disparate data sources throughout the enterprise. That meant higher implementation costs but also longer time to results, sometimes as much as nine months, creating a major barrier to adoption. By pulling data directly from the agent desktops for every customer transaction, the need to integrate with disparate, multiple data sources is all but eliminated. The same projects that took multiple quarters to complete are now able to be completed in one to two months. Enkata believes that this one development will dramatically shift the adoption rates for performance management applications driven by lower cost and faster time to results.
Performance analytics continues to be a key component in driving the success of an enterprise. Perhaps now more than ever, the focus is on analyzing data to uncover performance issues and increase the effectiveness of performance, especially in the areas that contribute to cost control or cost reduction. Another driver of analytics is cost avoidance, which can be achieved through initiatives that reduce customer churn or increase the handling of more diverse and complex tasks with the same, but better skilled, resources.
As expected, continuing economic challenges tend to put more pressure on cost than satisfaction. However, the more visionary enterprises are able to correlate satisfaction to costs and address both simultaneously. Performance analytics is a primary tool used to identify and exploit the correlation. The use of analytics to identify topics or issues that can be handled through self service or alternative media instead of calls is not new, but may be seeing resurgence as companies look for methods to reduce costs.
Further, optimizing customer dynamics is the key to maximizing customer experience while containing costs and streamlining operations. The ability to capture and understand customer intent, analyze that intent to gain insight and use that insight to impact the entire organization is a powerful differentiator for companies in any economy. Optimizing customer dynamics also delivers value across a wide range of business imperatives. These benefits include managing the risks associated with compliance and fraud and streamlining operations to run efficiently and effectively. They provide a customer experience that sets a company apart from its competition and expands value beyond the contact center into sales and marketing organizations, the back office and, ultimately, the entire enterprise.
Customer dynamics optimization includes capturing and understanding customer intent across all channels, including social media. As social networking continues to grow as a result of new services, new media, and a new demographic of users, the ability to monitor and analyze what customers are doing or saying indirectly across multiple channels can create a differentiator for a company. When interactions occur in the form of unstructured data, such as free-form text messaging, tools are needed to mine those interactions for insight. The challenge is determining how to gain access to the interactions and develop an understanding of trends, rather than simply responding to individual issues. Without a dialogue to evaluate, analyzing text out of context on social media may lead to false findings or assumptions.
Integrating business intelligence and analytics with quality, workforce and performance management tools has become an essential step, as has the incorporation of back office management into the performance analytics data set. Extending data capture and analysis to the desktop is a new domain for performance analytics solutions. Capturing desktop application usage, monitoring a process end to end, and attaching metadata to enhance the analysis will soon be considered must-have features for quality management, workforce management and performance management. These tools apply to the inbound, outbound, back office environments, and basically anywhere there is a customer transaction or supporting transaction. Applying proven performance analytics processes to this new data set from the desktop will uncover significant opportunities to increase customer satisfaction, improve both employee and customer retention, and reduce costs.
Historically, vendors delivered performance analytics through third-party business intelligence solutions that were sold separately. These solutions tended to be quite expensive as well as only lightly integrated with the vendor systems. A significant shift has taken place whereby vendors can tightly integrate performance analytics solutions in order to greatly increase the value and benefit delivered. In addition to the analytics tool set, vendors are providing extensive metadata definitions. This greatly reduces the time and effort a contact center user expends in exploiting the wealth of data to affect performance in their organization. The integrated solution approach has also greatly reduced the initial investment and ongoing cost of ownership.
Panorama Software (www.panorama.com)
Rony Ross, Co-founder and CTO
Contact center managers are realizing more and more that there is a need to define and use KPIs to evaluate employee performance and customer satisfaction. We believe there is a shift from cost control to improved customer satisfaction, and we see more usage of speech recognition systems directed at identifying customer dissatisfaction.
Overall we see a couple of major trends happing in the performance analytics industry:
Relevancy of information
Data at the fingertips of the agents to help increase customer satisfaction and close calls quicker
It is interesting to see that contact centers managers prefer to push analytics and KPIs down to the agent level. As customers prefer to have their issues solved more quickly, there is a mutual interest for contact centers to ensure relevant data is available to agents. Pushing data in real time to the agent is, therefore, becoming more critical.
Empowering agents to conduct self-service analytics is a huge trend we are seeing. As contact centers, managers and agents become more sophisticated, the need for self-service analytics without involving IT is growing. In most cases, contact centers need to conduct fast analytics on specific issues to deal with them quickly. Waiting for IT to create views and reports for them isn’t an option any more.
There are so many best practices happening inside the contact center, yet nothing is being shared. This is going to change from the ground up. Social intelligence is going to be the fastest growth area in contact centers. Agent will save and share intelligence processes, discuss them in real time, and collaborate with other agents, “following the sun.”
New systems, like Panorama, have social intelligence embedded in them. They practically bring together the best of the analytics processes among all the group members, sharing best practices within the systems.
Collaboration with callers
A new big area of growth we see is collaboration between contact centers and callers (e.g., customers). Contact centers now allow callers to conduct their own analytics on bills, products, warranties, allowing more self-service and shorter resolution times.
We see a growing need for combining analytics from various sources, for example, quantitative and textual. We see a growing trend to do speech search or text search in analytical data, where the user wants to be able to ask questions like, “Show me the calls from certain type of customer in a certain area that are relevant to a certain issue for the past year.” The user expects the system to be able to interpret this question and retrieve the relevant view or report. He may also ask to see all the reports that involve a certain customer when the customer is on a call.
Or, when an employee indentifies a problem during an analytical session, he expects to open a discussion about the issue with his boss. The system has to be able to provide him with the relevant facility for such communication.
We actually see the cost of analytical systems decreasing and quite a few vendors can really show much lower total cost of ownership (TCO) than before. The prevalence of analytical infrastructure systems that utilize industry standards (such as Microsoft’s (News - Alert)) and that are open for integration with common environments (like MS Office) makes the TCO paradigm much more affordable.
Brendan B. Read is TMCnet’s Senior Contributing Editor. To read more of Brendan’s articles, please visit his columnist page.
Edited by Stefania Viscusi