Boosting customer satisfaction is more important than ever before. Consumers today live in an instant gratification society and are not only choosier with how they spend their money, but also demand an exceptional customer experience. Now's the time to take control and learn how to improve customer satisfaction and reduce operating costs by reading VPI's article on 'Quality Assurance 2.0: Using Analytics to Focus QA on Outcomes," which has been featured as the top story in the Quality Assurance & Training Connection (QATC) newsletter.
Quality Assurance 2.0: Using Analytics to Focus QA on Outcomes
By Patrick Botz, Director of Workforce Optimization, VPI
As the economy continues to slowly recover, organizations remain under pressure to further reduce their contact center operating expenses while optimizing the customer experience – all without making major resource investments. To accomplish this, it is absolutely crucial to gain a thorough understanding of customer needs and expectations. This is particularly pertinent right now due to the fact that the economy has strongly impacted the spending habits and priorities of most consumers, while social media and mobile technologies have improved their knowledge and increased their demand for high, immediate satisfaction. As consumers become much more sophisticated, delivering an exceptional customer experience across multiple touch points goes beyond the traditional integration of technology – it requires improved agent skills and the real-time orchestration of the full array of the contact center’s knowledge resources and relevant applications by making them more intuitive and efficient.
The Need for Better Call Center Quality Assurance
There are several key factors driving organizations to re-examine and re-focus their contact center quality assurance (QA) efforts. According to a recent Harris Interactive Customer Experience Impact Report, 86% of consumers will quit doing business with a company because of a bad customer experience, up from 59% just four years ago. And with the advent and growing popularity of Social Media, word now travels faster than ever before – it takes just seconds for a customer to rave about or complain to thousands about that poor experience with your contact center via blogs, Twitter, and Facebook.
Customers are also now becoming more comfortable with the idea of using self-service channels such as the Web and IVR for basic inquiries or tasks, such as checking an account balance or merchandise shipping status. When they actually take the time to call into the contact center, customers expect fast and competent answers to more complex inquiries. The majority of those phone interactions are far more important to individual customers than ever before, thus the QA of these communications is becoming more important than ever before.
With so many consumers demanding a better quality customer experience, what’s alarming is that, according to a Customer Experience Peer Research study conducted by Forrester Research in 2010, only 30% of organizations incorporate the needs of target customers into their decision-making process and only 31% closely monitor the quality of interactions with target customers.
Limitations of Traditional Quality Assurance
Traditional contact center quality assurance (QA) has been used to monitor and improve internal agent quality and compliance. This involved random recording or the selection of a small random sample from all recorded calls. The objective was to confirm that agents exhibit desirable behaviors, without deviating from prescribed internal rules, scripts, and policies. The outcome of the evaluation was then reflected in the agents’ compensation. These traditional QA tools and processes are often too cumbersome and inadequate to embrace the latest customer mindset - they were not really designed for this purpose. The fragmented, unfocused data they deliver hardly provides any reliable business insights at all, and they often limit or stifle the cognitive abilities of contact center agents and supervisors, dulling their motivation to do well for their organization.
The five major shortcomings of traditional QA are:
1. Primary focus on the agent – Most recordings of customer-agent interactions carry relatively low business value. Consequently, most random samples of recordings are likely to provide low-value information With these limited insights, managers are unable to make informed business decisions, unless other tools are engaged to look at customer communications from a more intelligent perspective. This process clearly fails to balance agent excellence from a customer or business perspective with internal compliance.
2. Although traditionally seen as “objective,” random QA monitoring is wasteful – Evaluating low value interactions with a QA template that takes upwards of 30 minutes on average to complete when scoring a two minute contact only adds to the cost of an already expensive interaction.
3. Manual, time-consuming workflow – Traditional QA often involves many manual, tedious, arbitrary tasks that do not take attributes of different types of calls into consideration, assuming that the contact center is already providing the right products and services to its customers. Not only does this expend resources and drive up costs needlessly, it misleads contact center managers into attacking the symptoms of deficiencies rather than their root causes.
4. Difficult to assess effectiveness – There are many cases when QA evaluations are performed in bulk at the end of the month. Feedback and coaching is then given to the agents at month-end when they have already forgotten about the interaction and can no longer make a connection. Plus, most businesses have found themselves stuck in the rut of adding new QA components to an already hefty QA form, only causing unbelievable customer dissatisfaction, organizational turmoil, and reduced agent morale and job satisfaction.
5. Siloed from other important systems – Traditional QA systems and reports were siloed from other contact center performance management systems. There was no easy way to coordinate delivery of agent training assignments that were based on a combination of QA scores and Key Performance Indicators (KPIs). And, there was no way to report on how improvements in QA skills impacted other contact center performance metrics, such as whether customer satisfaction was improved or sales increased.
The Rebirth of Quality Assurance
Traditional contact center QA has reached the end of a good long life. The new generation of QA goes far beyond internal agent compliance – representing a rebirth and evolution of the concept of QA designed to meet the needs of today’s contact centers. The new approach provides insight and information – not only on agent performance based on compliance with internal rules and critical industry or legal regulations, including PCI DSS and HIPAA – but it also measures the customer experience, business value, and performance of various technologies that support the transaction. It does it much more efficiently than ever thought possible. The new, intelligent QA systems
rapidly identify and deliver insights into critical business issues and opportunities to improve the customer experience and revenue. Perhaps most importantly, Quality Assurance now encompasses the entire process of doing good business throughout your contact center.
Shifting the Focus of QA from Agents to Desired Outcomes
Leading contact centers are beginning to focus the Quality Assurance process on the business areas that they want to improve most. They capture all of their multi-channel customer interactions and then automatically categorize and prioritize them for review and quality evaluation by type and business value. Utilizing analytics and workflow automation, new QA tools can also reduce the manual steps required by most QA applications by 60 to 80 percent.
Customers are not as concerned about an agent following company script as they are in ensuring that their issue is resolved. In fact, most customers appreciate customized contact handling for their specific needs, and frequently disengage when being offered standard scripts or approaches. Most customers are focused on receiving fast, courteous assistance while getting information or issues resolved, so the QA forms and processes used for monitoring should focus on that, with the most critical component being issue resolution, and/or first contact resolution (FCR), tied to a specific issue that the customer calls about. Customer opinion should become an inseparable component of today’s QA.
In these days of enlightened leadership and sophisticated technology, call quality monitoring has evolved from internal surveillance to performance improvement and skill development. With the latest, analytics-driven QA technologies, you can interact with a variety of data and rapidly uncover and help address critical business and customer experience issues across all customer communication channels – cost effectively and rapidly. These unique, unprecedented tools equip contact centers to improve the overall customer experience and bottom line in ways that were previously only possible with complex, costly analytics.
Desktop Analytics Powering the New Generation of QA Tools
Desktop screen analytics is making automated call categorization and prioritization according to each call’s business value for Quality Assurance easy. It can be used to automatically pull critical business data like Customer ID Number, Case ID Number, Account ID, sales order value and collections values directly from application screens or application fields accessed or entered by your employees – and tag that value data to appropriate points within recorded interactions. Organizations are also tracking information like: “Was the call put on hold?”, “Was it transferred?”, “What level of employee was it handled by?”, “Was it a VIP customer?”, “Was there a sale or no sale?”, “What was the value of the sale?”, etc. When enriched with this data, recordings can be organized, reported on, and analyzed very effectively, even before being played back. What’s more, evaluation forms can be pre-scored with performance and business statistics, increasing their value.
Automated Call Categorization and Intelligent Sampling
As Desktop Analytics mechanisms gather the data, new QA systems can automatically classify your most important calls so that you can focus your evaluation and analysis efforts on high-value calls. This may include calls from high value customers, high value transactions, costly repeat calls, missed up-sell opportunities, long hold and handle times, multiple transfers or escalations, and calls with a specific product focus or product issues.
Recordings tagged with metadata help organizations take action based on high-value attributes. For example, in order to identify and analyze low First Contact Resolution (FCR) rates, they identify and monitor inbound interactions with the same case ID – or same customer ID and the same reason for contact – in the last X number of days, and all such related calls would be automatically associated. Evaluators who focus on FCR may then discover that a recently introduced new product or service is affecting FCR adversely. Other types of root causes may drive the call activity for the same account. For instance, new agents to a program may be misdiagnosing the problem or misinforming the customer. Furthermore, they may be inputting wrong or inaccurate call work codes for the same account or case ID. Latest-generation QA systems can uncover these hidden causes, even without complex performance analytics or speech analytics.
Managers can now quickly find and pinpoint the issues that have the greatest impact on contact center operational costs and customer experience. This allows contact centers to maintain their current sample size of calls to be monitored each month – with increased business impact.
Leveraging Business Rules to Automate QA Workflow
Classifying calls with metadata is one piece to the puzzle, but the primary logic behind the operation of the latest-generation QA system is the Business Rules engine that takes a wide variety of automatic actions based on call, screen, and QA information collected. Instead of having your QA evaluators manually hunting and pecking through a pool of calls for potential evaluation, the rules engine automatically takes care of this by recognizing high-value interactions, assigning the right form to use for inspection, and assigning tasks to the people best qualified to perform the evaluation of each type of interaction. The call selection criteria may be driven by data about the interaction outcomes, such as product or service sales. Agent quality can still be assessed at the same time, via the same evaluation form – when calls for review are identified by the same criteria for each agent, individual agents are being reviewed objectively.
Meanwhile, a C-Level Executive in Sales and Marketing may be interested in reviewing specific highest value sales interactions with high-value customers regardless of which agent fielded the call. She may be looking at the workflow from an entirely different perspective using an entirely different evaluation form, or no form at all. Perhaps she’s interested in judging how a new bundled offer is performing. Sure, the agent behavior may still be a component of the review, but performance of the offer itself may be more interesting to the sales teams.
The new approach to Quality Assurance takes a much more comprehensive attitude towards measuring and improving customer interaction quality in ways that benefit today’s customers and business organizations alike. This next-generation approach supports your team’s ingenuity as you define goals for your contact center performance. It allows you to measure key criteria and interactions that are central to goals, identify and confirm root causes through analytics driven quality monitoring, improve agent behavior and critical processes through real-time alerts and targeted Coaching and E-learning, and develop a secure, central framework to continuously control the processes and monitor results.
Times change, and we don’t know what tomorrow will bring. Technologies continue to evolve and customer needs and demands will undoubtedly change also. This is why it is vital to strive to provide the best possible customer experience on an ongoing basis, and adopt the tools and methodology that will enable you to evolve and prepare for the challenges that lie ahead. Thanks to the new QA solutions and processes currently available, you can now take control of your organization’s ability to meet the challenges and demands that lie ahead.