In a previous blog, I delved into the pivotal role of Automated Quality Assurance (QA) in optimizing chatbot and IVR systems, highlighting how expanding the typical QA process from human interactions to bot interactions can significantly enhance the customer experience and operational efficiency. Building on this theme, it’s crucial to explore how advancements in AI technology have now broadened the scope of QA, enabling teams to undertake tasks that were previously considered too tedious or time-consuming. This evolution in QA methodology, particularly through the implementation of AI-powered screen recording, is revolutionizing the way businesses assess and enhance the performance of not just customer-facing agents but back office personnel as well.
Understanding Back Office Agents and Their Challenges
Back office agents are the unseen pillars of any organization, performing tasks that, while not directly customer-facing, are essential to the smooth operation and success of the business. These roles encompass a wide range of activities, from processing applications and handling disputes to managing orders and performing fraud investigations. Unlike their front office counterparts, back office agents traditionally have fewer tools and technologies at their disposal to monitor and enhance their performance, making QA for these roles tedious, costly, and limited in scope.
The Traditional QA Challenge for Back Office Operations
Historically, the quality assurance of back office operations has been a challenging endeavor. QA teams were often relegated to replicating tasks performed by agents to verify their accuracy. This method, akin to a math teacher asking students to show their work, has its drawbacks. If discrepancies arose, pinpointing where agents went wrong was arduous, complicating the process of coaching them towards better performance. Moreover, even if agents arrived at the correct outcome, there was no guarantee their process was efficient or compliant with best practices. This “results comparison” method of QA, while useful, fall short in offering a holistic view of an agent’s performance and operational opportunities for improvement.
Enter Level AI Screen Recording: A Game-Changer for QA
Introducing Level AI’s in-house developed screen recording technology, a revolutionary advancement in back office QA practices. Unlike solutions that rely on third-party platforms, Level AI’s technology is highly customizable, designed to cater to the specific needs of contact centers. This flexibility allows for support across all operating systems, including Windows, Mac, and Chrome, ensuring seamless integration regardless of the hardware environment.
Level AI’s solution stands out for its adaptability, capable of recording an entire agent’s shift or activating based on specific triggers, such as the start or end of a phone call. It handles concurrent chats, offering a granular view of multitasking in customer service. For back office workers, the technology is programmable to commence and conclude recordings in alignment with standard workflow events (e.g., task assigned, task completed), generating non-contact cases within Level AI for precise QA scoring.
This approach transforms the QA process from what was a “results-focused” evaluation to a comprehensive analysis of the agent’s workflow, capturing every action, click, and screen transition. By offering insights into the ‘how’ and ‘why’ behind each task completion, Level AI’s screen recording technology enriches the QA landscape with deeper, actionable insights. Importantly, the recording process is fully automated, removing the need for agents to manually start, stop, or pause recordings, thereby ensuring uninterrupted focus on delivering exceptional customer service..
Unveiling the “How” Behind Task Completion
Level AI’s technology extends its capabilities across various industries and departments, making it a versatile tool for any back office operation. From finance and healthcare to retail and beyond, this solution captures the nuances of agent work, offering a window into their interaction with multiple systems and tools. This visibility is crucial for identifying inefficiencies, ensuring compliance, and understanding the methodologies employed by agents, thus enabling targeted improvements and coaching.
Elevating Coaching and Supervisory Insights
The depth of insights provided by analyzing a broad range of performance metrics enables supervisors to deliver precise, actionable feedback to back office agents, fostering a culture of continuous improvement. Supervisors can now accurately identify inefficiencies, quality issues, and deviations from standard processes, guiding agents towards practices that significantly enhance the quality and accuracy of their work. By focusing on metrics beyond Average Handle Time (AHT) and First Call Resolution (FCR)—including Task Completion Rate, Accuracy and Quality of Work, Process Adherence, Workload Management, and Error Rate—supervisors have a comprehensive toolkit for driving operational excellence. This approach not only improves individual and team performance but also positively impacts customer satisfaction, efficiency, and the overall health of the organization. Through targeted coaching based on these diverse metrics, back office agents are empowered to optimize their workload management, adhere more closely to processes, reduce errors, and ultimately contribute to the contact center’s success by ensuring a high-quality, efficient backend support system.
Moreover, the detailed insights provided by screen recordings, coupled with Level AI’s shared library feature, play a crucial role in drastically reducing ramp time for new agents. By identifying best practices and common pitfalls within the tooling and workflow processes, training programs can be specifically tailored to address these areas. This targeted training approach enables new agents to become proficient in their roles more quickly, effectively shortening the learning curve and allowing them to contribute to operational goals sooner.
The shared library feature in Level AI allows for the creation and sharing of a collection of conversations and screen recordings within an organization. This library can serve various purposes, such as training new users, coaching individuals or teams to improve performance, providing personalized feedback, and establishing best practices. Departments across the organization, such as marketing, product, sales, and finance, can use these conversations and recordings as a source of information.
Agents can refer to these shared resources if they find themselves in similar scenarios to those captured in the library, even when immediate supervision is unavailable for consultation. This access not only accelerates the learning process for new agents by exposing them to real-life customer interactions and responses but also promotes self-improvement among existing staff by allowing them to review their own and their peers’ interactions.
Combining screen recordings with the shared library feature enhances operational metrics by enabling agents to handle customer queries more efficiently, leading to shorter call durations, higher productivity, and increased customer satisfaction. It also supports marketing and product development teams by providing direct insights from customer interactions, which can inform product enhancements and marketing strategies.
Enhancing the Toolbox: Optimizing Agent Performance and Experience
Level AI’s screen recording technology enables supervisors and QA teams to review agents’ tasks as if in real-time, though after the fact, maintaining the task’s original flow. This visibility into agents’ tool use and knowledge navigation is key for spotting improvement areas. Analysis of these recordings helps identify needs for simplifying processes, refining interfaces, or enriching knowledge bases to boost agent performance. This results in more efficient tooling, faster information retrieval, and quicker issue resolution, enhancing service quality.
Moreover, the detailed insights provided by screen recordings play a crucial role in reducing ramp time for new agents. By identifying best practices and common pitfalls within the tooling and workflow processes, training programs can be tailored to address these areas specifically. This targeted training approach enables new agents to become proficient in their roles more quickly, effectively shortening the learning curve and allowing them to contribute to operational goals sooner. The combination of optimized tooling and reduced ramp time not only improves the agent experience but also has a profound impact on operational metrics. Businesses can expect to see an improvement in back office agent KPIs, further underscoring the transformative impact of AI-driven screen recording technology on the quality assurance process and the overall operational ecosystem.
Prioritizing Security with PCI/PII Redaction
Recognizing the critical importance of data security, especially in back office operations where sensitive information is frequently handled, Level AI’s solution incorporates advanced PCI/PII redaction capabilities via computer vision. This feature ensures that all sensitive data captured during screen recordings is securely redacted, maintaining the highest standards of privacy and compliance. This commitment to security is detailed further on our security page, highlighting our unwavering dedication to protecting customer and business data.
The Future of QA with AI and Screen Recording
As businesses continue to embrace AI and innovative technologies, the landscape of quality assurance is evolving. Level AI’s screen recording solution exemplifies how technology can transcend traditional limitations, offering comprehensive insights into both front office and back office operations. This evolution not only enhances the quality of service provided but also propels businesses towards greater operational excellence.
In the realm of quality assurance, the journey towards innovation is continuous. By harnessing the power of AI and screen recording, businesses are now better equipped to understand the nuances of task execution, coach their teams more effectively, and achieve key performance objectives. The future of QA, enriched by these technologies, promises a landscape where excellence is not just envisioned but realized.
