The Evolution of QA in Customer Service: Insights & Predictions
A summary of the most noteworthy takeaways from our CX Summit keynote presentation
Key Insights and Trends
Navigating the Future of Quality Assurance
Understanding the transformations underway in QA is crucial for businesses to not only keep pace but to drive excellence in their customer support and call center operations.
Increased Pressure on QA Teams
In today's economic climate, QA teams are under immense pressure to prove the value of their programs as customer expectations soar. According to a recent poll, over 90% of respondents feel this mounting pressure. To meet this challenge, businesses must invest in robust, data-driven QA programs that offer meaningful insights into support operations and customer experiences.
More than 90% of QA teams indicated feeling increased pressure to demonstrate value.
Struggle to Measure the Impact of QA Programs
Businesses now demand more than just QA enhancements; they want actionable business insights that drive their bottom line. However, many QA teams struggle to measure the impact of their programs effectively, in fact 75% of survey respondents reported this fact. At the heart of this struggle lies a “data black hole,” a challenge experienced by countless businesses. Astonishingly, over 50% of organizations report that their valuable QA data remains isolated in silos, disconnected from other crucial metrics. Even more concerning, a staggering 17% admit to not being aware of where their data is stored.
Rebranding of the QA Function
In response to changing times, businesses are starting to rebrand their Quality Assurance programs as “Performance Excellence, “Quality as a Service” or “Continuous Improvement Teams” to reflect the evolving role and value of these teams within organizations. This shift goes beyond semantics; it represents a fundamental transformation of the QA team's mission and purpose, aligning it more closely with the broader goals of exceptional customer experience and business growth.
We changed our team name from Quality Assurance to Performance Excellence.”
Automated quality metrics will become a core KPI, providing better insights into customer interactions.
Rise of Automated Quality Metrics
The need for comprehensive and accurate insights into customer interactions has never been greater. To address this demand, QA teams are increasingly turning to automated quality metrics as a core Key Performance Indicator (KPI). These expand the potential of QA by leveraging AI, speech and text analytics to analyze 100% of customer conversations, providing valuable and real-time feedback on the quality of interactions between customer support agents and callers.
So what’s the goal of these automated metrics? To guide businesses on where to look, pointing them to the hotspots requiring attention and detailed root cause analysis.
Targeted QA - A Shift from Random Sampling
Automated quality metrics have transformed QA programs, analyzing 100% of support interaction instead of a small random sample. This change allows QA teams to focus on targeted deep dives, understanding the "why" behind certain metrics' spikes. The move towards Targeted QA has even given rise to “QA sprints”. These approaches are designed to tackle specific issues and challenges in a focused and time-bound manner, empowering QA teams to identify root causes, make data-driven improvements, and respond rapidly to changing customer needs.
QA teams will move from primarily Random to mostly Targeted
Rise of Blended Metrics to Identify “Hot Spots”
We predict that in the future, automated QA will stand shoulder-to-shoulder with traditional metrics like CSAT and AHT. With the integration of various metrics, QA teams can identify “hot spots” of friction and areas that demand attention. This proactive approach empowers businesses to rapidly respond to changing customer needs and make data-driven improvements.
Conclusion
The evolving landscape of Quality Assurance presents significant opportunities for businesses to enhance their support operations and customer experience. While automation will play an increasingly critical role, human intervention remains crucial. Automated quality technology will complement the capabilities of QA teams, guiding them towards areas that require their expertise.
With the use of automated quality metrics, businesses can gain data-driven insights that empower them to make informed decisions, optimize their customer support processes, and drive overall excellence in customer service.
Is it time to embrace the change and dive deeper into MaestroQA?
Phases of QA Evolution
- Compliance and Process Adherence: Establishing a foundation of rule-following, security, and regulatory compliance.
- Customer Experience Focus: Balancing business requirements with a shift towards customer-centric quality programs and flexible agent interactions.
- Performance Excellence: Looking at QA data in concert with all the other metrics you care about to strategically pick hotspots and measure the impact of QA
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