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Customer experience (CX) is at the heart of today’s competitive business landscape, shaping not only brand perception but influencing long-term loyalty and growth. MaestroQA’s recent CX Summit: The Art of Conversation brought together industry leaders, experts, and practitioners to explore the future of Quality Assurance (QA) within this critical domain.
From the role of AI in shaping customer interactions to the transformative impact of targeted QA approaches, the summit uncovered several trends that are redefining how businesses approach customer support, quality assurance, and agent performance optimization.
In this blog, we will delve into the six biggest tech trends revealed through the CX Summit Workshops which featured win stories and challenges from 50+ companies and experts in QA and CX. These trends point to one overarching theme: businesses are looking for ways to unlock the goldmine of data and insights inside their customer conversations and interactions. They want to take their CX strategies to new heights and gain an edge over the competition.
One trend that dominated discussions at the CX Summit was the growing use of Targeted QA. This practice takes QA beyond random sampling, aligning it with your business’s highest priority customer touchpoints, processes or policies to reveal deeper insights into specific business problems and opportunities.
Why is it so effective? It's all about precision and focus. With Targeted QA, companies can proactively address issues and optimize resources, ensuring the best possible customer experience. For example, one successful financial tech company shared their unique approach to Targeted QA. They utilize Targeted QA “sprints” to quickly analyze the quality of their product launches. Instead of waiting for problems to arise, they align Targeted QA with their product launch schedule to ensure agents are well-prepared and equipped with the necessary resources and training to ensure the rollout goes smoothly.
“By concentrating on high-priority customer touchpoints and specific business problems, targeted QA gains deeper insights and uncovers timely and actionable opportunities for improvement.” - Group 6
Another company shared how they wanted to reduce cost per contact and average handle time (AHT) was a major contributor to this. After implementing Targeted QA workflows to automatically surface and evaluate tickets with high AHT, they discovered that a long verification process was a primary driver in AHT so they were able to take actions to simplify this process, which effectively resulted in reduced AHT.
The shift towards targeted QA is not merely a trend, it’s an evolution in QA practices that is proving to be instrumental in optimizing resources, focusing on critical areas of improvement, and enhancing overall customer experiences.
In the world of customer support, the role of Quality Assurance (QA) is undergoing a remarkable transformation. It's no longer just about evaluating agent performance; it's about nurturing growth and excellence. The discussions at the CX Summit highlighted this inspiring trend — with many leaders pointing out that they are reframing QA from being perceived as the "bad guy" to becoming a genuine partner in agent development.
"Making sure the agents know we're here to help and not to criticize. The ultimate goal is to offer the best customer experience possible by enabling our agents to perform their best.” - Group 7
This trend is creating a culture where feedback is not just seen as a critique but as a catalyst for improvement. The presentations among industry peers at the Summit demonstrated that the most effective QA teams were those that directly linked QA outputs to agent development and growth strategies.
For example, one company shared that by implementing scorecards targeting new hires, QA helps catch, coach, and correct bad habits early on. This proactive approach nurtures a culture of high-quality customer interactions from the very outset of an agent's tenure.
Another company shared how they use quality data and clear benchmarks to provide agents with a roadmap for career development. By setting expectations and using QA scores to verify readiness for promotion and upskill training, agents are empowered with a clear and motivating growth path.
A company with a 100% remote support team also emphasized using QA to help agents feel supported and empowered. They shared how collaboration and trust was central to their success. By having team leads jointly shape the scorecard evaluation criteria with feedback from agents not only created more buy-in but paved the way for a more impactful coaching program.
What made this collaborative process even more effective is the utilization of tools like MaestroQA. With the ability to add examples to coaching sessions, agents are equipped with a laser-sharp focus on improvement areas and a better understanding of success criteria to implement feedback quickly and effectively. This targeted approach has led to increased engagement for both internal and BPO agents and team leads.
"Having a structured coaching program within MaestroQA has been a huge win for both internal and BPO agents and TLs. Increased engagement due to direct and targeted feedback." - Group 3
In the ever-evolving world of customer support, the saying “What gets measured gets managed" holds more relevance than ever. The CX Summit discussions spotlighted another trend that’s reshaping how companies approach agent performance measurement: the use of data-driven insights to propel agents and teams towards enhanced performance.
Central to this trend is the transformation of agents into active participants in their own professional growth. We heard several people at the CX Summit share how providing agents with direct access to QA grades, feedback, and performance metrics from their own dashboard has ignited a sense of personal ownership over their growth journey. This not only boosts internal engagement, it also fosters a heightened sense of accountability.
Another person pointed out the impacts of using data and dashboards to spark a “healthy competition” internally. By providing visibility into performance metrics and benchmarks, agents and teams can track their progress, identify areas for improvement, and celebrate milestones. As a result, team members are more connected to their performance and are motivated to continually raise the bar, culminating in an environment of self-driven excellence.
“We started comparing team and individual performance, it sparked healthy competition internally which drove up agent morale and engagement”
Lastly, we also saw an insightful example of how coaching data surfaced through QA can be a highly useful metric to track. One company discussed how they use MaestroQA’s platform to analyze the correlation between the number of coaching sessions led by managers and fluctuations in Customer Satisfaction (CSAT) scores. This correlation forms the basis of new metrics, opening doors to deeper insights into how training and coaching influence core metrics like CSAT and QA. It's not just about the numbers; it's about the impact. QA and CX leaders were most excited about the ways these insights gave them the datapoints they needed to create and propose an on-going roadmap for agent and call center training and coaching that actually accelerates customer satisfaction in a measurable way.
CX technology is undergoing a huge transformation, largely driven by the rise of AI. As we delved deeper into discussions at the CX Summit, it became clear that AI's potential is immense, however, finding the right balance between AI and human intervention is crucial for achieving optimal results.
One sentiment shared broadly across people at the Summit was that AI should not be seen as a replacement for human agents but as a complementary tool that enhances efficiency and effectiveness.
A prime example of this is the integration of AI in real-time assistance and chatbots. Rather than displacing human agents, AI is seen as a tool to ensure human intervention is concentrated where it's most valuable. A common strategy shared was leveraging AI-driven chatbots to “deflect volume” by handling routine queries and straightforward tasks, freeing up skilled agents to tackle more complex and nuanced customer issues. Other ideas companies are looking at include the use of generative AI for suggested replies for agents and conversation summarization for escalations.
As one group aptly put it, "Don't expect AI to fully replace QA, but to complement it in a directional manner." The prevailing sentiment among customers was that while AI could provide insightful trends at scale, it still requires human intervention to make informed decisions and interpretations.
"Don't expect AI to fully replace QA, but to complement it in a directional manner."
Research into AI's capabilities to identify trends at scale, whether in agent performance or policy adherence, emerged as a focal point. Customers expressed a desire for AI to guide their QA efforts, pointing out areas that demand attention and strategic intervention. While confidence in AI's ability varied, most attendees acknowledged the necessity of human oversight to ensure AI-generated insights align with the business's values and objectives. So many group presentations concluded that using QA to monitor AI accuracy was essential to avoid potential legal or reputational damage that could come from an AI chatbot responding to customer questions.
“QA on chatbots will be critical” - Group 6
In the pursuit of enhancing quality assessment practices, the concept of Auto QA and the identification of "hot spots" emerged as a driving force. By marrying various metrics and harnessing AI capabilities, QA teams can proactively identify friction points and high-impact areas that warrant immediate attention, enabling businesses to swiftly adapt to evolving customer needs.
The transformation brought automated quality metrics cannot be overstated. Shifting from random sample assessments to analyzing 100% of support interactions empowers QA teams to extract valuable insights from every customer interaction.
“We want the ability to see trends at scale to know where to target our QA efforts” - Group 6
However, a recurring sentiment was the acknowledgment that not all AI-driven solutions are equal. As one group put it, "bad AI is worse than no AI." While automated solutions hold immense potential, their accuracy and reliability remain crucial. This stance underscores the importance of combining AI-driven insights with human expertise to ensure that the solutions' outputs align with the company's values and desired customer experience.
An overarching theme within this trend was the desire to extract meaningful trends at scale, aiding in the strategic targeting of QA efforts. Whether it's identifying areas of improved agent performance or pinpointing policy-related concerns, customers expressed a need for AI to guide their QA strategies. This sentiment underlines the evolving role of QA teams from reactive evaluators to proactive enhancers of customer experience, facilitated by the insights generated from AI-assisted analytics.
This exploration of AI-powered CX operations also shed light on another big trend discussed at the summit: the need for highly custom metrics and KPIs to deliver enhanced insights.
“Sometimes driving toward ‘Business level metrics’ is not in alignment with agent level experiences”
Several companies pointed out that blending metrics is needed to bridge the gap between leadership's priorities and QA teams' coaching needs. It's about transforming data into actionable dialogue. One presentation acutely pointed out the need to “blend metrics” like NPS, CSAT, AHT with metrics that QA teams or CX management needs to coach to (FRT, hold times, sentiment, tone, empathy) in order to impact NPS, CSAT, etc. This approach ensures that data is not just numbers but a tool to enhance customer interactions.
One presentation noted that traditional productivity metrics like AHT and FCR lack the context needed to make actionable decisions. For example, they were seeing a spike in AHT and normally they would attribute this to an agent performance issue, but the customer was able to work with MaestroQA to use targeted QA and root cause analysis to get more contextual data points and insights to understand that the issue was actually due to an issue with their return policy.
The next wave of QA insights will bring a new dimension to CX analytics, going beyond standard KPIs metrics to gain a deeper understanding of the customer sentiment and root the cause behind adherence issues, agent performance problems, or policy/process issues.
Here are a couple notable examples of companies already moving in this direction:
The trends emerging from the Summit point to an industry that's not just responding to change but shaping it. From Targeted QA to AI's complementary role, from empowering agents to the emergence of custom metrics, the trends speak of a world where customer interaction is an evolving dialogue, rich in insights and opportunities.
Businesses are no longer just serving customers; they are engaging with them, learning from them, and growing with them. The Summit was a reminder that in the world of CX, every voice matters, every interaction counts, and every insight is a step towards a more connected, responsive, and empathetic business landscape.
Check out the full recording of the Art of Conversation: Keynote Address or sign up to attend our next CX Summit, and if you would like to learn more about what MaestroQA can do for your business, please request a demo today.
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