This article recaps a recent episode of Deep Learning with PolyAI. Enjoy this and other episodes here.
The benchmarks for contact center success have traditionally centered on driving average handle time (AHT) down, ensuring high agent utilization, and increasing first-contact resolution (FCR), focusing more on efficiency than experience.
We’re right in the middle of the shift from efficiency to effectiveness. This is causing the metrics for success to change. While efficiency metrics are still important, there’s growing recognition that the quality of interactions matters just as much, if not more.
Connecting efficiency and customer experience
Many companies mistakenly view metrics in silos, causing important aspects of customer experience to be missed. By connecting efficiency and customer experience, organizations can make more informed decisions about improving their contact center’s performance.
Instead of focusing on how to solve problems as quickly as possible, organizations should aim to make interactions meaningful and impactful to build long-term customer loyalty and, ultimately, cash flow. However, striking a balance between efficiency and customer experience can feel like a case of a rock and a hard place; improving one metric comes at the expense of another.
For example, you might choose to keep your agents on the phone longer to enhance first contact resolution and boost your CSAT. However, this approach could increase average AHT and potentially lead to longer wait times as a trade-off.
Creating a holistic approach with conversational AI
A more holistic approach is needed, which requires consideration of operational efficiency, customer sentiment, and engagement throughout the interaction.
Conversational AI and analytics are revolutionizing customer support by providing insights to shape support strategies and influence strategy for every department in your organization.
AI-driven solutions like voice assistants are now integral parts of the customer interaction journey. Rather than treating them as separate entities, organizations are integrating automated tools into the overall customer experience.
Enhancing customer engagement with customer-led solutions
By developing technology solutions that focus on the customer, contact centers can drive engagement that naturally creates efficiencies. In other words, if customers want to talk to the automated solution, they won’t push to speak to an agent.
If the automated system is capable of solving the customer’s problem, you increase first-call resolution. It costs less to handle routine queries that eat into profit margins, and you can redistribute your resources to focus on building valuable customer relationships.
Success metrics should adapt to include engagement levels with automated solutions. Metrics like conversation turns and customer-initiated interactions with bots offer valuable insights into the effectiveness of automated tools in establishing trust and creating positive customer outcomes.
Success metrics and sentiment analysis
As technology evolves, contact centers will be able to incorporate sentiment analysis into measuring success. This means analyzing the tone and feelings expressed in customer interactions to understand satisfaction levels better and find ways to improve. It goes beyond standard metrics, allowing organizations to grasp the emotional side of the customer experience for a more detailed view of satisfaction.
The evolution of contact center agents
The role of contact center agents is also changing. Instead of handling every inquiry, agents are becoming specialists focused on tackling more complex customer issues, leaving routine tasks to automated tools and AI-driven solutions like voice assistants. This shift aims to improve efficiency and make customer interactions more meaningful.
Conclusion
Success in contact centers is no longer just about efficiency; it’s about delivering meaningful, empathetic, and efficient interactions that build trust and loyalty. As technology advances, the future of measuring success in contact centers will require embracing a customer-centric approach that integrates human and automated interactions.
Contact centers must adapt metrics and strategies to meet customers’ evolving needs and expectations. By prioritizing customer experience metrics alongside operational efficiency, organizations can drive meaningful improvements and deliver exceptional service.
