Call centers are adopting AI and automation tools. According to a 2023 report, 83% of call centers consider AI a high priority, reflecting the significant shift towards adopting AI and automation tools in the industry.
But, this very adoption brings a new challenge: effectively integrating these technologies with traditional methods, specially in the learning and development context, where manual training and QA has been king so far. However, the truth is that relying solely on outdated manual methods can miss all the great benefits that AI brings. The ideal solution is a balanced combination that utilizes AI’s strengths alongside the unique expertise of human coaches.
Incorporating AI for coaching alongside human intelligence for nuanced feedback is crucial for maintaining excellent customer service. This blend ensures that as call centers adopt more advanced technologies, they can still provide personalized, high-quality customer interactions.
Traditional QA involves selecting a small sample of calls for review by analysts who evaluate various aspects such as call handling, script adherence, and customer satisfaction. Insights from these QA analysts are used for agent performance improvement. However, in today's industry, where the big companies have thousands of agents and several lines of business, this method falls short.
Coaches are not able to provide training and feedback in a consistent and scalable way, affecting operations at their very foundations. Traditional QA and coaching processes have significant limitations. Typically, only a small sample of calls are reviewed, leaving a vast number of interactions unchecked and potentially missing critical issues or trends. Additionally, the subjective nature of human auditors can introduce personal biases into their evaluations, affecting the objectivity and consistency of the feedback.
Furthermore, coaches and QA analysts often focus on a limited set of criteria during their reviews, which means they may overlook a few important details that might be crucial for comprehensive QA. This narrow focus can prevent the identification of broader patterns and areas for improvement, limiting the overall effectiveness of the coaching and the QA process.
AI coaching, such as SymTrain's Intelligent Coaching, comes in to transform performance by automatically ingesting and analyzing any agent’s call recordings. This comprehensive approach leverages data analytics to process call recordings, associated metadata, and QA scorecards, pinpointing exact areas for improvement in an agent’s performance.
AI-driven customization in call centers significantly enhances agent performance by creating personalized coaching programs at scale tailored to each agent's unique strengths and weaknesses. This targeted approach really accelerates skill development and boosts frontline performance in days, resulting in a more competent and confident workforce capable of delivering superior customer service.
Moreover, the integration of automated plan assignment and management features increases time efficiency by reducing the manual workload of supervisors. These systems handle routine coaching activities, freeing supervisors to focus on strategic priorities. This shift allows for a more focused and effective management approach, enhancing overall operational efficiency.
By integrating AI to the coaching and QA processes, call centers can also achieve a balanced approach that leverages the strengths of both, personalizing coaching with less resources and time, and analyzing the quality of calls in a much deeper way. This approach ensures that call centers can provide the best possible service to their customers, thanks to an ongoing coaching and improvement culture that translates to great NPS and CSAT scores.