Manually monitoring agent-customer interactions for performance evaluation is like using a typewriter in the smartphone era. Remarkably, 75% of contact centres still depend on internal teams or supervisors to perform this task manually.
The primary issue here is the inadequacy of such methods in meeting their objective. According to COPC’s 2023 Global Benchmarking survey, 74% of voice call evaluations are conducted randomly, indicating that supervisors seldom select customer interactions for review based on specific incidents, such as flagged conversations or negative feedback. This lack of a systematic approach leads to misrepresentations of performance and fails to provide adequate insights for enhancing agent effectiveness. The challenge originates from the sheer volume of customer interaction data, which exceeds the human capacity for analysis. That’s where artificial intelligence (AI) can make a significant difference, excelling at processing vast datasets efficiently. Here’s what we know…
Gaps in Current Agent Evaluation Methods and their Drawbacks
Manually evaluating agent performance can have consequences ranging from staff burnout to high attrition rates. To better understand these challenges, let’s examine the shortcomings of current agent evaluation methods:
- Oversights due to Limited Monitoring: On average, contact centre supervisors monitor only a tiny fraction of customer interaction recordings, which does not adequately reflect the challenges agents and customers face. It gets difficult to spot any inadequacies in agents’ skills, training, and knowledge. Moreover, insights into broader issues, such as ineffective processes or product-related problems, can be missed.
- Performance Misrepresentation: Agents are typically monitored based on a variable quota of customer interactions, which are adjusted based on their performance and experience. However, because this quota usually represents only a fraction of total interactions, it fails to accurately gauge an agent’s overall performance unless specific conversations are flagged.
- Evaluation Bias and Inconsistencies: Humans introduce bias unconsciously or otherwise. Supervisors’ evaluations can be affected by factors like how they feel that day, whether or not they like the agent, and environmental stress. Consistency and fairness become even more challenging when multiple supervisors perform agent evaluations.
While increasing agent evaluation quotas may seem the obvious solution, this can lead to operational overload and staff burnout, exacerbating staff attrition – a significant issue in the industry. Indeed, due to the overheads involved, and in spite of great intentions, many contact centres – even if they monitor calls – never actually get around to investing the time and effort in scoring their agents.
How can all this be fixed? The answer, unsurprisingly, lies in automation. Let’s look closer.
How does AI-Powered Automated Agent Evaluation Bridge the Gaps?
Technologies like AI can be harnessed to analyse the vast customer interaction data available in contact centres for a comprehensive and accurate evaluation with multiple benefits. AI can facilitate:
- Comprehensive Monitoring across all Channels: It can analyse and score 100% of your agent engagement – every interaction across all channels, such as voice calls, email, chats, and social media, thus providing a holistic view of the agent’s performance.
- Unbiased and Objective Evaluations: AI assesses customer-agent interactions based on customizable scorecards that measure company-specific criteria and metrics, resulting in unbiased, objective evaluations.
- Outliers flagged for follow-up: AI highlights conversations that fall outside defined standards – either good or bad. Supervisors need only review these scorecards to offer positive or constructive human input as required.
- Feedback-facilitated agent coaching: The agent-customer interaction patterns can reveal specific areas of improvement for agents. Supervisors can use this information to facilitate agent coaching and development.
In summary, automating agent evaluation can provide valuable insights that highlight issues and enable more effective, informed agent coaching and training. This will in turn improve both your service levels and your staff engagement, ultimately benefiting your customers and your business.
The Case for Automation – An Essential Shift
Automating agent evaluations is not a novel approach, but it needs to be better adopted. Statistics suggest that only 15% of contact centre executives use AI-based tools to monitor the quality of agent customer interactions, although AI can be truly transformative. Let’s do some number-crunching to understand this better. A recent automated evaluation one-month trial was run with ten agents, while the remaining 105 agents were monitored manually for the same period. Here are some of the findings:
- The supervisors manually evaluating the 105 agents managed 238 assessments for the period, or roughly two interactions per agent in the one-month period.
- Meanwhile, with AI-enabled agent evaluation, 100% of interactions for the ten agents were analysed, providing a much more comprehensive view.
- The AI evaluation also revealed unexpected issues in agent interactions (70% of the agents failed to use appropriate greetings) – as well as uncovering trends in issues previously unnoticed.
Unsurprisingly, the immense potential of automated agent evaluations now has contact centre leaders asking whether they or their businesses can afford to ignore a tool that offers such benefits.
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