Benchmarking in the Age of AI
Benchmarking provides a powerful tool to unlock valuable insights into the true performance of a call center.
For decades contact centers have engaged in benchmarking practices designed to measure their organizations against, not only global standards, but also the performance of their best agents and teams. This process enables leadership to identify areas in need of improvement and take the necessary steps to enhance overall production.
Whether aiming to optimize efficiency, customer satisfaction, or cost-effectiveness, call center benchmarking empowers businesses with the knowledge and strategies required to achieve their performance goals.
How Most Think About Call Centers Benchmarking
Most call centers measure agent performance using a wide range of key performance indicators (KPIs) with the hope to obtain a comprehensive assessment and general assessment. Traditional KPIs may include:
- Time to Proficiency: how long it takes a new agent to be customer-ready.
- Average handling time (AHT): which measures the average time it takes to service a customer.
- First call resolution (FCR): which evaluates the percentage of calls resolved on the first interaction.
- Customer satisfaction (CSAT): a vital measure of customer-agent interaction quality
- Traditionally collected through post-call surveys
- More recently, calculated using speech analytics technology
- Automatic quality management (AQM): scores interactions against a custom rubric that now often includes sentiment, language patterns, and compliance.
- Attrition rate: a measure of the percentage of the workforce that leaves the organization over a given time period.
Traditionally evaluated after the interaction concludes, advancements in computing, natural language processing, large language models, and AI now allow call centers to evaluate these KPIs in real time. Such monitoring tools allow supervisors to monitor the analytics of live calls and provide immediate feedback or intervention.
These KPIs and evaluation methods allow each constituency in the call center – the training, management, and quality teams, for example – to accurately assess agent performance during the window of time and on the dimension they are directly responsibility for.
The Problem with Silo’d Thinking
However, when you measure and optimize against a singular benchmark, without considering the journey an agent takes between them, you do your team and business an injustice. This risk is evidenced by the all-to-common story of the contact center that over-rotated on AHT and saw their CSAT tumble.
- Does your training team know how candidates are evaluated?
- Are agents benchmarked before they start onboarding (so you know where they started)?
- Do contact center supervisors know how well agents performed during training?
- Does QA monitor the same metrics as supervisors coach to?
- Can you measure the efficacy of your coaching program?
- Do you have a clear understanding of how performance benchmarks correlate to attrition?
To raise contact center performance against all its benchmarks simultaneously, to achieve proficiency quickly, to resolve issues succinctly, to see CSAT soar… we need to think wholistically. We need to discover how these benchmarks relate to each other over the entire agent lifecycle.
Evolving benchmarking in the age of AI
In the realm of agent performance measurement, AI-powered solutions offer unprecedented capabilities, enabling call centers to comprehensively benchmark the entire agent lifecycle – from candidate to top performer and beyond.
For the first time, we can benchmark and evaluate the performance of staff at each stage – candidate, trainee, junior agent, cross and reskilling, all the way to seasoned contact center ninja – allowing call centers to assess their potential success.
By utilizing AI-powered systems, such as Coach Sym, to transform conversations with customers into AI-powered dialog simulations. This allows you to evaluate every agent against the same benchmark. Let’s consider how this would look in practice.
Say you evaluate your existing agent pool on a simulation created from a real-world customer interaction. You measure them on all your dimensions including application proficiency, conversational efficiency, and confidence and tone – the known leading indicators of AHT and CSAT success.
You might find that 80% of agents typically perform at an 80% proficiency level on this test. Now what if you took this new, more wholistic benchmark evaluation and assessed candidates or trainees – or better both!
When you leverage AI-powered simulations to evaluate performance against a consistent, based on real-life, benchmark from day one, you’ll have the unique perspective to know how your agents evolve their skills over time.
Such an AI-powered benchmarking process helps:
- Identify candidates who meet the profile of successful agents
- Ensure that new hires meet or exceed 80% proficiency before they enter production
- Measure the success of your continuous learning and coaching program
Downstream effects of modern benchmarking programs
AI-powered automated role-play solutions such as SymTrain, automated role-play solutions aid in identifying teams that may require additional support or training, as well as individuals within teams who may benefit from personalized coaching in specific areas.
This is a big shift away from the build one training lesson and target a whole group strategy and is made possible because of the scale that AI-powered automation provides.
By leveraging AI-powered performance measurement, call centers can optimize their workforce, improve overall team performance, and drive continuous development of their current agents, hitting proficiency faster and almost eliminating nesting periods for new hires. This alleviates the burdens of attrition and provides a path for your team to continually improve.
Benchmarking the right way
To stay ahead in today’s highly competitive CX market, you need to hire the best and keep them performing at the top of their game. Businesses’ can no longer afford to measure their team in silos. A wholistic approach to agent performance benchmarking is the unique approach to evaluating and improving agents’ day-to-day work that you need to get ahead.
By implementing the right tools and methodologies, organizations can assess these processes in an unbiased manner, enabling a more accurate comparison of agents’ performance on the floor. Consistent use of key metrics can be evaluated through an unbiased, AI-powered benchmarking process allow you to understand an agent’s entire proficiency lifecycle.
Don’t stop measuring on multiple dimensions, stop using inconsistent tests to evaluate isolated benchmarks. Agent attrition rates, agent productivity, and customer satisfaction scores are all interrelated and can be effectively measured and enhanced through this approach to benchmarking.
Leveraging technology allows organizations like yours to identify the percentage of agents who excel in up-selling or cross-selling opportunities, providing valuable insights to drive revenue growth and foster customer loyalty.
Benchmarking in the age of AI is unbiased, automated, widespread, and what we at SymTrain believe will set the operationally effective contact centers apart from their flailing competition. But don’t take our word for it, hear from businesses already using AI-powered, automated role-play to improve their CX.