Do you know how well your call center agents meet your and your customer’s expectations? The best way to measure a call center’s performance is with a call center quality monitoring scorecard.
This scorecard helps you objectively measure individual agent performance and aggregate results to generate an overall performance measurement for your teams. It can provide valuable insights into where the customer experience may be affected (negatively or positively) by the agent’s knowledge, communication skills, soft skills, or company guidelines.
In this article, we’ll show you how you can use scorecard questions to get to the root cause of inefficiencies in your call centers. You’ll also get the steps to create your own call center scorecards and use them as a quality assurance tool to provide a consistently positive customer experience.
Contents
- What are quality scores in a call center?
- Why call center quality monitoring scorecards are important
- How to build a call center quality scorecard
- How to calculate scorecards
- How to measure call center agent performance
- Call Center Quality Monitoring Scorecard (Template)
What are quality scores in a call center?
A call center quality monitoring scorecard measures your call center agents’ performance related to the customer experience. It can be used to identify areas of improvement for individual agents, and the team as a whole. It can also be used to understand where your team excels.
Here’s how it works:
A scorecard is created for each customer interaction. That interaction is divided into sections that are analyzed and given a numerical score (more about the specific sections below). The scores are calculated for each customer interaction, then used to generate an overall score for the agent. These scores can be analyzed over time to see if and where growth is happening or where the agent needs help, coaching, or training.
Receiving “low” scores in your call center isn’t necessarily a bad thing as long as you can recognize them in a timely manner and take steps to fix them.
👉 Learn more about how you can fix bad customer service.
Why call center quality monitoring scorecards are important
Call center scorecards are beneficial for three key groups of people:
- The individual agents: Insights from customer service scorecards provide agents with a third-party view of where they can perform better. With this information, they can work with their supervisors to get additional training or support to increase their scores, which could eventually lead to a promotion or pay raise.
- Your company: Your company can use a call center scorecard to see who needs support (and to provide it to them), identify leaders on the team, and provide insights into systems and processes that can boost your customer service quality across the organization.
- Your customers: The goal is to track these scorecard metrics over time to see continual improvement. Improvement in these scores generally correlates to happier customers who are getting what they need from contacting your customer support team.
Scorecard scores and metrics are important for trend monitoring, but more important are the insights you can pull from them.
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How to build a call center quality scorecard
Building your own call center quality monitoring scorecard is simple and can be fully customized to the business metrics you have and your goals. Here are the steps to create your call center quality monitoring scorecard:
Step 1: Set goals and objectives
Before you begin, set your goals and objectives. Look at your organization’s goals (such as to increase revenue or push upsells and cross-sells) and any goals your support team has (such as getting customers to an amicable resolution quicker).
You likely already have many metrics that you could use to measure call center agent performance, but prioritize ones directly related to these goals and objectives for more helpful insights.
Step 2: Choose your KPIs and metrics
You’ll want to gather qualitative and quantitative metrics for a well-rounded view of performance. For example, call handling time would be a quantitative metric, while emotional intelligence would be a qualitative metric. As well, gather the metrics that relate to your goals. If you have a business goal to increase upsells on support calls by 25%, gather quantitative metrics that lead to that goal. If you want to increase the number of calls your call center agents can make daily, gather metrics related to call handling time.
Some metrics you could include in your call center quality monitoring scorecard include the following:
Quantitative metrics
Customer Satisfaction scores (CSAT)
A measure of customer satisfaction regarding the conversation or interaction. Higher satisfaction scores usually mean the agent handled the call well and to the customers’ expectations.
Average Handling Time (AHT)
Length of customer service conversations. In most cases, you want to resolve the customer’s problem as quickly as possible, but be mindful that some more complex cases will require longer AHT and may skew your scores if the data is not segmented by user issue.
First Call Resolution (FCR)
When the customer query can be resolved without escalating the call to a manager or co-worker or requiring additional calls or correspondence. Your agents should have the skills to solve all customer queries without escalating or requiring follow-up.
Average speed of answer
How long it takes to answer a call or respond to a chatbox text or email message. These should always be as quick as possible, especially with “live” channels like phone calls and chat boxes.
Follow-up time
How timely agents follow up with customers after the interaction. If any follow-up is needed for resolution or quality assurance, it should be done according to your company guidelines.
Qualitative metrics
Conflict resolution skills
How well the agent deals with difficult customers. This may include an analysis of the appropriateness of the language and tone the agent uses during the conversation.
Knowledge of products and services
How well the agent can answer any question. In a perfect system, the agent receiving the customer call should know the organization’s offerings and processes in detail so they can answer any question without passing the call to another agent. Proper call tagging and assignment can ensure that any agent with specialized knowledge of a specific topic receives those queries.
Step 3: Create a (concise) scorecard
Begin drafting your scorecard and assign values to each element you’re analyzing. It’s not helpful to have a long or complicated scorecard, especially if there’s any manual (human-generated) score generation (such as rating the employee’s conflict resolution skills or attitude). Customers don’t want to answer long surveys, either. If your scorecard is wholly generated by customer feedback, your response rate (and thus consistency) of developing scorecards will be low.
Step 4: Choose supporting software and systems
Once you’ve picked your top metrics for your call center quality monitoring scorecard, choose a software or platform to help you collect and analyze the data. Many organizations start with digital survey software (like Survey Monkey, Typeform, Google Forms, or Microsoft Forms), then manually review the data.
A more effective way is to feed all metrics and data from various touchpoints into one platform like Idiomatic, which uses machine learning to help you uncover specific insights quickly and with greater accuracy than human analysis.
With Idiomatic, you can uncover the specific types of issues your agent has lower scores on, so you can get a full-picture view on what they struggle with and how you can offer better coaching to overcome them.
Step 5: Begin call center scorecards program
Once you have your scorecard done and chosen data collection and analysis systems, it’s time to begin tracking the KPIs and completing these QA scorecards for your team members.
As agent performance may vary depending on various factors (personal life, distractions, motivation, energy levels, time of day), it’s important to gather scorecards from a variety of situations before analyzing. This will help you get a better representation of their performance and not have results skewed because the call center agent was having a “bad day” when you gathered scorecard data.
Step 6: Analyze the data and act on insights
Once you have a good cross-section of data for an employee, you can begin analyzing it to look for trends. If done through human analysis, the results may not be as accurate because it’s open to human error in calculation and interpretation (and will take a long time, especially for large call centers).
Instead, this is when you can use software integrations to gather all your data in one place and then use AI to analyze it in seconds. Idiomatic can help you get human-quality insights at scale without the need to dedicate team members to time-consuming manual analysis. Its sophisticated tagging and categorization ability helps you segment call center agent metrics by any category you want, including customer issue or resolution status
When you categorize your scorecard data by issue, you can get more targeted insights into how each type of customer service interactions are being handled. This could indicate if the root cause of the low score(s) are related to agent knowledge and skills, a product defect, or a systems and technology issue.
How to calculate scorecards
With these quality assurance scorecards, you’ll gather data on individual customer conversations and use those to generate an overall score for each employee or team. Take the scores from all your scorecard metrics and calculate the average response or score for each question. This is the information you’ll discuss in performance reviews. Then you can dive into the metrics and outcomes from specific customer conversations to get performance examples.
For higher reporting to executive teams, you may be asked to provide customer service scorecard metrics for your team as a whole. This will likely be tracked over time to review your team’s overall success. After all, company executives don’t care which individual employees have low CSAT scores. They only care about the overall performance of that department.
How to measure call center agent performance
Having a call center quality monitoring scorecard for your organization is an excellent first step to increasing agent performance. However, it doesn’t provide actionable data to make changes to improve agent performance and customer satisfaction.
When you use customer satisfaction software like Idiomatic, you can understand why and what kinds of cases drive these scores. It can tell you if an agent’s low scores are because of their performance or a larger issue (and what that issue is).
With Idiomatic, you can generate a call center scorecard for each agent and each type of case. This level of detail and specificity will help you better understand what training or support the agent needs.
Request a demo of Idiomatic today to see how it can help you get the valuable, data-based insights you need to improve the performance of your call center agents.
Call Center Quality Monitoring Scorecard (Template)
Use the below scorecard for each customer call you’re analyzing. Feel free to add any other metrics (such as CSAT scores, customer feedback, speed of answer, and handling time).
Category | Metric | Point Value | Agent Score | Comments |
Case Numeric Metrics | Average Handling Time (AHT) | 5 | ||
First Call Resolution (FCR) | 5 | |||
Average speed of answer | 5 | |||
Emotional Intelligence | Conflict resolution skills | 5 | ||
Tone of voice | 5 | |||
Energy and positivity during call | 5 | |||
Professionalism | 20 | |||
Skills | Product knowledge | 20 | ||
Playbook knowledge | 10 | |||
Customer Satisfaction | Customer satisfaction score | 20 | ||
TOTAL | 100 |