Category: Customer Support
Last updated on Jan 2, 2023
When it comes to measuring your businesses’ SAAS customer support metrics, you need to take a data-driven approach. To identify how your team members are performing, what good actually looks like, and how it is impacting your business, it’s critical you have a strategy to consistently monitor and evaluate the data points that have a genuine influence.
Your support teams are your support capabilities. They’re on the front line every day, engaging with your customers and delivering satisfaction at every opportunity. But just how well do they do it? What could they improve? Where do they excel?
These are all good questions, and unless you have the right SAAS Customer Support Metrics in place, it’s likely you won’t be able to answer them.
Understanding how they’re performing is an essential capability and helps with decision making throughout the support function.
In most support infrastructures, a single support team will be overseen by a support team leader. This individual will look at the both individual and team metrics and work to improve them wherever possible. In this management structure, it’s critical the team leader has access to the right information to effectively evaluate team performance and improve the quality of support delivered on a day-to-day basis.
Most businesses benefit from a data-driven approach to customer service management. They monitor, evaluate and iterate to ensure each element of customer service is delivered to a high quality and that changes are made where needed to maintain the quality customers expect. Customer satisfaction is key to successful SAAS customer support and so it’s essential the right metrics are in place to ensure evaluations are done in the right way and to deliver above and beyond expectations.
Here we take a look at the team metrics that make a genuine difference and how they help you evaluate your support performance. With these in place, you’ll be able to identify your support strengths and weaknesses and take steps to unlock the full potential of your support function.
The average query handling time across a team
The average amount of time it takes for a team to handle a query will depend on multiple factors. In most instances, a team’s average handling time will often reflect the complexity and depth of the average query and this makes it very difficult to measure and identify what good looks like. However, if you have several teams working with the same customer base, comparing their stats is viable and will provide high-quality data, helping you to effectively measure their relative performance and set valuable goals.
Most teams are set a target handle time based on their own set of variables and this encourages them to find the most efficient way to deliver high-quality customer service, without sacrificing customer satisfaction. However, the times set must justifiable to ensure they maintain accountability within the business.
The average amount of time it takes to respond to a customer support enquiry
Average response time is a good indicator of how well a support team is performing and is often indicative of whether they deliver a high-quality customer support experience. Customers left waiting long will often consider their support experience sub-par and may take action that impacts your bottom line.
In most instances, where the average response time is high, the support team are either too busy due to the volume of calls, wrongly prioritizing other activities or lack the resources/capabilities to quickly and effectively resolve the calls that do come in. If the response time is low then customers are receiving a high-quality of customer service and are likely to be satisfied, as they’re getting the attention they need, when they need it most.
The longest a customer has had to wait on hold before talking to a support operative
Understanding the longest wait time for your customers is key to effectively evaluating your performance and helps you understand how well your team operates in peak periods. In addition, it may also offer perspective on the resources your team has available and whether greater numbers are required to meet customer support demand.
Most support teams are set a target for highest wait-time that must not be exceeded. This is to ensure an acceptable quality of service is delivered. Many institutions are embracing alternative solutions to prevent customers waiting for excessive periods, such as call-backs or messaging systems. As such, this metric is becoming less important as it’s having less impact on the quality of service delivered.
The amount of time support teams are online (%)
Your support teams are often busy and so they’re not always online to handle support activities, although it should be one of their primary concerns. As such, it’s important you monitor how much time they’re active, to ensure enough is being committed to delivering a high quality of service.
If team utilization is low, it may mean support activities are being misprioritized, or alternatively, there may in fact be too much resource for the support demands. Whatever the case, team utilization is a good indicator of efficiency within your support teams.
The average performance score based on external customers surveys
This figure evaluates how satisfied customers are with the support provided after the call is finished. The score will often reflect the capabilities, attitude, resources and quality of the team in question.
A good average score suggests the team is happy and has everything they need to deliver a desirable quality of customer service. A low average score on the other hand suggests there are issues or challenges that must be addressed.
Asking customers to evaluate teams is the best way to recognize good/bad performance. Averaged out over multiple calls, this is often one of the strongest and most reliable indicators of high/low-quality customer service offerings. In some instances, it may even be worth incentivizing your customers to answer this question, as the more data you can collect, the better and more valuable the insight will be.
When it comes to the customer support metrics that matter to management, it’s only the very top-level data that really makes a difference. After all, they’re looking for results and just want a vague picture to understand the costs/benefits of ongoing support activity on a weekly/monthly basis.
With all this in mind, here are the metrics that really matter to management:
The total number of engagements for the current month
The number of customer engagements helps management understand the current demand for support. This is important as it can be acted on immediately if necessary. For example, in the event, the figures are low, there may be a significant amount of downtime in the support team, and that presents an opportunity to use that resource for support optimization tasks. If the number is high, then management can make a reactive decision to determine if the temporary resource is required, ensuring quality standards remain consistently high.
The total number of monthly engagements for the current financial year, broken down by month.
Understanding the number of customer engagements in a year so far, broken down on a monthly basis, helps management to identify trends and recognize the demand for customer support. In the event requests are signed up, this will encourage management to investigate further to understand the reasons behind the rise. In addition, this will also help identify if any regular catalysts are causing a rise in requests, and may encourage actions to pre-empt such rises in the future, like new support collateral, tackling the common issue.
The average speed to answer for the current financial year, broken down month by month.
The average speed to answer over a yearly period is a good indicator of how well support teams are handling the volume of calls on a daily basis. In addition, it’s also useful to identify patterns and the causes of regular anomalies, for example, if there are periods when support teams are busy, how does this impact speed to answer?
When this number is combined with the number of customer engagements throughout the year, it becomes easy to identify trends and see how demand impacts answering speed. If it makes a significant difference, then management will want to know and may consider contingency options for future scenarios to ensure the quality of support delivered remains consistent and up to standard. It’s insights like this that make the longer-term data points critical to strategic decision-making at the management level.
The average Customer Satisfaction Score for the current financial year, broken down month by month.
The customer satisfaction score over an extended period of time is critical to effectively evaluating the output of the support team. Everything from how well-trained or resourced the team is will influence this figure, as such it’s not a great indicator for granular analysis. However, this will be a priority metric for most management teams as it’s the culmination of their support strategy and decisions.
A consistently high customer satisfaction score over an extended period of time indicates the strategy team has everything they need to meet and exceed customer expectations. This is critical as customer satisfaction plays a significant role in customer retention, and ultimately this will influence the bottom line.
The average handle time for the team in the current financial year, is broken down month by month.
The amount of time it takes to solve the average query over an extended period of time is a good indicator of the types of the query being asked and a good reflection of the support team’s ability to satisfy customer needs. If the average query answer time is very short, it may mean there are a few key pieces of information that are missing in the public domain, which are leading people to contact regarding simple easy-to-fix issues. This can be rectified quickly with a small investment in new content tackling the issue and could reduce call volumes significantly.
Alternatively, if average call times are long, then it may suggest the teams don’t have easy access to the information they need quickly, they’re not trained well enough or the nature of the standard call is highly technical. Whatever the case, handling time is a good indicator of performance and should be recognized as such.
The total cost of the support function, is divided by the number of customer engagements.
This metric correlates financial expense with delivery and quality of output, helping management to identify the relative value of support activity. In the event, costs are high, it may be an indicator the company is overspending, and depending on wider business objectives/situations, this may be considered an issue. However, if metrics like customer retention and lifetime customer value are being prioritized on a business-wide scale, then high spend in the support function can be considered justifiable, providing the customer satisfaction delivered is also high.
This figure is critical to support decision-making as it’s the strongest indicator of whether a business’s support function is delivering more to the business than it takes.
Beyond these key metrics, management may also want to see client-specific data, particularly if certain organizations have been flagged as resource-heavy and incur losses. In some circumstances, it may be valuable for management to understand which clients are requiring significant support so an alternative solution can be found. Alternatively, this may also flag up gaps in the company support offering, if one company, operating a certain way, is struggling and requiring regular support, then chances are, they cannot find the information they need on their own. This helps educate future decision-making and resource allocation.
This type of information gives management an idea of how the customer support function is being used and what companies are needing it the most.
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With the right information on-hand, your team will be able to effectively monitor, evaluate and improve their support team’s performance and take action to enhance efficiency and the quality of the support delivered. Metrics not only help them to see strengths and weaknesses but also enhance visibility on opportunities to improve, effectively informing the decision-making process.
It also, help compare performance across the business. If there are multiple support teams involved, all serving the same customer base, then these metrics will help determine what good looks like at a team level, and management level and how it can be achieved. This ability to compare is essential to setting the baselines that will play a large role in scoping and setting further objectives for your business.