It should go without saying, but SAAS Customer Support Metrics play a key role across multiple tiers of your business. The very best use data in every business unit to monitor performance, optimize efficiency and make good commercial decisions – and the area of customer support in a SAAS business is no exception.
Most SAAS Customer Support functions are regularly evaluated at this top level using a few key metrics, this helps decision makers understand what customer support is contributing, what it’s costing and how it can be improved.
In fact, 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 is 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 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 recognise the demand for customer support. In the event requests are significantly 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 in regular anomalies, for example if there are periods where 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 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 makes the longer term data points critical to strategic decision making at 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, 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 query being asked and a good reflection on 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, that are leading people to contact regarding simple easy-to-fix issues. This can be rectified quickly with 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, handle time is a good indicator for performance and should be recognized as such.
The total cost of the support function, 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 prioritised 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 for 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 on how the customer support function is being used and what companies are needing it the most.
Sign up for your 14-day free trial with Document360 nowGet Started
- Number of customer engagements
- Number of customer engagements, year to date
- Customer satisfaction score, year to date
- Average speed to answer, year to date
- Average call handle time per team, year to date
- Cost of chat services delivered, year to date
As you can see, the SAAS customer support metrics that management really care about are largely designed to inform on wider trends within the Customer Support function in the business. They want to see information covering a wider period of time to identify long-term concerns and opportunities.
With this in mind, it’s worth remembering the role of data in SAAS Customer Support, it’s critical management have an appreciation for these figures, and what they mean to maintain a healthy and effective customer support offering. Management teams who choose to ignore these figures will continue to operate in the dark, with no real idea on how effective their support teams are or the impact they’re having on the wider business.