KPIs can be a blessing and a curse. 

Customer support is–in comparison to many other industries–extremely easy to measure. KPIs provide crucial insights into the customer experience and can provide a lot of direction for you.

That said, an overly rigid focus on individual metrics can lead teams to chase numbers at the expense of genuine customer success. The best way to avoid that is by taking a holistic approach. Understanding how these metrics work together is essential in crafting a data-driven strategy. 

The good news is that Zendesk provides a wealth of reports that make it easy to track all the data you need. It also offers a ton of features that you can tweak to implement strategies that balance productivity with customer satisfaction.

Here’s how. 

Key customer support KPIs and how they influence each other

The most widely used support KPIs include:

  • First Response Time (FRT): The time it takes for an agent to respond to a customer's inquiry for the first time. A faster response should correlate with higher CSAT and a low resolution time. 
  • First Contact Resolution Rate (FCR): The percentage of tickets resolved in the first interaction without the need for follow-ups. FCR should also lead to low resolution times and higher CSAT–and ideally a lower first response time in the long-run as well, since fewer tickets require a second response. 
  • Customer Satisfaction (CSAT): The percentage of customers who are satisfied with the support they receive, typically based on post-interaction surveys. This can sometimes be measured in a scale as well. 
  • Contact Rate: The percentage of customers submitting support tickets. An increasing number of knowledge base views or interactions with an AI solution should result in a lower contact rate. 
  • Ratio of Knowledge Base Views vs. Tickets submitted: A measure of how often customers turn to the self-service knowledge base compared to submitting tickets. Ideally, if the number of knowledge base views increases in relation to tickets submitted, it should also come with good helpfulness ratings on the articles. 
  • Deflection Rate: The percentage of contacts that are resolved using self-service options (such as a chatbot or knowledge base), without a ticket being submitted. This works best when combined with another qualitative metric like CSAT or a Customer Effort Score.

Each metric provides only part of the picture. 

Aiming for a fast response time should mean that customers are more satisfied because they’re getting their answers solved faster. But it could also mean that customers are getting low quality answers. 

A low contact rate should mean that customers are managing to solve their questions before they reach out, but it could also mean that customers are struggling to find contact options. Even CSAT, which might feel like a good catch-all metric, can suffer from low response rates and fluctuate. 

Considering how these metrics interact will help you make informed decisions that genuinely improve agent productivity and the customer experience, rather than chasing numbers for their own sake. 

Five proven strategies for maximizing productivity in Zendesk 

Zendesk is a powerful help desk with a range of features for maximizing productivity. 

These features vary in complexity. Some are simple and quick to implement, like triggers and automations. Others require more experience and knowledge, like creating custom-built dashboards in Zendesk Explore. 

Zendesk also has more than 1600 apps and integrations available that offer extra features beyond what Zendesk can do natively. Using Geckoboard, for example, you can create custom KPI dashboards, which are much better at surfacing real-time metrics to your team – so you can create faster feedback loops between your agents and their KPIs.

Because Zendesk is a flexible tool, there will be multiple ways to implement each of the following strategies. Treat these as inspiration and adapt them based on your setup. 

Optimizing ticket routing

Ticket routing is often the foundation of the entire Zendesk setup. Most teams start by creating a few basic triggers and automations that categorize incoming tickets and assign them to the correct people.

That often leads to inefficiencies as you scale. As these triggers grow organically every time there’s a need, it’s easy to have triggers overwriting each other or for the team to develop ingrained habits manually assigning and reassigning tickets when these actions should be automated.

Zendesk has a few key features for ticket routing:

  • Skills-based routing is the most impactful, allowing you to match tickets with agents based on their specific expertise, language abilities, or product knowledge. These involve defining and assigning skills to specific agents and combining these with triggers that identify those tickets.
  • Triggers and automations are slightly different features but can be used similarly. They enable you to create rules based on ticket properties like priority, channel, customer segment, or custom fields.

The best metrics that would indicate if there are opportunities here are:

  • The escalate or reassignment rate looks at the percentage of tickets that have to get reassigned.
  • First assignment time will display how long tickets spend in the queue before getting assigned. You can also see if there’s a large gap between first assignment time and first reply time. 
  • Full resolution time, broken down by agent group. It’s normal for higher tiers to have a longer time here but if it’s unreasonably long, improving ticket routing should help.

Adjusting coverage to meet SLAs

SLAs are a great tool for maximizing productivity in general. Psychologically, the design of having a countdown attached to a ticket that turns red when the SLA is breached is very effective for most teams. 

And adjusting coverage to meet SLAs is quite obvious. The difficulty is in implementing it in practice, especially in response to unexpected surges in volume.

Zendesk has a ton of time-based reports for volume and SLA breaches, so it’s easy to identify recurring patterns–if 80% of SLA breaches happen at 3pm on Wednesdays and if peak volume comes in at 2pm on Fridays, these reports will show that.

One additional solution is to use volume metrics and tagging data to identify how large the impact of an unexpected event is. 

For example, say you experience a high-impact bug. How many more tickets did you receive in that hour or those days than you would usually expect? And how often do these high-impact bugs impact your team? 

That data should give you an idea of how much buffer or extra capacity you need to bridge those times. Doing this type of planning in advance is effective at enabling your team to consistently meet SLAs.

Improving macros based on analytics

Macros are powerful efficiency tools, but their real value emerges when you refine them based on usage analytics. 

Zendesk has a few features that are great for macros:

  • It automatically suggests macros for agents, which should increase how often a macro is used and improve its adoption rate. 
  • Macro suggestions for admins help admins create macros and suggest relevant actions. This is part of the Zendesk Advanced AI add-on.

That said, it doesn’t offer detailed reports on macro performance. You have build your own reports to dig into which macros are most effective and which need improvement by cross-referencing macro usage with resolution times and CSAT. 

If a frequently used macro correlates with lower satisfaction scores or higher reopen rates, it might need to be revised. Macros with high success rates but low usage might need better visibility or agent training.

There are tons of apps that offer better analytics like Macros Reporting or that help you optimize macro usage. For example, Zendesk’s native feature only allows you to search for a macro based on the title. Swifteq’s Macro Search app lets you search through the content as well. 

Digging into response times

Each of the strategies above should already improve response times, but sometimes taking a more targeted approach can also help.

Zendesk's analytics tools can break down ticket handling time into specific components: first response time, time between agent responses, time spent waiting for customer replies, and total resolution time. You can also measure average handling time, although that requires installing the Time Tracking app.

This granular view helps identify exactly where bottlenecks are in your support process:

  • If the delay is caused by a high agent wait time, you can try to reduce the need for follow-up questions by improving your contact form or asking more clarifying questions upfront. 
  • A high time between agent responses suggests that agents are juggling too many tickets simultaneously or that there are inefficiencies in ticket routing.
  • Tickets with a high first response could benefit from automation or better macros. 
  • To improve full resolution time, look at the ticket types that are consistently taking longer to resolve. You can develop specialized workflows or provide targeted training for agents handling those issues.

Implement knowledge-centered service (KCS)

The KCS methodology is a proven and structured framework for making every member of your team responsible for creating, using, and updating your knowledge base and documentation.

That might not seem like a way to improve your agents’ productivity. If they’re each spending time updating your knowledge base, isn’t that actually going to slow them down?

It might, for a short period. But the broader long-term impact of implementing knowledge-centered service is that it makes your entire team — from new hires to experienced agents — vastly more productive.

When you have a knowledge base that’s comprehensive, up-to-date, and constantly being refined, every agent on your team is able to help customers faster (and you’ll probably see your self-service improve, too!). 

Swifteq has written a detailed guide to implementing KCS within Zendesk, but the core methodology relies on four principles:

  1. Abundance - get every member of your team involved in creating and maintaining knowledge.
  2. Create value - capturing knowledge (which you can use later) is a valuable part of a customer interaction
  3. Demand driven - create knowledge as a response to demand (e.g. a customer’s question), rather than trying to anticipate issues or questions that customers may not even have.
  4. Trust - trust your team to create accurate knowledge, build a trustworthy knowledge base, and trust your team to use it well.

Implementing the KCS framework can take some time, but it leads to massive gains in productivity across your whole organization. 

Refine your Zendesk workflows over time

Maximizing productivity isn’t about working harder but working smarter.

Zendesk is releasing new features constantly and might have features that have existed for a long time that you’ve never looked at. Reassessing your setup once or twice a year is a great way to ensure that you’re constantly improving your workflows and equipping your team with the right tools they need. 

Agent productivity and customer satisfaction aren't opposing goals–they're complementary ones. 

When agents have the right tools, efficient workflows, and clear priorities, they can focus on what matters most: solving problems and building long-term relationships with your customers.