Time to Resolution: What It Is, How to Measure and Reduce It
When your customer reaches out through an online support ticket or the help desk hotline, the clock starts ticking. Customer service teams are often overwhelmed by the sheer volume of requests and customers face a long wait for resolution, which translates into ongoing frustration and can silently erode loyalty. This is why the Time to Resolution (TTR) metric becomes critical to shaping the overall customer experience.
The stakes for customer experience have never been higher. In this article, I explain why Time to Resolution is critical, what influences it, and how businesses can optimize it through better support processes, improved workflows, and enhanced functionality. Because, when your customer is waiting, every second matters!
What Is Time to Resolution?
Time to Resolution (TTR) is the amount of time it takes for a customer support team to fully resolve a customer issue, starting from the minute a support ticket is raised to the time it is tagged as resolved.
Unlike First Response Time (FRT), which only measures how quickly a customer gets an acknowledgement, TTR is all about complete issue resolution. It also differs from Average Handle Time (AHT), which tracks the actual amount of time an agent spends actively working on the ticket, excluding waiting time, follow-ups or delays. TTR captures the entire customer journey within the support experience—from frustration to resolution—offering a more holistic view of your team’s performance.
For example, if a customer calls the help desk hotline number or raises a support ticket on Wednesday at 9 AM, and it gets resolved on Friday at 9 AM, the TTR is 48 hours, even if the actual handling time was only two hours, and the first response was sent within 10 minutes.
TTR draws attention towards resolution, and not just responsiveness because customers are concerned about when their issue is resolved rather than when it was acknowledged. From a customer’s point of view, a swift "We have received your request" means little if it takes days to actually solve the issue.
TTR is more than just a metric. It is a window into how well your brand listens, responds, and resolves real problems in real time.
Why Time to Resolution Matters
Time to Resolution (TTR) has a tri-fold impact—on your customers, business performance, and your employees. It is more than a metric, it is a signal of how well your support function is working, and how aligned it is with customer expectations.
- TTR affects customer satisfaction and loyalty
When customers experience long wait times, and unresolved issues, their frustration builds quickly. According to a HubSpot study, 90% of customers consider getting a quick response essential when they reach for support, and over half expect that response within 10 minutes.
Forrester research further shows that 77% of customers feel the most important thing a brand can do is respect their time, especially during online interactions. These statistics reinforce the urgency brands must feel, not just to respond quickly but to resolve problems in a timely, and satisfying manner. A high TTR communicates the opposite—it tells customers their time isn’t valued, which directly affects CSAT, and increases churn risk.
- TTR reflects broader business performance
A persistently high TTR signals inefficiencies across your support workflows, ticketing systems, and resolution processes. It impacts key operational metrics, from forecasting and staffing to queue management and customer journey mapping. Brands that consistently resolve issues faster often see higher NPS and better retention outcomes.
- TTR influences employee morale and agent performance
A backlog of unresolved tickets or long resolution times can overwhelm agents, and lead to burnout. Overloaded agents dealing with complex, unresolved issues can quickly lose motivation, resulting in high employee turnover, and increased training costs. Over time, this creates a cycle of reactive rather than proactive support, further worsening the customer experience.
Factors That Affect Time to Resolution
This metric does not always directly depend on the time taken by the support agents to resolve the problem. TTR is influenced by a wide range of operational and contextual factors, not all of which are directly within control of the support agents. Some vary across industries, teams, and customer support models. That said, here are some factors to consider when benchmarking or evaluating your TTR:
- The complexity of the customer issue or request
- The channel through which the customer initiates contact (phone, email, chat, social media etc.)
- The availability of support agents during peak hours
- Whether your customer support team operates during fixed business hours or offers 24x7 support
- The presence of real-time routing and notification systems
- The role of internal tools, help desk platforms, and automation in ticket management
- Escalation paths and structure of internal hand-offs
- Language or localization needs that impact ticket handling
- Integration of customer support data with CRM systems and other tech stack components
- The quality and accessibility of self-service resources like FAQs or knowledge bases.
How to Calculate Time to Resolution
TTR = Total resolution time for all tickets / Total number of tickets
Most CX platforms allow you to segment your TTR by time period, support team, channel, ticket types, or customer segment. These filters can help you identify trends, compare performance across teams, and uncover inefficiencies tied to specific workflows or escalation paths.
There is no single benchmark that defines what a good TTR looks like. It varies significantly depending on your industry, the complexity of the issue, and overall customer expectations.
What is a “Good” Time to Resolution?
A “good” Time to Resolution (TTR) does not have a universal standard—it depends on multiple factors including the industry you are operating in, the complexity of the issue to be resolved, and evolving customer expectations. What feels fast and efficient in one context could feel unacceptably slow in another.
For example, customers submitting a request to an e-commerce brand may expect their issue to be resolved within an hour, while a B2B SaaS customer with a technical query may tolerate a longer wait, as long as the resolution is thorough and well-communicated.
Here are some general industry averages to help contextualize what a “good” TTR might look like:
| Industry | Average TTR |
| SaaS / Tech Support | 6 - 12 hours |
| Retail / e-commerce | 1 - 3 hours |
| Telecom and Utilities | 24 - 48 hours |
| Financial Services | 8 - 24 hours |
| Travel and Hospitality | 4 - 8 hours |
Keep in mind, these are ballpark ranges. The “right” TTR is the one that consistently meets or exceeds your customers’ expectations.
Benchmarking against industry averages can provide direction, but ultimately it is the customer perception that defines the acceptance time frame for issue resolution. Some brands also analyze TTR by persona so they ensure that VIP customers or enterprise clients receive faster resolutions.
Pro Tip: Regularly reviewing CSAT scores in relation to TTR can help you fine-tune benchmarks for your brand over time. If customers are satisfied despite TTR being slightly longer, it may indicate that communication and clarity matters more than pure speed.
Common Causes of a High TTR
High Time to Resolution (TTR) often stems from operational inefficiencies, poor communication, or unclear ownership. Below are common causes of elevated TTR, and how support teams can proactively address them:
| Cause | How to Address It |
| Complex ticket submission process | Streamline forms, add smart routing, and use chatbots to guide customers. |
| Tickets routed through slow or low-priority channels | Set channel-based SLAs and encourage real-time options for urgent issues. |
| No real-time notifications for high-priority tickets | Set automated alerts for urgent tickets across team communication channels. |
| Inadequate training for support agents | Run ongoing product and customer support training. Maintain a searchable knowledge base. |
| Unclear escalation paths or ticket ownership | Define SOPs and ownership at each resolution stage, use internal playbooks. |
| Inefficient internal tools or fragmented tech stack | Consolidate tools and integrate platforms for better workflow and unified view of customer data. |
| Lack of prioritization logic in ticket queues | Automate tagging and prioritization rules for different issue types. |
| Breakdowns in cross-functional communication | Promote team visibility and collaboration across CX, product, and engineering. |
| Language or localization barriers | Enable multilingual support and smart translations for global customers. |
Benefits Of Measuring Time To Resolution
By monitoring average Time to Resolution along with other factors like CSAT and First Response Time (FRT), brands gain a comprehensive view of their customer interaction health. Beyond surface-level responsiveness, measuring TTR provides insight into the entire lifecycle of customer issues—where delays occur, teams that are impacted, and how workflows affect resolution speed.
By mapping TTR across various touchpoints in the customer journey, CX leaders can uncover key inefficiencies and prioritize areas for improvement. Here are some ways in which measuring TTR is useful:
Helps streamline resource planning
Tracking TTR trends by channel, time of day, or ticket type helps support managers to better forecast staffing needs and workforce management. If certain types of requests consistently take longer to resolve, leaders can redistribute workloads, adjust shift schedules, or assign more experienced agents to high-impact queues.
Improves team performance visibility
TTR metrics can spotlight underperforming workflows or teams. When analyzed alongside agent-level data, TTR reveals whether bottlenecks stem from individual capabilities, team collaboration, or broader systemic issues. This helps teams diagnose the root of delays and adapt coaching strategies accordingly.
Supports training and onboarding programs
Historical TTR data can serve as a powerful training tool. By showing new hires real-world resolution timelines, managers can set realistic expectations and performance benchmarks. If certain teams or issue types have longer TTRs, targeted training can help close those gaps early in the onboarding process. Over the long-term, this ensures the employee expectations are met, which translates into greater satisfaction and retention.
Uncovers product or process issues
Recurring delays in resolving similar types of tickets often point to deeper issues, like bugs, poor documentation or unclear policies. Measuring TTR at the category level can help product or engineering teams identify and prioritize fixes that will have the greatest impact on support efficiency.
Informs continuous improvement initiatives
TTR is a leading indicator of how well your internal processes are functioning. It surfaces friction points that can be optimized, like redundant approval loops or tool-switching overhead. Even small improvements to average TTR can compound into higher customer satisfaction, and better retention over time.
Limitations of the Time to Resolution Metric
While TTR is a valuable performance indicator, it does have limitations, and should not be used as a standalone metric. Relying solely on TTR can lead to misleading conclusions about service quality or team performance.
1. Outliers can skew the data
A handful of unusually long tickets, such as those that remain open due to delayed customer responses or rare technical escalations, can distort the average TTR. This makes it harder to identify realistic benchmarks or compare teams fairly unless the data is properly segmented or normalized.
2. TTR doesn’t reflect issue complexity or severity
Not all tickets are created equal. A password reset should not be measured against a multi-system technical bug. TTR doesn’t account for the depth of investigation required, which means complex issues can unfairly make teams look slow even when they are delivering quality service.
3. Speed can compromise quality
Optimizing for TTR alone can lead to hasty resolutions that fail to address the root cause of the problem. Quick fixes may resolve the immediate symptom but create repeat issues that ultimately hurt customer satisfaction, and retention.
4. It misses emotional and contextual factors
TTR measures time, not tone. A longer interaction that includes empathy, reassurance, or education may result in a much more satisfied customer than a quick, transactional resolution. Metrics like CSAT or customer feedback are needed to fill this gap.
5. It does not tell you why delays are happening
TTR tells you that resolution was slow but it does not tell you why. The delays could stem from internal hand-offs, lack of tools, low agent confidence, or external blockers. This requires deeper analysis to interpret the metric meaningfully and take corrective actions.
Common Myths About TTR
- Faster is always better: While speed is important, prioritizing quick resolutions at the expense of quality can lead to poor customer outcomes and repeat tickets.
- One size fits all: Every customer segment has different needs. A good TTR for an enterprise client handling complex issues won’t look the same as that for a B2C e-commerce shopper.
- It is the frontline’s fault: TTR is not just about the agent. Delays often stem from inefficient tools, unclear escalation processes, or lack of cross-functional coordination.
- Once resolved, it is done and dusted: A ‘resolved’ ticket may be misleading if the customer comes back with the same issue. Repeat tickets indicate that the root problem was not addressed accurately, even though the TTR looks good.
- TTR is just an operational metric: In reality, it also affects brand reliability. Customers equate fast and effective support with professionalism, competence, and care.
- TTR is fixed and static: TTR should evolve based on changing customer expectations, product complexity, and support channel strategies. It can, and should be, continuously optimized based on wins and failures.
How to Reduce Time to Resolution
Reducing TTR requires a combination of the right tools, clear internal workflows, empowered agents, and continuous process involvement. Below is a tactical checklist for CX leaders looking to streamline support processes, and improve resolution efficiency.
-
Define ownership and escalation paths
Ensure every ticket has a clearly assigned owner, and an established path for escalation to avoid confusion and delay. -
Automate ticket routing and classification
Use AI-powered help desk tools to tag and route tickets based on category, urgency or customer segment. -
Offer robust self-service options
Empower customers with a knowledge base, FAQ section, blog tutorials, and AI chatbots to resolve common issues independently. -
Deliver continuous training and enablement
Provide quarterly refreshers and product knowledge updates to help support agents troubleshoot more efficiently. -
Establish priority-based SLAs
Set clear service level agreements based on issue severity and customer type to manage internal expectations and reduce backlog. -
Enable real-time collaboration across departments
Use integrations with messaging tools like Microsoft Teams or Slack to instantly loop in cross-functional team members for complex issue resolution. -
Conduct weekly resolution reviews
Have team leads review long-resolution tickets to identify patterns and remove process-level blockers. -
Share performance dashboards across the organisation
Make TTR metrics visible to other departments (product or engineering) to encourage shared ownership and faster support workflows.
Here are some real-world case studies that demonstrate effective strategies for reducing Time to Resolution (TTR):
Case Study: 86% reduction in TTR for Hoag Health with Zendesk
Hoag Health's HR department transitioned from Microsoft Outlook-based processes to Zendesk Suite, resulting in an 86% decrease in ticket resolution times. This change also led to a 13% increase in their Customer Satisfaction Score (CSAT). The implementation provided enhanced visibility, automation, self-service tools, and data insights, transforming HR into a vital business partner.
Case Study: Nomad’s 70% reduction in TTR with Gorgias
Nomad implemented automation with Gorgias, leading to a significant decrease in both first-response, and resolution times. The integration with Shopify streamlined the user dashboard, enabling more effective customer communication, and feedback tracking.
Other Important Customer Service Metrics
While Time to Resolution is a critical performance indicator, it’s most powerful when paired with other customer service metrics that offer complementary insights.
Companies should also track metrics like Customer Satisfaction Score (CSAT), Net Promoter Score (NPS), First Response Time (FRT), Customer Effort Score (CES), and Ticket Volume trends to build a more complete view of their support effectiveness and transform customer experience. Some KPIs are specific to the type of customer service operation your team is running. For instance, call center performance metrics include Average Handle Time, First Call Resolution, and Call Abandonment Rate.
What’s Next?
Time to Resolution (TTR) is not just a performance metric—it is a proxy for your brand’s value, reliability, and respect for customer time. If you want to transform the overall customer experience and win big on customer trust and loyalty, improving how the support team manages TTR is one of the fastest and most impactful steps your brand can take. One of the simplest ways to do that is to adopt the right customer service software.
As customer expectations evolve in real time, the way we measure success must evolve too, and TTR should be at the centre of that transformation.
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