First Contact Resolution

What Is First Contact Resolution (FCR)?

First contact resolution (FCR) is a customer service metric that measures the percentage of support inquiries resolved during the customer's first interaction, without requiring a follow-up, transfer, or callback. Also called first call resolution in phone-based environments, FCR is widely considered one of the most important indicators of support quality because it directly reflects whether customers get their issues fixed the first time they reach out.

The standard formula for FCR is:

FCR = (Number of issues resolved on first contact / Total number of issues) x 100

For example, if your team handles 1,000 support interactions in a week and 780 are resolved without any follow-up, your FCR rate is 78%.

How First Contact Resolution Is Measured

Organizations measure FCR using several methods, and the approach matters because it affects the number you get. The most common methods include: customer surveys that ask "Was your issue resolved?" after the interaction, repeat contact tracking that flags any ticket reopened or followed up within a defined window (typically 24 to 72 hours), and agent-confirmed resolution where the agent marks the ticket as resolved on first contact.

Each method has tradeoffs. Surveys capture the customer's perception but suffer from low response rates. Repeat contact tracking is more objective but can miss cases where customers give up rather than call back. Agent confirmation is fast but may overcount resolutions if agents close tickets prematurely. Best practice is to combine at least two methods for a more accurate picture.

Why First Contact Resolution Matters

FCR is a leading indicator of customer satisfaction, operational efficiency, and support cost. Research consistently shows that every percentage point improvement in FCR correlates with measurable gains in customer satisfaction and reductions in operating cost. When customers have to contact support multiple times for the same issue, satisfaction drops sharply, cost per ticket rises, and ticket volume inflates.

Industry benchmark: According to SQM Group's 2024 industry analysis, a "good" FCR rate falls between 70% and 79%, while world-class contact centers target 80% or higher. FCR varies by industry, with billing and order inquiries typically scoring higher than complex technical support.

FCR also impacts agent morale. Agents who resolve issues on the first try report higher job satisfaction than those who frequently handle repeat contacts and frustrated customers. For enterprises, improving FCR is one of the highest-ROI investments in the support organization.

FCR Benchmarks by Industry

FCR benchmarks vary significantly by sector and issue complexity. General industry guidance for 2025 suggests these targets:

Retail and e-commerce: 75% to 85%, driven by straightforward order and return inquiries. Financial services: 65% to 78%, reflecting more complex account and compliance issues. Technology and SaaS: 65% to 75%, where technical troubleshooting often requires deeper investigation. Healthcare: 60% to 72%, due to regulatory complexity and multi-step processes. Telecommunications: 60% to 70%, reflecting high call volumes and technical infrastructure issues.

Organizations using AI customer service platforms consistently report FCR rates above these baselines. The key factor is whether the AI can access enough context and knowledge to resolve the issue completely, not just provide a partial answer that generates a follow-up contact.

The Maven Advantage: FCR Rates That Set the Standard

Maven AGI was built to maximize first contact resolution. Every component of the platform, from the AI Agent to the knowledge base to the AI Copilot, is designed to give the AI (or the human agent) everything needed to resolve the issue on the first interaction. Maven's RAG-powered retrieval ensures responses draw from the most current, accurate company data, while 100+ integrations provide real-time access to CRM records, order systems, and internal documentation.

Maven proof point: Mastermind achieved a 93% live chat resolution rate. Enumerate reached 91%. K1x hit 80% resolution, a 10x improvement over their prior AI, all deployed within weeks. These are not deflection numbers. They represent issues fully resolved on first contact.

The difference is Maven's resolve-first architecture. Where legacy tools deflect customers to self-service portals and call it "handled," Maven's AI Agents pull from verified data, take actions in connected systems, and confirm resolution before closing the interaction. For more on FCR methodology and benchmarks, see Forrester's customer service research or Gartner's guidance on AI-driven customer service.

Frequently Asked Questions

What is a good first contact resolution rate?

Industry benchmarks place a "good" FCR rate at 70% to 79%, with world-class organizations targeting 80% or higher. However, these benchmarks assume traditional support models. AI-powered platforms like Maven AGI regularly achieve resolution rates of 80% to 93%, resetting expectations for what "good" looks like in the age of AI Agents.

How does AI improve first contact resolution?

AI improves FCR by providing instant access to relevant knowledge, understanding customer intent through NLP, pulling data from connected systems in real time, and resolving issues autonomously when possible. For issues that reach human agents, agent assist tools surface the right information and suggest responses, reducing the need for follow-up research.

What is the difference between FCR and resolution rate?

FCR specifically measures whether issues are resolved on the first contact, meaning no follow-up, transfer, or callback is needed. Resolution rate is a broader metric that measures the percentage of issues resolved overall, regardless of how many contacts it took. Both matter, but FCR is a stronger indicator of customer experience because it reflects the customer's effort and wait time.

Does improving FCR reduce support costs?

Yes. Every issue resolved on first contact eliminates the cost of follow-up interactions, which can include additional agent time, repeat phone calls, supervisor escalations, and the administrative overhead of managing open tickets. Industry data suggests that improving FCR by even a few percentage points can produce meaningful reductions in overall support costs.

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