AI is boosting First Call Resolution (FCR) by tackling common challenges and improving efficiency, satisfaction, and agent performance. Learn how!
A strong First Call Resolution (FCR) rate is generally considered above 70%. However, despite significant efforts to improve this metric, many companies find it challenging to reach that benchmark. Complex inquiries, insufficient training, and lack of the right tools are some of the biggest obstacles. However, artificial intelligence is proving to be a game-changer as it is enhancing FCR rates while also boosting customer satisfaction, service quality, and agent productivity.
What is First Call Resolution and Why Does It Matter?
FCR stands for First Call Resolution, a key metric that measures the percentage of inquiries made by customers which are answered during the first interaction, without the need for escalation or a follow-up call.
Alongside ATH, CSAT, and NPS, FCR is one of the most important KPIs in customer service. A high FCR percentage rate reflects a smooth customer experience, optimised processes, quick access to information, and a well-trained agent workforce. On the other hand, a low FCR rate often signals inefficiencies and a lack of adequate support.
How AI Enhances First Call Resolution
Traditionally, efforts to improve FCR have mainly focused on agent training, process optimisation, and knowledge management systems. Today, artificial intelligence solutions such as AI Care Now are unlocking new tools to increase FCR rates by up to 5%.
Automating Routine Tasks
Routine tasks such as retrieving customer information, updating CRM data in real-time, or categorising and classifying tickets have traditionally been time-consuming for agents. Now, automation streamlines these processes, freeing up agents’ time, accelerating resolution times and reducing errors.
Real-Time Support for Agents
AI empowers agents with real-time recommendations during customer interactions. By analysing conversation context and customer history, AI can quickly pinpoint the root cause of an issue and suggest solutions in a natural language, delivering instant actionable support to agents.
Data Analysis and Insights
AI systems can process and analyse vast amounts of data from past interactions to uncover patterns and trends during customer inquiries. This insight enables the prediction of potential problems, optimisation of resource allocations, and ongoing improvements to resolution processes.
Key Benefits of AI-Driven FCR Solutions
- Improved Customer Satisfaction: for each percentage point increase in FCR, customer satisfaction is estimated to rise by 1%. Implementing AI has a direct, positive impact on FCR rates.
- Reduced Operational Costs: AI reduces the need for follow-up, optimising agent time. The number of tickets can be cut by as much as 78%.
- Continuous Improvement: AI continuously learns from each interaction, which helps refine responses and leads to a progressively more efficient service.
Practical Tips to Improve FCR with AI
Implementing AI solutions into customer service requires a well-designed strategy to achieve your desired results:
- Choose the right tool: look at AI solutions that integrate seamlessly with your systems, are easy to use, offer strong support, and allow customisation.
- Ensure high-quality and current data: make sure to keep databases well-structured so that AI can accurately access and process information. Data needs to be as current as possible to maximise the AI´s potential.
- Train your agents: provide comprehensive training, so agents can effectively use AI tools and maximise their potential.
- Involve your team: engage agents in the implementation process, leveraging their expertise while listening to their needs and feedback.
- Leverage customer insights: Use AI to analyse customer feedback and identify areas for improvement to refine your strategy.
Measuring and Tracking First Call Resolution with AI
Choose an AI solution that offers real-time dashboards and analytics to monitor performance efficiently. Define your most relevant KIPs, set SMART objectives, track progress, and continuously refine your strategy.
Metrics like average resolution time, transfer rate, resolution success rate, and customer satisfaction, combined with agent feedback, provide valuable insights into AI’s impact on FCR. You can also run pilot tests that can help you compare and validate results before scaling further.
