First Contact Resolution (FCR) is often tossed aside in the race towards embracing cutting-edge technologies. What’s more, this disregard has resulted in a decline in customer satisfaction and, hence, a missed opportunity to improve return on investment (ROI).
According to a study conducted by SQM Group, a 1% improvement in First Contact Resolution (FCR) can lead to a 1% increase in customer satisfaction. This highlights the direct correlation between FCR and customer satisfaction, emphasising the missed opportunity for businesses not prioritising FCR.
What is needed is a harmonised strategy that combines technology with human empathy, designed to boost FCR and customer satisfaction.
In this blog, we’re going to show you how using speech analytics can improve both FCR and ROI.
Why is FCR Important?
FCR is a key metric used in contact centres to show how efficiently customer issues are solved at first interaction. But how do traditional methods of measuring FCR work? They’ve been tricky, posing numerous challenges for contact centre managers such as inconsistencies, limited insights and missed chances.
Enter speech analytics. It’s a game-changer for tracking this crucial metric.
Let’s break down the old versus new. We’ll delve into the hurdles of traditional methods and contrast them with the perks of using speech analytics.
So, let’s dive in. FCR and how you can use it to improve your contact centre’s ROI is about to get a whole lot clearer.
The Traditional Way to Approach FCR
Three words to describe it: tedious, time-consuming and tiresome. The traditional approach was all about manual evaluations. Thankfully, these have been eclipsed by advanced technologies offering real-time insights and proactive strategies.
But, let’s delve into what the traditional approach was all about:
- Manual Tracking: Contact centre managers would manually track customer interactions and resolutions, relying on agents or supervisors to document whether a call was resolved on the first attempt.
- Subjective Evaluation: The evaluation of FCR was highly subjective, with agents or supervisors making judgement calls on whether a resolution was successful or not.
- Limited Data Sample: Traditional methods typically rely on a limited sample of interactions, which might not accurately represent the entirety of customer interactions.
- Reactive Analysis: Analysis was often conducted reactively after the fact. This made it difficult to address issues promptly and proactively.
These traditional methods pose several challenges to measuring FCR:
- Inconsistent Metrics: Traditional FCR measurement methods often result in inconsistent metrics due to the subjective nature of evaluations. It’s easy to see why when you consider this real-life example: In a busy airline contact centre, two agents handle similar customer complaints differently. While both mark their respective calls as successful FCRs, the quality of resolution varies significantly due to their individual/subjective interpretation of what constitutes a successful resolution. This leads to unreliable data.
- Limited Insights: Traditional methods provided only a limited view of FCR performance, offering little beyond surface-level assessments. Managers lacked comprehensive insights into the nuances of customer interactions, making it challenging to pinpoint areas for improvement. Imagine a customer reaching out to a tech support helpline due to recurring software glitches on their device. The agent resolves the specific issue reported by the customer. However, the customer might not mention their frustration with the overall user interface, assuming it’s unrelated to the current problem. In this scenario, traditional methods would consider this a successful resolution because the immediate problem was fixed during the first contact. However, without deeper insights, the support team might miss the customer’s broader dissatisfaction with the software’s usability.
- Missed Opportunities: The limitations of traditional FCR measurement meant that valuable opportunities for process improvement and enhanced customer experiences were frequently overlooked. Managers struggled to identify patterns and trends that could lead to operational enhancements. Consider a hotel – guests often report minor issues, like a malfunctioning TV remote or slow Wi-Fi, which the hotel staff promptly addresses during their stay. From a traditional FCR perspective, these issues are resolved successfully, ensuring a positive check-out experience. However, because of the limited scope of traditional FCR, the hotel management might miss an underlying pattern – a recurring problem with their room amenities or technology. Without recognizing this trend, the management doesn’t realise that upgrading room amenities or enhancing Wi-Fi services could significantly enhance guest satisfaction. This lack of insight means the hotel misses out on the chance to make systemic improvements, leading to lost opportunities for process enhancement and ultimately, superior customer experiences.
- Resource Inefficiencies: Without a precise understanding of FCR performance, contact centres often allocate resources inefficiently. Overstaffing or underutilisation of agents during peak and off-peak times was common, leading to cost inefficiencies. Consider an e-commerce company with a contact centre handling customer inquiries. During sales events, such as Black Friday or holiday promotions, the call volume significantly increases. Without accurate insights into FCR performance, the management might overcompensate by overstaffing the contact centre with extra agents to handle the expected surge in cells. Conversely, during regular days or slower periods, they might not have enough agents available because they base their staffing levels on generic historical data rather than FCR specifics. This results in overstaffing during peak times, leading to unnecessary labour costs, and understaffing during off-peak periods, which can lead to longer waiting times for customers and decreased service quality.
The Benefits of Using Speech Analytics
Speech analytics technology has revolutionised the measurement of FCR in contact centres:
- Automated Analysis: Speech analytics automates the analysis of customer interactions, capturing and processing vast amounts of data in real time. It can identify whether an interaction resulted in a successful resolution objectively.
- Objective Criteria: Speech analytics relies on objective criteria, eliminating the subjectivity associated with traditional methods. It evaluates interactions based on predetermined criteria, providing consistent and reliable metrics.
- Comprehensive Insights: By analysing speech patterns, keywords, sentiment, and other data points, speech analytics offers comprehensive insights into customer-agent interactions. It can detect trends and issues that might have gone unnoticed using traditional methods.
- Real-time Feedback: Speech analytics provides real-time feedback, allowing contact centre managers to identify and address issues as they occur. This proactive approach enables continuous improvement and enhances FCR rates.
Final Thoughts
The shift from traditional methods of FCR measurement to speech analytics has been a monumental advancement for contact centres. Speech analytics offers contact centre managers a more objective, comprehensive, and proactive approach to measuring FCR, effectively addressing the pain points associated with manual evaluations.
With speech analytics, contact centres can enhance FCR rates, improve customer satisfaction, and streamline operations, ultimately achieving their goals more effectively in the competitive landscape of customer service. The future of FCR measurement is data-driven, responsive, and customer-centric, thanks to the power of speech analytics.
As the contact centre landscape continues to evolve, the adoption of speech analytics is poised to play a pivotal role in creating data-driven, responsive, and customer-centric customer service operations. If you want to learn more about how Callbi Speech Analytics can help your contact centre achieve 100% call coverage and insights, please contact us for more information or a demo.
