First Call Resolution (FCR) is an indispensable metric for contact centres to measure and improve.
Research conducted by Ascent Group suggests that 60% of companies measuring FCR for a year or longer reported improvements of up to 30% in their performance. Measuring FCR is beneficial as it evaluates the efficiency of the agents, reflects the quality of customer services and provides insights on the improvement areas.
FCR is a valuable business metric as it not only improves customer satisfaction but also helps in minimizing operating costs.
For instance, let’s say a contact centre receives 25,000 calls every month and the FCR rate is 60%. This shows that 40% of calls require follow-up support. If the FCR rate improves by just 10%, there will be 2500 fewer calls every month or 60,000 fewer calls every year. This reduction in calls enables a contact center to allocate resources better, and saves a lot of time and money!
Here are 7 actionable ways you can quickly improve your FCR rate and enhance customer experience.
Chatbots have become an essential addition at contact centres to streamline several parts of customer service. “25% of customer service and support operations will integrate bot technology across their engagement channels by 2020, up from less than two percent in 2017”, report by Gartner suggests.
Enabled by conversation AI, NLP and ML, chatbots today are capable of understanding the ‘intent’ behind customer queries and conducting human-like conversations. This ability enables them to handle tasks such as providing information, answering FAQ, sending instant responses, collecting user information, among many more. Chatbots provide self-service options to customers and can be used 24/7 for customer care.
Chatbots also act as the first line of support and only route extremely complex conversations to agents. All these capabilities of chatbots help them to engage customers until the issue is resolved – thereby reducing the need for a follow-up conversation and improving the FCR.
Another emerging bot technology to consider is conversational IVR. Powered by AI and Natural Language Processing, conversational IVRs provide a unique voice-based and hands-free solution where customers can interact using natural language as opposed to choosing the options from a long static menu offered by traditional IVRs.
Reduced customer service costs, improved CSAT, increased agent productivity, streamlined workflows, a decrease in the number of customer emails and calls are some more key business benefits of deploying bots in contact centers.
Rewarding agents on resolving issues on the first call is a great way to motivate agents to perform better and an investment that companies should make as the returns that they reap on reducing the number of call-backs is much bigger.
Evaluating agents based on the average handling time can prove to be an ineffective strategy as they can close calls without successfully resolving an issue to save time. Incentivising agents on resolving customer requests on the first call would be a good long term strategy as it relieves them from the pressure of saving time and shifts the focus to effectively resolve issues. This reduces call-back from customers and in turn saves time.
Customer journey analytics can be an eminent tool at call centres to have a well-rounded understanding of customer service journey. It is one of the primary steps to resolve FCRs and build an effective interaction with customers to avoid voice calls.
Traditionally, companies have relied on customer surveys to glean insights on escalations to agents, which proved to have serious limitations. Companies are deploying customer journey analytics to accurately understand the events throughout the customer service journeys that lead to failure escalations and failure in service.
Customer journey analytics provides insights to predict the likelihood of escalation and is a great tool to proactively design self-service to customers. With customer journey analytics, structured and unstructured data from various channels like website, mobile app, chatbot can be integrated. This is useful in eliminating the silos across the channels and have a comprehensive cross-channel understanding of customer behavior, issues and drop-offs, which offers a proactive preparedness for contact center agents for potential escalations from various channels.
In order to measure FCR, contact centres traditionally were dependent on reports by agents, QA team analysis and customer surveys. However, these practices are becoming increasingly ineffective. Agent reports can be inaccurate and biased, QA teams usually are not so confident in the data they’re provided and customers don’t actively participate in surveys.
Organizations are therefore implementing speech analytics – a great tool to understand customer pain-points by recognising patterns and keywords in conversations that indicate customer distress or dissatisfaction.
It can be used to measure the number of customers who call more than once to resolve their problem. It also helps in identifying trends, attrition hints, process issues and any inhibitors to FCR.
Speech analytics provides actionable information about customer calls and supports root cause discovery. This allows call centers to reduce repeat calls and the need for callbacks.
Equipping contact center agents with exhaustive knowledge and training meticulously on their function is fundamental to improve FCRs. Agent training hours is found to be one of the biggest drivers for first call resolution that yields improved rates of FCR and higher customer satisfaction.
Following up on the previous point, while training agents it is also essential to equip their knowledge with all the essential information they may need to effectively help a customer.
Dashboards that provide a 360-degree view of customers can be a useful tool for agents to have a better understanding of the customers that approach them. These dashboards equip agents with all the necessary information about customers like purchase history, preferences, conversation history that are essential during a live conversation to provide a seamless interaction and resolve issues on the first contact.
This reduces the handling time as agents spend less time in gathering necessary information to understand the issue.
Next Issue Avoidance (NIA) is a useful metric to enable agents to predict prospective customer issues. NIA is derived by analyzing data from large sets of tickets raised by customers to anticipate the issue that customers can come up with, which can be leveraged to eliminate a large number of calls.
NIA is a critical strategy adopted by several contact centres to reduce customer effort, improve contact centre effectiveness and establish loyalty from customers. Research suggests that 46% of customer support cases are avoidable by predicting the next potential problem.
As customer service costs continue to increase, measuring and improving FCR is an imperative part of any effective Customer Experience (CX) strategy. By using the right processes, approaches, technologies and resources companies can now predict and resolve issues with the least Customer Effort Score (CES), reduce contact center volume and improve CSAT.