It can be stated with some confidence that first-contact resolution (FCR) is one of the keys to a successful contact center.
Our annual survey of 1,000 U.S. customers for the recent ContactBabel report, "AI for First-Contact Resolution," found FCR is the top driver of customer experience, even more important than short queue times or polite and friendly agents.
So, it makes sense that to improve customer satisfaction companies have to improve their FCR rates.
The ability to understand a query and deal with it in a reasonable timeframe on the first pass reduces the cost of interactions while providing the customer with a good experience, both of which impact organizations' overall performance. This also has a positive effect on agent morale (and thus, staff attrition and absentee rates) and increases the chances of successful cross-sells and upsells.
It's little wonder that the FCR metric has grown hugely in importance. Unlike many other metrics, it works for both customers and businesses.
Yet the contact center industry has not reported any lasting or significant ongoing improvements in FCR, which is actually declining. While the average call is more complex than it used to be, requiring follow-up work and perhaps more expertise, this drop in FCR has a negative impact on customer experience and profitability by increasing costs incurred by repeat contacts.
FCR can be problematic to quantify accurately, and this risks the metric being downplayed, especially as it is not simply a matter of producing a monthly report from automatic call distributor statistics. It is as much a measure of the entire business' success as it is an internal contact center metric. And, as with any single metric, excessive focus on achieving perfection can have a negative impact elsewhere.
AI can be used not only to measure FCR accurately but also to provide insights into what drives repeat contacts and how to reduce them. But before any organization can improve its first-contact resolution, it needs to measure it and understand it.
AI assists by leveraging automation, data analytics, and real-time monitoring, including the following:
- Automated Data Collection and Analysis -- AI can analyze customer interactions across multiple channels to determine if the issue was resolved in the first contact, as natural language processing can extract key phrases from conversations to identify resolution status.
- Predictive and Sentiment Analytics -- AI-powered sentiment analysis can determine whether customers are satisfied with the resolution or likely to call back, with machine learning models predicting whether an issue will require follow-up based on historical data.
- Intelligent Call and Chat Monitoring -- AI can monitor live interactions and flag unresolved cases when the customer expresses uncertainty or frustration. Real-time transcription and analysis can help verify resolution status without manual input.
- Automated Follow-Up Surveys -- AI can trigger post-interaction surveys via SMS, email, or chatbot to confirm resolution. Sentiment-based surveys can detect implicit dissatisfaction, even if the customer doesn't explicitly say the issue is unresolved.
- Customer Journey Tracking -- AI can track customers' journeys across multiple interactions to check if they reached out again for the same issue, integrating CRM, ticketing, and call logs to ensure resolution measurement is accurate.
- Root Cause Analysis -- AI can identify common reasons for repeat contacts and suggest process improvements, allowing predictive analytics to address issues proactively before they lead to multiple contacts.
With FCR consistently ranking as the main factor driving customer experience, organizations should always be looking at ways to measure, understand, and improve this key metric. AI can help improve FCR in the following ways:
- Interaction Analytics -- AI analyzes historical data to identify common customer issues and the solutions that have resolved them, suggesting the most likely solutions to agents during the first call and increasing the chances of resolving the issue without follow-up.
- Root Cause Analysis -- AI can find patterns in past interactions to identify recurring issues that frequently require multiple contacts. This then provides the business with the insight to fix the processes that are causing these issues.
- Intelligent Routing -- AI matches incoming calls with the best-suited agents based on various criteria, including agent skills and expertise, caller intent, and customer profiling. Compliance-based routing can ensure calls are routed to agents who are certified or trained to handle specific regulatory requirements, reducing call transfers or call-backs.
- Agent Assistance and Channel Optimization -- AI-enabled agent assistance helps FCR by providing the right information at the right time, which is especially useful for inexperienced agents. The AI draws on the dynamic knowledge base, and by following the conversation in real time can gather the relevant information and present it on the agent's screen, which also reduces call duration and cost. AI can also make sure that agents have followed all of the correct procedures, which reduces the risk of repeat calls due to agent error. Post-call work can also be optimized through automatic initiation of back-office processes, reducing the risk of human error. AI can also maintain and disseminate consistent and correct information across all channels, making it available to digital agents and human agents, improving the level of sophistication and functionality available to customers using self-service and digital channels.
- Toward No-Contact Resolution -- By analyzing historical data, purchase behavior, and customer interactions to find where customers are likely to need support or information, AI can proactively engage customers to reduce the costs associated with high call volume. This information can be fed back to departments and process owners, who can improve the messaging and activities that are causing repeat calls and customer uncertainty.
Through the judicious use of AI-enabled analytics, organizations can move beyond aiming for FCR and start delivering no-contact resolution, giving customers what they need before they even realize they need it.
Steve Morrell is managing director of ContactBabel.