Forbes reports that nearly 74% of companies are actively looking into implementing AI to support their customer support agents. The reason is that AI offers contact centre managers a solution to support their staff's working experience, sense of job satisfaction and ability to provide quality levels of support when dealing with customers. The broad appeal is that by adding technology to the current process, ‘augmented agents’ can perform more effectively in their customer-facing roles.
Before we explore how AI can help improve performance in call centre agents. We must look at some typical struggles agents are facing. Here are seven common challenges.
At EdgeTier, we have spoken to over 50 contact centres to understand their issues. Our research highlighted seven key challenges that managers experience regularly. Here they are:
Before we explore how AI can help improve performance in call centre agents. We must look at some typical struggles agents are facing. Here are seven common challenges:
1. Poor First-Time Resolution
From the moment your customer reaches out to you for help, the clock is ticking.
First time resolution is the ability for an agent to get the response right the first time i.e. answer the customer question correctly at the time they ask. However, this is not always possible for a variety of reasons. For example:
- Agents must engage with the customer for longer periods of time to extract more information before solving the issue.
- Customers often have complex problems that cannot be answered with simple responses
- Staff turnover in contact centres is approximated at 30-40% meaning newer agents may struggle to solve issues at the first time of asking.
- Language barriers.
- Agents can provide unclear responses or low-quality replies that force customers to respond for clarification.
2. Slow First response time
66 percent of consumers feel that valuing their time is the most important thing companies can do for them. First response time (FRT) refers to how long it takes a customer service agent to respond to a customer support request.
Often, speed of response is a direct result of how well equipped your support team is to perform their jobs. The reality is that modern contact centres often fail to adequately train teams or provide them with enough tools to improve first response times.
David Bailey-Lauring, CEO at Blu Mint Digital emphasises the importance of quick agent reactions:
‘’If they don’t respond, I’ll find a new company to do business with (if possible). Slow response times definitely leave a bad impression for any future business.’’
3. Manual Organisation of Queries
When a customer query arrives at the help desk, often agents or team leads need to categorise and prioritise the query manually., Even where automated query categorisation is in place, queries can end up in the wrong place and need to be manually re-assigned. The result is a slow and manual ticket handling process that leads to delayed response times.
4.Multiple Languages cause issues
Agents are often faced with customer contacts from all over the world. This means staff must reply in multiple languages in order to resolve customers' issues. Language barriers result in poor customer experience and friction in conversations, not to mention scheduling headaches for contact centre managers.
5. Agents juggle multiple systems to handle the customer query
Agents can spend a long period of time searching multiple systems and databases for relevant customer information and historical context. This process often means agents will spend time switching between multiple tabs and windows in order to gather the necessary customer data.
6. Agents fail to alert management about issues
Agents are supposed to alert management of issues they face, but they don't have the time, or the tools to do it. The responsibility of finding and flagging issues, often means agents are late in raising problems to management or raise the issue at all.
AI can empower agents to get through more queries in less time and with higher quality by removing manual processes like ticket selection, drafting responses, wrap-up, as well as time spent searching for customer information. AI frees up agents’ time that they would have otherwise spent on error-prone, repetitive backend tasks.
Let’s drill down on how AI solves some of the aforementioned challenges and augments the current manual agent process.
1. Improved First-Time Resolution
AI can improve first time resolution by increasing the quality of the agent's response, reducing the likelihood that a customer will have to come back for clarification.
For example, EdgeTier's Agent-Assist technology will analyse a customer query and completely draft a response for the agent. Generated responses are best-practice with responses designed to minimise the need for a customer to respond for clarification.
2. Ai Supercharges First response time
Agent assist technology will also reduce first response time by making agents faster, therefore shortening queue times. We’ve worked hard to support agents in responding to customers quicker Here’s how.
EdgeTier supports agents with personal and topic-specific auto-responses and advanced prioritisation which can greatly improve first-time resolution. Agents can vary each customer’s auto-response with their account information, data on their query, and potentially redirect to internal self-service applications.
To ensure a consistent tone of voice the EdgeTier system follows best-practice in your contact centre to generate a completely individualised response for the customer. Responses go far beyond template suggestions, mimicking advisors' decisions around the topics being handled.
3. Tagging, routing, categorising and prioritising
Artificial intelligence will use text-based analytics to automatically analyse incoming tickets and route them to the most suitable pool of agents – turning ticket routing into a fast and effective process.
''EdgeTier is no ordinary software product ... It has completely changed how we work''
4. Ai is Completely MultiLingual
AI-based translation is now incredibly accurate and so can help agents respond to customers in different languages. EdgeTier AI is inherently multilingual allowing an agent to handle contacts in any language and achieve frictionless conversations with real-time translations. EdgeTier AI reduces the need for agents to speak multiple languages in order to communicate with customers..
5. Ai brings all relevant customer data to the agent
EdgeTier's AI lets agents get through more queries in less time by removing time spent searching for customer information on multiple systems. Once the AI understands a query, all pertinent information and historical context is retrieved automatically, reducing the need for time-consuming and error-prone window switching.
6. Monitoring and alerting AI
EdgeTier Alerts AI removes the burden on agents and instead allows AI to report issues to management. This ensures agents can focus on the customers rather than raising issues to management. Here is how:
- Monitoring: 24/7 monitoring of your customer conversations and contact centre activity for unusual patterns and anomalies.
- Alerting: AI learns your contact centre patterns and automatically surfaces errors and anomalies to yo
EdgeTier AI for Agent productivity
Customer service will always be your biggest competitive differentiator. AI is offering an accessible solution to boost the performance of support teams and individual agents.
If you are looking for a next-generation, customer support solution.