Top 10 Questions to Ask When You Hire Your Next Call Centre Representative Asking the applicant what they think working in a call centre looks like can help gauge their
AI has already fundamentally shifted our approach in many industries already. And customer service is no different. Experts believe in the coming years we will eventually reach a point where
AI has already fundamentally shifted our approach in many industries already. And customer service is no different. Experts believe in the coming years we will eventually reach a point where the AI will become the agent and be indistinguishable from human agents.
Earlier applications of AI in customer service have proven itself to lower costs, improve staff and customer loyalty, drive customer satisfaction and increase revenue. Because of all these benefits AI brings, it’s hard to conceive of a future where full adoption industry-wide doesn’t occur.
If you want to dive deeper, we have an entire ebook dedicated to this topic. Except the ebook showcases real world use-cases of how exactly AI has helped improve CX for real companies. It makes it easy to digest while showing you its direct impact.
QA specialists host a vast amount of responsibilities from measuring, scoring, analyzing tickets across different channels and providing coaching to agents. It’s a key role and one that definitely helps increase customer experience. But it’s very time consuming and prone to bias and error. However this is something that AI can easily automate. When it comes to reviewing calls for example: A QA specialist only has time to cover 2% – 5% of all calls because of how time-consuming it is. AI can cover and monitor 100% of calls across all channels and collect that data. This means less time collecting and analyzing data, and more of doing what you really love to do – coaching your agents!
It was found by Aberdeen, that contact centers using AI capabilities enjoy a 3.5x greater annual increase in customer satisfaction rates (10.1% vs 2.9%). Leveraging AI means using speech analytics, text analytics, desktop analytics and journey analytics to capture data. Customer support teams use these tools to monitor and analyze customer-agent conversations in real-time. What this means for the agent is AI helps guide them in a timely, efficient, and effective manner enabling them to enjoy great improvement in driving customer success and satisfaction.
In customer support today AI is serving more of a supporting role. AI is amazing at capturing large amounts of data, analyzing it and presenting results back to us in a digestible manner. This way of using AI would help humans streamline the decision making process and figure out consequences to their actions.
This can be seen in the application of AI in CRM systems. A normal CRM system needs a lot of human interaction and upkeep. With AI a normal CRM system becomes a self-updating, auto correcting system that stays on top of relationship management for you.
If you want to see exactly how customer support teams utilize AI, I highly recommend downloading our e-book “Improving Customer Experience with AI” as it has several real-world use cases to learn from.