Contact centres have always been challenging environments that involve high workloads and high volumes of data. The challenge is often arming the contact centre with sufficient resources and empowering agents to deliver an excellent customer experience.
The flexibility of cloud contact centre technology helps contact centres to be more responsive to customers’ needs but it’s not a magic fix to your typical contact centre challenges.
Artificial Intelligence (AI) stands to give cloud contact centres a much-needed boost, solving many pressing problems while introducing new customer service capabilities that can dramatically enhance the customer experience.
How AI Is Transforming Contact Centres
AI is having a transformative effect on countless technology applications – and cloud contact centres are drawing substantial benefit too. It’s not just a matter of faster processing and around the clock availability, AI brings new possibilities too. Let’s take a look.
Fixing IVR Frustrations
Yes, voice recognition on its own can help customers skip pass tedious IVR lists, but it’s not uncommon for customers to get frustrated with voice-enabled IVR. AI technologies including natural language processing can better understand what a customer really wants to achieve with their call.
In turn, customers get the assistance they need right there and then or at least get transferred to a contact centre agent that has the necessary expertise.
Ensuring Responses Around the Clock
Needless to say, robots do not need rest, sleep or days off. Particularly for smaller to medium-sized businesses the highly desired objective of 24/7 support can be hard to achieve.
Live agents will always be needed to deal with certain queries, but AI can be a valuable tool to support contact centres, especially as helping customers deal with their issues around the clock becomes a necessity rather than a unique selling point.
Live Agents Get Better at Resolving Issues
AI is not just there to help customers: AI-driven contact centres can also help live agents while they are dealing with a customer by, for example, providing solution recommendations in real-time – based on an AI-informed analysis of a customer’s past interactions. Doing so leads to rapid issue resolution.
Similarly, AI can suggest the most useful answers to the typical questions posed by customers by taking into account aggregate customer interactions. This can feed into your Knowledge Base or FAQ section that can be used internally by agents and externally by customers. In turn, more efficient agents and customers lead to a boost in customer satisfaction, while keeping contact centre costs down.
Understanding Customer Intent
AI goes beyond simplistically parsing voice inputs by also understanding the true intentions of a customer. AI does this by using a mix of natural language processing and machine learning to glean insights into the real motivations for a call, based on an analysis of thousands of past interactions.
Understanding the context behind a customer’s query can steer them through a contact centre quicker and easier, while building data to show what the customer really wants – and indeed the customer’s state of mind. Of course, combining an understanding of customer intent with analysis of previous interactions can truly transform the customer experience.
Predictive Analytics, Business Intelligence
Contact centres – and indeed entire customer service operations – perform better when harnessing the large pools of customer data generated during service interactions. AI can learn from customer data and present insights that improve contact centre performance.
These insights have far-reaching benefits – from the way contact centres are organised through to how individual calls are dealt with. The machine learning algorithms that underpin AI also delivers far deeper insights into customer experience metrics such as customer effort, useful in establishing where customer experience pain points are.
Example of A Typical AI Use Case
At Conn3ct we helped a large UK supermarket to transform their IVR system from routing only 30-35% of calls correctly to over 90%. This resulted in more happy customers being routed to the right place, saving the customer and supermarket significant time and money respectively.
The key technology behind the solution was natural language understanding (NLU), which can understand human speech. The supermarket used Amazon Connect and a newly-developed chatbot to empower customers to speak their postcode and state their needs.
In addition to harnessing the power of voice technology, the supermarket also uses CLI (caller line identification) to correctly route calls. This is synced with their supply chain fulfilment partner’s database.
Now, when a customer dials in, the supermarket can look up their CLI, or caller display, to identify the caller in their database and their location. This also ensures customers are routed through to the right contact centre straight away.
If the customer’s CLI isn’t displayed (this is sometimes hidden), or their phone number isn’t stored in the supermarket’s database, the system will ask the caller to say their postcode to determine their location and call destination.
Engaging with AI in Your Contact Centre
Companies that want to get the most out of AI in their contact centres need to take a step back and approach the AI-powered contact centre for the revolution it is. Rather than just using AI to improve existing processes, companies should see AI in contact centres as an opportunity to re-invent.
Conn3ct has implemented AI-driven contact centre solutions for countless clients and we know how its AI capabilities can transform the contact centre experience and contact centre performance.
Download our guide, 3 Ways Amazon Connect Will Transform Your Customer Service Capabilities to get a broader insight into Amazon Connect’s transformative potential. Or, get in touch with Conn3ct to see how Amazon Connect can deliver progress for your contact centre.
Blog published with permission from original source: https://www.conn3ct.com/blog/ai-cloud-contact-centre