Call centers are very complex environments and are facing the biggest challenges of their industry. Call centers are now a [$200 billion sector].
According to Forbes, "AI-enabled conversational agents, for example, are expected to handle 20% of all customer service requests by 2022" Technology, such as AI and robotics, will improve customer service and provide more options for the customer.
First call center problems arise
Call centers are a vital part of modern business and customer relations, but many companies struggle to provide the best possible service. One of the most common complaints from customers is that call center employees often do not seem to be listening to their concerns.
Although there are many reasons for this, one of the most prominent is that most call center employees rely on pre-scripted responses and don’t have any context about the customer’s situation. This can lead to miscommunication and frustration on both ends of the line, but conversational AI has opened up new opportunities for call centers by allowing them to personalize their interactions with customers.
What is conversational AI is made of to help call centers?
Conversational AI has become the most widespread innovation in customer service in the last decade. This is because it is a relatively simple technology and building and implementing conversational AI apps into the businesses' operations isn't as expensive and tedious as some think. Conversational AI can be programmed to be highly personalized, which means that every customer will have a unique experience, and the AI will take into account the context of the conversation.
The biggest challenge of conversational AI is how to train the technology to be able to understand human speech and respond. This can be done by using natural language processing and learning about human speech patterns. Dasha AI, for instance, uses a set of machine learning (ML), natural language processing (NLP), text-to-speech (TTS), speech-to-text (STT). The technology can be trained using a combination of supervised and unsupervised learning. The technology also uses unsupervised learning to learn speech and language patterns.
Let's take a look at what the most common call center issues are and how conversational AI can help you solve them.
Major call center problems and conversational AI solutions
- Budget constraints
According to CallCentreHelper, over 70% of call center companies experience a lack of budget. That is because of the high cost of staffing and training.
Conversational AI can be a great solution because it allows call centers to handle more calls using less human resources. In addition to that, since the technology can handle more calls and better track those conversations, call centers can reduce their idle time. This means that they can spend more time on a different, more complex service for their customers.
- Call center employee churn
It is not uncommon to hear stories of call center agents quitting within the first few months of working at a call center. This is because they are not given enough time to adapt to the new technology. They also have to deal with high stress levels, which are known to interfere with their performance. Many call center agents also suffer from burnout, which is especially prevalent in call centers that do not offer much support and are not well-equipped to help call center agents combat stress.
The turnover rate can be even higher in call centers located overseas, where call centers are usually managed by outsourced agents. Because of the high turnover rates, it leads to wastage of resources and increases the cost of maintaining a call center.
The turnover rate is even more pronounced in low-wage call centers, because they cannot afford to invest in training and recruitment. The turnover rate also increases the likelihood of poor customer service and leads to customer complaints. Lastly, the turnover rate can result in the loss of company image and customer trust. The lack of trust in the company or call center leads to reduced sales.
Conversational AI is a viable solution that can reduce the turnover rate and increase customer satisfaction. Because the technology is not prone to human errors, it is a great solution for call centers that struggle with high rates of inaccurate or incomplete customer interactions. Furthermore, conversational AI removes the need for customer service agents to be present during the calls, allowing for a more cost-effective customer service model.
Another challenge of working in a call center is absenteeism. That is because call center agents are often required to work late nights and some even work for a full week without taking a day off. This is because call centers are required to meet industry standards on customer service and customer satisfaction. With fewer customers or calls, call centers are forced to run for longer hours to meet their targets.
As a result, call center agents often suffer from fatigue related illness such as exhaustion, stress, and poor sleep. This further results in the agent making mistakes or not understanding the customer. This in turn affects the quality of the call. So, the lack of a healthy lifestyle can also be a reason for absenteeism from the call center.
There are a number of ways to address absenteeism in call centers. The first option is to create a healthier work environment to facilitate a better work-life balance. The second one is to implement conversational AI to reduce the number of calls that are missed.
Conversational AI can reduce the need for human agents to be present in the call centers. In a scenario where there is no need for a human agent on the spot, AI can step in and help the call center to operate 24/7.
When operators work at a call center long enough, they can experience burnout. Burnout, in turn, may lead to a lack of motivation to perform well and work towards the next promotion or pay raise. In such a case, targets are not being met, leading to frustration of both the managers and the employees.
Since the call center environment is a fast-paced one, the management might not have enough resources to combat the lack of motivation and stimulate and upskill the employees.
Conversational AI is a great asset in this case since both the management and the staff will have the necessary time to improve the call center operator's skills, both technical and soft skills.
- Lack of first call resolution
Sometimes the first call taken by customer service agents is not an easy one. It might be a call where the customer is not satisfied with the service and is not following the instructions. These calls are not easy to handle. The first task of the agent is to establish the problem and help the caller with the problem. This may require the agent to spend a lot of time on the call and even put the caller on hold. In such a case, the agent might not have enough time to solve the caller's problem. In some cases, the agent might need to call another technical support team to solve the issue. This leads to a low first call resolution.
Conversational AI can get all the information needed from a customer without putting them on hold or transferring them to an agent, who might later transfer the customer to yet another agent. Conversational AI can handle it all when the conversational AI app is programmed to recognize the person's problem, whatever it might be, and resolve the issue in a short time.
What can conversational AI automate at a call center?
- Handling calls from different time zones
Conversational AI can answer all of the questions asked by callers and provide the caller with the required information. Conversational AI can even handle calls with accents. This frees up more time and effort for the agents to solve all the other calls. More time can be spent on other areas of the call center, such as training new agents, improving the customer service system, or reducing the number of missed calls.
Transfering leads automatically to your CRM
With a simple HubSpot integration through Zapier, you can send the lead’s information to HubSpot, for instance. Here's the post to check out for more detail.
Automating lead qualification, conversion, and scoring
If you have the infrastructure to support it, have your sales team send leads to the conversational AI app to get their questions answered. Conversational AI can handle lead qualification, conversion, and scoring automatically. The more leads the app gets, the higher chance of the lead turning into a customer.
- Automatic customer follow-ups
After a conversation with either an AI or an operator, you can program the conversational AI app to initiate follow-up calls if no resolution was found during the initial call.
Conversational AI can be used 24/7. It isn't restricted to working hours. It is a great asset to your call center. It can handle a huge chunk of the workload that your employees have been dreading. With the help of conversational AI, you can reduce the number of calls transferred to agents.
Examples of conversational AI apps
Here are a few examples of what use cases conversational AI can be used for:
You could start off by building a simple insurance customer service app: Embedded content: https://www.youtube.com/watch?v=46nyWBTSHgs
Or an automated receptionist for a hotel front desk: Embedded content: https://www.youtube.com/watch?v=2Glp_HC-VHc&t=29s
OR you can integrate Dasha with an incident management platform to be able to resolve incidents on the go: Embedded content: https://www.youtube.com/watch?v=TeJAFI993_0
Or build an app to qualify inbound leads and integrate it with Hubspot: Embedded content: https://youtu.be/MjKQ2Zibqgk
Even a non-developer can create conversational AI apps
Dasha is intuitive and simple enough to let those with no prior coding experience automate tasks. The abovementioned demos were not made by developers, but by those with either minimal or no programming background.
Try it yourself and join Dasha Developer Community to get all the support and help you need! Looking forward to seeing you there :)