Saying that the future of the Contact Center goes through artificial intelligence is nothing new. However, do you know what it means? What are the three main problems they face? How will the CC business model adapt with AI? How will autonomous centers benefit? of this technology? If you are considering giving your customer service and call center service a boost, hiring a new one, or just dedicating yourself to it, I think this post can help you. Let’s go for it.
Contact centers have always been considered a cost center and a source of frustration for both companies and customers. Although companies have used BPO to reduce the cost of running a contact center, they have not solved the fundamental problems.
For contact centers to thrive, organizations must address these issues. But how can contact center and customer service leaders do this? The answer lies in artificial intelligence and the introduction of an autonomous contact center .
The 3 fundamental future problems of a Contact Center.
Despite outsourcing and attempts at automation, contact centers have historically faced three major problems that still persist today:
1. Difficulty forecasting supply and demand.
Even with the best CRM you can handle, it’s hard for contact centers to accurately predict call volumes and always have the perfect number of agents on staff to meet demand. Contact centers end up with too many or too few agents, leading to higher costs or long wait times and poor customer experiences.
2. High turnover rates.
The above problem is aggravated by the fact that agents do not stay in contact centers for very long. Call centers typically have an average turnover rate of 30% to 45%. Some even have triple-digit turnover rates.
Turnover is so high because most agents prefer a less boring job, i.e. when agents take too many repetitive, level 1 (very basic) calls, it can lead to burnout. That exhaustion one day and another, ends up implying a change of work.
3. Bad customer experience.
The more repetitive the tasks, the harder it is for agents to stay focused and engaged. As a result, your quality of work and customer experience suffer.
If your business has to do with customer service, or your brand usually works with this type of service, you will have felt identified with each point that I have just mentioned. However, there is good news. There is no reason to resign yourself to these problems, since artificial intelligence has a lot to say about it. I tell you.
How Artificial Intelligence can help to create a new Contact Center model.
One of the first points that was sought to work with AI was to eliminate all those repetitive tasks that caused so much damage to the call centers of the Contact Center . Through bots based on artificial intelligence, it would be possible to serve users in “type 1” call phases. This customer service-oriented automation, however, has not always been successful, in turn frustrating customers in some cases. The phone, in particular, has been difficult to automate because it requires artificial intelligence to process the context of a customer’s call, accurately understand the request, and respond quickly.
Companies that have tried to develop voice AI in- house have rarely managed to put the technology into production or process thousands of calls with AI. On the other hand, companies that have not created a custom solution have turned to IVRs (Interactive Voice Response). Because IVRs use primitive AI models or phonetic recognition, they require clients to learn their language, that is, clients have to say numbers, specific phrases, or keywords that the IVR recognizes. When IVRs fail to understand the problem, customers are passed to an agent and have to repeat the problem. This leads to further frustration.
However, there is another type of more advanced intelligence, that of autonomous Contact Centers , which provide a more efficient way to take advantage of artificial intelligence technology for customer service . Using the power of voice artificial intelligence, these act as the first line of defense in resolving Level 1 customer service issues, without burdening agents with repetitive, high-volume calls or keeping customers on hold. .
But they also help agents in more advanced calls, through, for example, dynamic script generation . Thanks to these, the contact center staff also has a fully segmented database that helps them to better direct campaigns and arguments, and through a system of predictive markers to speed up contact.
Another fundamental aspect lies in what is related to the customer experience , since through artificial intelligence, from the moment the call is being made, the intelligence software is carrying out an exhaustive analysis, which has repercussions on subsequent improvement of service and customer experience.
And finally, everything related to customer knowledge , where AI allows us to extract all the information we have in the CRM, analyze it and help us understand what they want based on their demographic, geographic, sociographic, and even psychographic characteristics. , offering us that information at the time of making the call.
They also provide customers with multi-experience omnichannel support through voice, SMS, mobile and other channels. When the AI cannot resolve an issue, it is escalated to an agent and a summary of the interaction is shared with the virtual agent. Customers don’t have to repeat themselves, and the agent can jump straight to solving the problem.
In this way, autonomous contact centers solve the 3 fundamental problems that I have spoken about previously, in the following way:
1. Level 1 issues are resolved immediately.
It is in this type of repetitive and predictable tasks that machines perform best. For example, looking up the status of a shipment, finding the location of a branch near the customer or reporting the status of their subscription, are some of the tasks that you can completely eliminate your team of agents, thanks to AI. In this way, agents can focus on solving more complex problems.
2. The number of agents is adjusted to the call demand forecast.
Artificial intelligence makes it possible to predict call peaks, but what is better, by having an automated filtering of virtual agents, makes the real transfer to agents, because they are queries really out of the ordinary, reduce, having the Contact Center from the right agents so you don’t keep incoming calls on hold.
3. Greater customer satisfaction.
Anyone does not care if a machine or a person helps, as long as they do not have to wait for their solution to the problem and it is resolved as quickly as possible. With this system, every call is answered immediately by AI, and calls are faster and more efficient. When talking to a machine, there is no chat. Customers also don’t have to wait while agents manually enter information or navigate between multiple systems. By connecting to CRMs and contact center software, AI technology instantly finds and updates information. It also automatically generates summary notes for more detailed information about the calls you’ve handled, greatly reducing manual data entry by agents.
As you can see, AI makes a significant leap in customer service management and satisfaction. Surely you will wonder, how to start to start it. To do this, you must be clear about each of these points:
- Identify a use case for automation.
- Determine which systems need to be integrated.
- Make sure the data is up to date and accurate.
- Implement one of the use cases and determine its value from a business point of view.
New tech could give Chatgpt a run for its money. It turns your Youtube videos into video games..keeps people engaged to watch every second. You can even reward them for watching the whole video and they give you their email to get the reward 😉 As seen on CBS, NBC, FOX, and ABC.