To say that the future of the Contact Center passes through artificial intelligence is nothing new. However, do you know what it refers to? 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 a boost to your customer service and call center, hiring a new one, or simply 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, both for 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 solve these problems. But how can contact centers and customer service leaders do this? The answer lies in artificial intelligence and the introduction of an autonomous contact center .
The 3 fundamental problems of a Contact Center.
Despite outsourcing and attempts at automation, contact centers have historically faced three major problems that still persist today:
Difficulty forecasting supply and demand.
Even with the best CRM you can handle, it’s difficult 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, that is, when agents answer too many repetitive calls, level 1 (very basic), they can cause burnout. That exhaustion one day and another, ends up implying a change of work.
Bad customer experience.
The more repetitive the tasks, the harder it will be for agents to stay focused and engaged. As a result, their 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 sought to work with AI was to eliminate all those repetitive tasks that did so much damage to Contact Center call centers . Through bots based on artificial intelligence, it would be possible to serve users in phases called “type 1”. This customer service-oriented automation, however, has not always been successful, as it has, in turn, frustrated 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 the 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 customers to learn their language, meaning customers have to say numbers, specific phrases, or keywords that the IVR recognizes. When IVRs fail to understand the problem, customers are turned over to an agent and have to repeat the problem. This leads to further frustration.
However, there is another type of more advanced intelligence, it is that of the autonomous Contact Centers , which provide a more effective way of taking advantage of artificial intelligence technology for customer service . Using the power of voice artificial intelligence, they act as the first line of defense when resolving Tier 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, the dynamic generation of arguments . Thanks to these, the contact center staff also has a completely segmented database that helps them to better direct campaigns and arguments, and through a system of predictive dialers to speed up contact making.
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 an impact on a subsequent improvement of the 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 across voice, SMS, mobile and other channels. When the AI is unable to resolve a problem, 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 right into solving the problem.
In this way, autonomous contact centers solve the 3 fundamental problems that I have talked about previously, in the following way:
Level 1 issues are resolved immediately.
In this type of repetitive and predictable tasks, it is where the machines behave 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.
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.
At Inquisitive Technology we have been working for more than two decades to offer excellence in omnichannel customer service , through our own Contact Center with specialized agents and with a minimum level of rotation. Technology has always been our flagship and through which we have entrusted the service to our clients, coming to work for many of the main international brands.
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