Apparently, we can’t help Barbara anymore. But how can we avoid the premature aging of Megan, John, Anthony, and all of their hard-working colleagues in traditional call centers?
And how to improve the user experience of their customers?
Both these questions have a common answer: implementing AI. Specifically, machines can help enhance call centers by:
- Reducing call volumes
- Offering intelligent call routing
- Personalizing the user experience
- Assisting human agents in their duties
Call centers are evolving!
What about the last time you contacted a call center? Did you have to type the entire first canto of the Divine Comedy on your phone screen to move through the prompts?
Have you talked to fifteen different operators and ended up yelling at the last poor guy on the other side of the phone?
Fortunately, organizations are beginning to understand that their call centers are critical interaction channels for improving customer satisfaction and engagement, providing quick problem solving and a personalized experience.
Implementing AI is the right way
According to a study by American Express, 78% of consumers did not make an intended purchase due to poor service experience.
To avoid such situations, many call centers are focusing on modern artificial intelligence and machine learning technologies. This allows them to gain valuable insights into customer preferences, potential churn and retention rates, and willingness to buy.
Once this information is gathered, call centers that have implemented AI can use all available data to guide each customer interaction.
Somebody said “data”? Let’s stop one moment on this concept, which can enlighten us on AI’s potential.
Leveraging data with Machine learning
Artificial intelligence can play an essential role in call center activities thanks to its ability to manage data better and faster than humans. The reason for this amazing capability lies first of all in AI’s most recent evolution, known as machine learning (ML).
Machine learning is a branch of AI focused on creating algorithms that can learn from data, recognize specific patterns, and make predictions about it. And the best part is that these algorithms are not even specifically programmed to do so!
Think about an algorithm to distinguish between cats and dogs in a pic. Our machine, which is a notoriously rebellious student and doesn’t trust its professors, will teach itself how a cat or a dog looks by analyzing thousands of animal pics.
The algorithm’s target, which is to identify cats and dogs, has been defined by programmers, but the path to reach this aim will be understood by the machine itself after training on data.
The same logic can be applied in call centers!
If we feed an ML-based system with data such as employees’ performances and career or customers’ behavior, issues, and account history, the machine will start to recognize patterns and categorize people in different archetypes with common traits.
Some practical examples?
When a call center operator proposes an offer to his customer, it can be a good idea to record any crucial information about this interaction (starting with positive or negative responses) and pair it with information about the client itself.
How do we use pattern recognition?
AI can analyze a wide series of repeated interactions with many customers and discover patterns. Maybe a certain offer or marketing strategy turns out to be attractive to a specific type of client.
By combining data about the agents, their actions, and the responses received, AI will offer companies efficient negotiating models to follow.
AI could even understand that specific operators tend to excel in some tasks and, on the other hand, struggle when facing different issues.
An operator may be a sales wizard, but he could have some trouble dealing with the stress of repeated complaints from dissatisfied customers.
The great step forward: deep learning
A further step has been taken with the development of deep learning, a branch of ML that trains machines to learn from huge amounts of data thanks to artificial neural networks.
DL-powered systems can recognize the most hidden and unpredictable patterns by digging deeply into the data and processing the information through the sprawling structure of their networks.
Deep learning unlocks even more surprising innovations, first of all in the field of speech recognition and interactive voice response.
Basically, any virtual assistant and chatbot make extensive use of these algorithms to process the human voice and respond accordingly. This allows companies to automate a wide range of processes in their customer care, including call centers.
Another interesting application of speech recognition is linked to behavioral analysis and aims to identify signs of discomfort during a customer’s phone call, for example by analyzing the tone of voice or the choice of words.
1. AI to reduce call volumes
All right, now that you have a clearer idea of how these new technologies work, let’s take a closer look at the benefits AI can deliver to call center companies.
The first is to prevent customers who wait for an operator from turning into skeletons after seventy years in the queue. That’s what happened to Yuri. You can see a recent pic of him below.