How Are AI/Ml Advancing Call Centres To The Next Level
With the pandemic hitting businesses worldwide, contact centres have emerged as an essential link between brands and their customers. However, as per various studies, many customers feel demotivated to complete a purchase due to lack of quality engagement. To put it in numbers, American Express conducted a survey and found more than 78 percent of customers decided to call off their purchase due to poor customer service. As a solution, many brands are warming up to the idea of infusing Artificial Intelligence (AI), and Machine Learning (ML) based technology systems to leap into the next level of revenue generation and customer servicing. Here are some advantages of AL/ML based contact centres.
Segregating Unstructured Data
Today contact centres have become an epicentre of massive customer data, which can be utilised to make crucial business decisions. Here AI, along with ML, can play a vital role in organising the unstructured data and impact every level of functioning to serve customers better. AI and ML can store the tiniest customer detail, interaction and engagement history in a systemic manner, which can be pulled out as and when required. For instance, the calling agent can pull out an entire engagement history of the calling customer and deal with the problem without having the customers repeat his/her issues.
Scalable Solution To Handle More Queries At Same Employee Strength
Apart from automatically capturing the data, AI can also route calls to the suitable agent based on the analysed data initially. It allows customers and brands to save precious time and find concrete solutions instantly. Further, AI also helps in creating customer profiles for any unforeseen future references. Here, all these activities and more can be performed without hiring additional human resources.
Personalised Chatbots To Offer 24x7 Support
The combined power of AL and ML can make chatbots come alive to handle level-1 queries for brands. Simple customer requests to add, delete an item in the purchase list or cancel an order, and etc., can be managed beautifully without human intervention. AI and ML allow chatbots to quickly analyse human sentiment basis customer's intent and respond accordingly in a positive manner.
Agent To Focus On More Complex Queries
As a result of technology managing most queries, it allows brands to engage calling agents to handle more complex issues, giving more personalised attention to customers. Here, it is essential to note that AI/ML-based chatbots also provide customised solutions however, complex queries the intensity of understanding human sentiments reach challenging levels and demand human intervention.
Automate Manual Tasks With Zero Scopes Of Errors
Automation is a crucial aspect of AI and ML-based technology. It empowers brands and their employees to automate various transactional and time consuming tasks such as capturing customer profiles, sorting data and much more. By automating such tasks, brands can delegate more strategic work to the employees and spend more time and effort in training the staff.
In their strive to provide a seamless customer experience via contact centres, AI and ML empower brands with deep learning to create knowledge graphs to arrive at matured answers to common business queries. On the other hand, it will continue to allow brands to offer a highly personalised and feel good service to customers leveraging a combination of intelligent technology and human resources.
Segregating Unstructured Data
Today contact centres have become an epicentre of massive customer data, which can be utilised to make crucial business decisions. Here AI, along with ML, can play a vital role in organising the unstructured data and impact every level of functioning to serve customers better. AI and ML can store the tiniest customer detail, interaction and engagement history in a systemic manner, which can be pulled out as and when required. For instance, the calling agent can pull out an entire engagement history of the calling customer and deal with the problem without having the customers repeat his/her issues.
Scalable Solution To Handle More Queries At Same Employee Strength
Apart from automatically capturing the data, AI can also route calls to the suitable agent based on the analysed data initially. It allows customers and brands to save precious time and find concrete solutions instantly. Further, AI also helps in creating customer profiles for any unforeseen future references. Here, all these activities and more can be performed without hiring additional human resources.
Personalised Chatbots To Offer 24x7 Support
The combined power of AL and ML can make chatbots come alive to handle level-1 queries for brands. Simple customer requests to add, delete an item in the purchase list or cancel an order, and etc., can be managed beautifully without human intervention. AI and ML allow chatbots to quickly analyse human sentiment basis customer's intent and respond accordingly in a positive manner.
Agent To Focus On More Complex Queries
As a result of technology managing most queries, it allows brands to engage calling agents to handle more complex issues, giving more personalised attention to customers. Here, it is essential to note that AI/ML-based chatbots also provide customised solutions however, complex queries the intensity of understanding human sentiments reach challenging levels and demand human intervention.
Automate Manual Tasks With Zero Scopes Of Errors
Automation is a crucial aspect of AI and ML-based technology. It empowers brands and their employees to automate various transactional and time consuming tasks such as capturing customer profiles, sorting data and much more. By automating such tasks, brands can delegate more strategic work to the employees and spend more time and effort in training the staff.
In their strive to provide a seamless customer experience via contact centres, AI and ML empower brands with deep learning to create knowledge graphs to arrive at matured answers to common business queries. On the other hand, it will continue to allow brands to offer a highly personalised and feel good service to customers leveraging a combination of intelligent technology and human resources.
