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How Advanced Artificial Intelligence Based Chatbots Help Save Time In Customer Service

Nowadays, chatbots are not just about providing quick resolution to customer inquiries, they have become advanced enough to understand customer emotions and predict behavior. Data Analytics and Machine Learning with chatbots can be used to identify customer demands and industry trends. They can help better differentiate a company from the competition, learn customer interests, and suggest necessary revamps. Moreover, the platform independence and omnichannel capability of chatbots can reduce operating costs for businesses and provide better leads for employees to target. Along with this, the new advancements in technology, such as sentiment analysis, artificial intelligence, and natural language processing have further enhanced experiences for both customers as well as employees.

Here’s How AI Chatbots Help Save Time In Customer Service

1. Reduced average handle time 

We all know that companies have thousands or even more inquiries coming in every day and mostly that’s where most businesses implement chatbots. But, businesses should not just restrict chatbots to simply answering customer concerns 24/7. 

Actually, chatbots are much more than that! 

Chatbots with Artificial intelligence and data analytics capabilities are proficient in analyzing tons of incoming data from across multiple platforms. In fact, customer interactions are not only from the website or social media alone. It can come from online communities, surveys, feedback forms, forums, comment sections, and several other sources. For a manual employee or employees to make sense of this data, categorize it based on priority and respond to it on time will be extremely challenging. It requires efficient scraping from all available channels, understanding the priority of requirements, and then taking the next best action. This can be done with the help of intelligent chatbots or virtual assistants. Chatbots are capable of generating meaningful insights from these data and therefore can help employees react to important conversations promptly. This can significantly reduce the manual time needed to evaluate all the data and can also increase business efficiency. 

2. Proactively enhanced network resilience 

Let’s say an organization has enough resources to address customer challenges promptly and does not need the assistance of a chatbot. As more and more employees are connected over a network, this tremendously increases network interruption and causes outages.  Such interruptions can delay workforce management and can have a considerable impact on other business’ areas’. These types of an outage and expanded network usages are mostly seen in call centers that don’t proactively allocate network connectivity. By using chatbot development services with advanced analytics, companies can not only automate customer interactions but can also run simulations that predict network capabilities and resiliency. Call centers and similar enterprises that interact with a large number of customers per day can identify and prioritize a set of specific actions. These actions can considerably reduce the recovery time, customize depending on which sites or queues are affected, etc.

3. Improved service-to-sales conversion 

To truly improve customer services, chatbots should not only be capable of increasing efficiency and reducing costs but also proactively unlock new revenue opportunities. An advanced AI chatbot can unlock several unseen factors about a customer or website visitor. They can provide better website insights and analytics such as user demographics, behavioral profiles, and preferences based on purchase history. They can also monitor real-time website users, ask questions and predict the next product the customer is most likely to buy. Sentiment analysis algorithms can help identify a customer that is potentially regretting a purchase he or she made, the bot can initiate a hassle-free return or cancellation process. All this will not only lead to better sales but will significantly improve customer satisfaction even if he/she found the product not up to the mark. 

Originally posted on ThinkPalm Website

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