Retail chatbot interactions can exceed 22 billion by 2023(Juniper Research). Such systems are based on the NLP, which makes them work naturally to serve the customers. It reduces the need for hiring customer care executives, cutting costs by 25 per cent.
Voice has always been the most dominating channel for customer care as it accounts for over 80 per cent of the interactions, and many companies use voice assistants to handle client queries.
Robots as Assistants
Conversational robots are voice assistants who can process data to gather information. It can send messages in written or verbal format. It is often installed as a customer representative and is useful for businesses as it cuts hiring costs and provides safe, reliable information based on facts.
Many websites that initially involved human representatives in attending to the visitors' queries are using it. Facebook bots are the most common based on 100 per cent automated service. Such services can be provided by software like botsify.
Enterprises can use the responsive voice system, which includes messaging apps, phoning devices and other assistants that can listen to the conversation, gather the keywords /text content, and search for information to deliver desired operation or data.
The capabilities of such systems require natural language processing, conversation management, intent prediction and response generation.
Robotic process automation is the system that can get into the difficult communication zones of the firms to help customers.
It can be installed back office where the applications related to operations, finance, IT and other departments can be accessed to locate the exact information required to process.
RPA can be used to serve virtual assistants and humans. These can access data across multiple systems to get to a decision and effectively execute repeatable tasks. It can work in batch modes and help to reduce the turn- around time for individual operations.
The customer calls can be rescheduled or sorted based on setting up priority. These systems mimic human workers, and their processing loads can be distributed across machines.
Several firms are using such features to expand in other areas of automation, as the machines help employees get extra time for generating and implementing new ideas and strategies. In addition, it increases the amount of information exchanged daily between the departments and managers.
However, it involves several risks like high implementation costs, difficulty in integration, limited skills and difficulty in scaling applications.
In addition, such implementations require all systems to be automated and optical character recognition and natural language processing applications to handle different processes. Other risks include data privacy and cybersecurity problems related to such implementations.
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