Data science chatbot

Chatbots, big data and the future of customer service

The rise and development of big data has paved the way for an incredible array of chatbots in customer service. Here's what to know.

Big data is changing the direction of customer service. Machine learning tools have led to the development of chatbots. They rely on big data to better serve customers.

How are chatbots changing the future of the customer service industry and what role does big data play in managing them?

Big data Leads to the deployment of more sophisticated chatbots

BI-kring published an article about the use of chatbots in HR about a month ago. This article goes deeper into the role of big data when discussing chatbots.

The following terms are more popular than ever: 'chatbot', 'automated customer service', 'virtual advisor'. Some know more, others less about process automation. One thing is for sure: if you want to sell more on the internet, handle more customers, save on personnel costs, you certainly need a chatbot. A chatbot is a conversational system that was created to stimulate intelligent conversation between a human and an automaton.

Chatbots rely on machine learning and other sophisticated data technology. They are constantly collecting new data from their interactions with customers to offer a better experience.

But how commonly used are chatbots? An estimated 67% of consumers around the world have communicated with one. That figure is going to rise sharply in the near future. In 2020, over 85% of all customer service interactions will involve chatbots.

A chatbot makes it possible to automate customer service in various communication channels, for example on a website, chat, in social media or via SMS. In practice, a customer does not have to wait for hours to receive a reply from the customer service department, a bot will provide an answer within a few seconds.

According to requirements, a chatbot may assume the role of a virtual advisor or assistant. For questions where a real person has to become involved, in analyzing the received enquiries bots can not only identify what issue the given customer is addressing but also to automatically send it to the correct person or department. Machine learning tools make it easier to determine when a human advisor is needed.

Bots supported by associative memory algorithms understand the entire content even if the interlocutor made a mistake or a typo. Machine learning makes it easier for them to decipher contextual meanings by interpreting these mistakes.

Response speed and 24/7 assistance are very important when it comes to customer service, as late afternoons and evenings are times of day when online shops experience increased traffic. If a customer cannot obtain information about a given product right there and then, it is possible that they will just abandon their basket and not come shop at that store again. Any business would want to prevent that a customer journey towards their product takes a turn the other way, especially if it's due to a lack of appropriate support.

Online store operators, trying to stay a step ahead of the competition, often decide to implement a state-of-the-art solution, which makes the store significantly more attractive and provides a number of new opportunities delivered by chatbots. Often, following the application of such a solution, website visits increase significantly. This translates into more sales of products or services.

We are not only seeing increased interest in the e-commerce industry, chatbots are successfully used in the banking industry as well. Bank Handlowy and Credit Agricole use bots to handle loyalty programmes or as assistants when paying bills.

What else can a chatbot do?

Big data has made it easier for chatbots to function. Here are some of the benefits that they offer:

  • Send reminders of upcoming payment deadlines.
  • Send account balance information.
  • Pass on important information and announcements from the bank.
  • Offer personalised products and services.
  • Bots are also increasingly more often used to interact with customers wishing to order meals, taxis, book tickets, accommodation, select holiday packages at travel agents, etc.

The insurance industry is yet another area where chatbots are very useful. Since insurance companies are already investing heavily in big data and machine learning to handle actuarial analyses, it is easy for them to extend their knowledge of data technology to chatbots.

The use of Facebook Messenger chatbots during staff recruitment may be surprising for many people.

Chatbots are frequently used in the health service as well, helping to find the right facilities, arrange a visit, select the correct doctor and also find opinions about them or simply provide information on given drugs or supplements.

As today every young person uses a smartphone, social media and messaging platforms for a whole range of everyday tasks like shopping, acquiring information, sorting out official matters, paying bills etc., the use of chatbots is slowly becoming synonymous with contemporary and professional customer service. A service available 24/7, often geared to satisfy given needs and preferences.

Have you always dreamed of employees who do not get sick, do not take vacations and do not sleep? Try using a chatbot.

Big data has led to fantastic developments with chatbots

Big data is continually changing the direction of customer service. Chatbots rely heavily on the technology behind big data. New advances in machine learning and other data technology should lead to even more useful chatbots in the future.

Author: Ryan Kh

Source: SmartDataCollective