Using Chatbots to increasing customer engagement


Why does a retail business need a chatbot

Chatbot is a software program that resembles a human in the ability to reply to queries raised towards it. Their applications can include customer service, product enquiry, personal assistant etc. They can serve as a first line of communication with customers. Having an automated customer support system allows the business to quickly respond to customers. Easier queries can be served by a chatbot while the harder queries can be handled by human support staff. By having a semi-automated approach to customer service using chatbots, businesses can aim to lower the cost of customer support operations.

Since chatbots are electronic in nature, they can address the support needs of a business even during public holidays. The ability to be in touch with customers 24 / 7 across 365 days gives a sense of confidence to the customers that their needs will be addressed at any time. Also the electronic nature of the chatbot helps in blurring the differences due to time zone. Earlier businesses used to set up dedicated support teams to address the operating hours of each time zone. By configuring a chatbot as a virtual assistant for the customers visiting a business website, the business can give a more friendly feel for the customer. The applications of chatbots are quite wide and it is a matter of imagination of the business stakeholder to conjure a use case for this technology.

How to build a chatbot

Chatbot that is capable of general conversations is available from major cloud vendors like Microsoft Azure, AWS and Google GCP. When adding a chatbot service to your business, the first question to ask is, where will you use the chatbot. Is it for customer service or product enquiry or for personal assistance or a combination of some of this. After defining the chatbot strategy for the business, the business stakeholder will have to identify the sequence of interactions that a potential customer will take in using the chatbot. Some tools like Dialogflow from Google, provide a low code approach to define the interaction sequence. One can think of the interaction sequence as a flow chart for the customer's dialogue sequence. The service from Azure, AWS or GCP allows the chatbot to be hosted on the website or the application of the business.

What are the best practices in chatbot development

Chatbots are software programs built to resemble a human response in terms of the quality of the response. The emotional cues and bonds that exist in natural human interaction will not be replicated in chatbots. Its best to use chatbots in scenarios where the response sought is factual in nature. An example for a factual query of information from a data store, is the case of an incident retrieval. Say for example the customer has registered a complaint about his service and would like to get an update about his complaint, the chatbot can do a good job at this. For instances where a more human and personal connection is required, it is best not to use a chatbot.


By the nature of the construct of a chatbot, it is possible that chatbot fails in cases where its training is incomplete or partial. In scenarios where a strong retrieval of information is not possible, the chatbots should be programmed to return a default value that makes it clear to the human user that the chatbot was unable to retrieve the requested information.

Ethical AI practices would require that the user know that he is interacting with a chatbot and not a real human user. So chatbot developers need to heed to this requirement for ethical use of AI. One of the best practices would be to call out explicitly that it's the chatbot that is interacting with the user during the start of the dialogue exchange process.

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