How can chatbots contribute in transactional enquiries?
Chatbots that are transactional in nature are different from other bots. They can do a single task really well but find it difficult to provide information or do other tasks that are not related to the primary task.
This doesn’t mean transactional chatbots are not intelligent. They are not like the automated telephones of yesterday that make their users go through a predetermined path of conversation. Instead, they focus on making the customer experience easy and convenient by addressing one specific purpose at a time.
With the help of a transactional chatbot, customers would have the ability to make quick transactions by adhering to contextual conversation. It is an efficient way to conduct similar actions like repeat purchases. (For Eg. A popular fast-food delivery chain can use a transactional chatbot by allowing the customers to order food of their choice with the help of an emoji. In this use case, the customers have the ability to use the services of a transactional chatbot to do the work for them rather than going through the tedious steps themselves.)
What is a transactional bot?
In order to accomplish a predetermined task, a transactional chatbot can be used instead of a human agent if the task is a mundane or repetitive one. Transactional chatbots work best when customers ask them questions that are contextual in nature with the conversation that they are programmed to understand.
Conversational chatbots, Information chatbots are some of the names of chatbots that are transactional in nature. Transactional chatbots are not similar to regular chatbots because their main duty is to provide a fast and efficient experience to the customers who interact with them for the predetermined purpose that they are programmed for. Sometimes websites or mobile applications lead to complicated interfaces, which can slow down the response time, therefore it is very important to use optimised transactional chatbot to carry out specific tasks that are monotonous in nature and do not require human intervention.
Informative Chatbots are well known to provide the users with boring static answers again and again, but Transactional Chatbots can provide dynamic relevant answers due to being connected to an external server/platform. The data provided on the external server gives them the ability to give dynamic impactful answers to their users.
How does a transactional chatbot work?
Just because a transactional chatbot is created to perform a specific task, that does not mean it is limited or basic in nature. A transactional chatbot can be quite clever and can possess the ability to comprehend natural language with the help of relevant technology.
NLP (Natural Language Processing) provides transactional chatbots to be better at certain tasks than traditional basic chatbots.
Implementation of Natural Language Processing gives traditional chatbots the ability to understand the queries asked by the users and provide them with relevant answers by choosing between many possible responses.
A transactional chatbot can go live within a few days because they have the capability to accumulate large amounts of semantic knowledge.
What are transactional chatbot use cases?
E-commerce: A transactional chatbot can be used to update or cancel an order placed by the user. It can also be used to help users with filtering items and getting the product that they are looking for.
Banking: Monotonous simple tasks such as confirmation of transfers, identity verification blocking stolen cards, etc. Which would traditionally be handled by a human agent can now be handled very efficiently by a transactional chatbot.
Insurance: A transactional chatbot can be used in the insurance industry to give customers the ability to download forms, certificates, etc. Some transactional chatbots even have the ability to generate leads and convert potential customers. For eg., If the insurance quotation provided by the transactional chatbot is meeting the budget and requirements of the prospect, then they can carry out all the necessary documentation within the platform itself.