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How would you choose an AI chatbot for your Organization?

Apr 20 2021 , Navaniranjan N

To give a gist, AI chatbots are bots built on Artificial Intelligence software that can make conversations with humans and hence these are also termed as Conversational bots. The more sophisticated the bots, the better the orientation in terms of understanding and responding to the customers. Few AI-powered chatbots can make initial conversation and few other bots can also make Sales conversion discussion. Depending upon the needs of an organization they can choose the type of Chatbots that would best suit their customer experience goals.

#Tip –While going for AI chatbots, the main intent should be to provide better customer experience which in turn will provide better results in terms of lead generation or sales conversation.

Moving along, we will find out what is the best way to use an AI-based Chatbot for better customer service/experience. At iOpex Technologies, we have developed a tool named Opexwise which will enable companies to make the right decision for choosing their chatbots at a relatively lesser cost than others. This might sound like a sales pitch but will explain in detail to help you understand why this can be considered as one of the best AI chatbot systems.

Data-driven decision making: Though there are many use cases of AI Chatbots, the two most important use cases are providing round the clock customer support and personalized communications with the customers. When a company is managed to build a chatbot that can take care of these two use cases at top priority then there are many associated benefits like improving the response rate, streamlining the shopping experience, cost benefits etc.

This is where most of the organizations fail to understand the right way to build a chatbot and this is where Opexwise comes into the picture, this tool helps to produce a heat map from the unstructured data provided by which the desired chatbot can be created addressing the most important and critical needs of an organization. For example, A bunch of tickets provided to this tool will segregate the most frequently raised tickets and form a pattern of answers which are most relevant to the query, in this way the unstructured information is converted into a structured one by this tool.

For example, in an organization, if the frequent queries are related to payments then this tool will highlight that particular query and based on that the best possible replies/answers can be fed to the AI chatbot to respond to customers.

The above screenshot shows one of the bubble chat illustrations provided for one of our clients in their IT services. The top red portion is the most critical areas of queries - the bigger the bubble the more it needs attention, the AI-based chatbot is built on the above outcome so that the most critical queries are addressed likewise the priority is measured and deployed into the chatbot system.


The below features will allow an organization to build the best AI-powered Chatbot in the most cost-effective way to enhance your customer service or experience.

  • Functions as a framework/prototype with data mining capabilities rather than Hadoop setup.
  • Uses artificial intelligence to maintain a knowledge base derived from the skills and experience of SMEs.
  • Enables resolution of complex issues by providing a technical analysis of incident occurrences, their causes, and suggestions for incident avoidance in the future.
  • Presents the on-the-floor scenario to managers with customizable dashboards which highlight favorable & undesirable events by continuously updating business-critical metrics.
  • Helps you sift through voluminous incident logs & unearth areas of improvement by allowing you to add/remove dimensions for comparing various factors in real-time.
  • Being agile, the tool facilitates SQL-like selection for choosing or eliminating multiple criteria and generates graphical reports on the fly in the desired format.
  • Correlation Engine and auto tagger functionality to segregate and optimize data at various levels.
  • Leverages on its Distance Vector Correlation engine to rationalize spend and resources.
  • Eliminates the challenge of “focus on process and operations only, without considering people efficiency”, by giving an integrated view of people productivity as a live dashboard.

So, the search for building the best AI chatbot ends here, for further queries you can contact us by clicking the Get in touch button.

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