In Part 1 of this blog series, we learned about Predictive Analytics and why it is booming, covered the risks of False Positives, bias creeping in, problems caused in training a model, while understanding the algorithms used in predictive analytics and the use of crowdsourcing technique.

Prediction is booming. Nowadays, the prediction is done by machines using artificial intelligence and machine learning. Classified under the broad area of business analytics, predictive analytics has the power of answering the question as to what is likely to happen. Here historical data is combined with rules, algorithms and occasionally external data to determine the probable future outcome of an event or the likelihood of a situation occurring. It is widely used in commerce, manufacturing, healthcare, government and law enforcement.

In the Part 1 of the Chatbot Testing blog, we introduced an overview on Chatbots and why it has become pervasive in our lives today. We also learned about the advantages and disadvantages of using a Chatbot in businesses.

Further, we learned about Chatbot testing via Intent Testing, BOT’s way of Introduction, Conversational Flow, Accuracy, Natural Language Processing Friendliness, Latency (Speed) of the BOT, among other aspects of testing a BOT.

Chatbots are the new conversational agents that are made available through a website or any other interface to assist customers. As chatbots use the natural method of human interaction – a dialogue, it is true that chatbots are supplanting the customer interaction space traditionally served by customer service representatives.