Bot platform – the right choice for building chatbots

About Event

People around the world have embraced bots and according to Mindshare, 63% are willing to communicate this way with various businesses and brands. Building intelligent bots has become necessary for enterprises as part of their marketing campaigns. Only a good bot platform will allow building bots which naturally interacts with users. A bot platform should be intuitive to use and allow for easy customization.

There has been a constant war between frameworks and platforms when it comes to building good bots, and enterprises are having hard time understanding the differences. In this two-hour meetup we will talk about the pros and cons of frameworks and why a bot platform is the need of the hour. We would also highlight the factors that need to be considered while moving forward with platform implementation including technology stack, deployment environment and more.

Meet us at the event and learn more about the benefits of implementing a bot platform – as a transformational change in your business.

Agenda

• Introduction to bots
• Platform vs framework
• Why bot platform
• Bot platform
  • -  Features
  • -  Solution architecture
• Bot Platform vs Custom built bots
• Demo
• Q & A

Questions & Answers

The following are the answers to the questions that were asked during the event.

Question 1: Is it possible to integrate your chatbot platform with an inventory management system?

Answer 1: Yes, this is possible.

Question 2: How are neural networks connected to a chatbot?

Answer 2: Although this is a very technical concept, we will try to explain this in a non-technical manner. The main purpose of the chatbot is to recognize the input it receives from the user and determine the best reply to the query or statement typed by the user. The reply that it gives should -

(1) Either answer the question asked by the user
(2) Give out relevant information to the user
(3) Ask follow-up questions if required, or
(4) Keep talking in a way that mimics a human conversation

The chatbot should be capable of understanding the intent behind a user’s message, decide on what kind of response to give and make sure that the response it gives meets the grammar rules and lexicon of the language in which it is replying. However, most of the chatbots in the market today are unable to understand our intentions or keep sending us incorrect information and can be quite infuriating to deal with overall.

This is where deep learning comes in. It is capable of accepting text typed by the user; analyzing it and can also rank it for future reference. In the end, it gives the appropriate answer via services.

Question 3: What types of reports can be generated out of the data?

Answer 3: Using Microsoft’s AppInsights and Bot analytics feature, we can derive the following reports:

- Messages/user count
- Retention - % of users who messaged again (in the last 10 days)
- Users per channel
- Messages per channel

Custom Reporting: If we have control over the code, we can generate various other custom reports/matrix out of the data that we have as well.

Question 4: How sentiment analysis is useful in analyzing a chatbot?

Answer 4: Sentiment analysis can be useful in a number of ways. Here are a few questions that a chatbot can help you answer.

• How satisfied are the customers with your product?
• How well are you treating your customers after the sale?
• How can you improve your overall process?
• What are the expectations of your customers towards your company?
• What is the future demand of the product?

Question 5: Which machine learning algorithm is useful in building chatbots?

Answer 5: There are many machine learning algorithms available in the market and the one you choose to use should be based on your business need. The available algorithms cannot be implemented as they are since they need to be modified based on your requirements.