Intro Building an SMS chatbot on Twilio tied to Zendesk for ticketing using Python and NLTK
Автор: Jare Dunn
Загружено: 2020-08-28
Просмотров: 52
Описание:
Building an SMS chatbot on Twilio tied to Zendesk for ticketing using Python and NLTK
• Building an SMS chatbot on Twilio tied to ...
Building an SMS chatbot on Twilio tied to Zendesk for ticketing using Python and NLTK
Do you have a business who's customer service needs could be met by intelligent chatbot? We've all dealt with them - let's see how to create one! What's more is that we'll focus on creating a chatbot that notices trends or sentiment in language, in order to triage, tag, escalate support tickets (thru Zendesk) better.
Overview
Introduction
Do you have a business who's customer service needs could be met by an intelligent chatbot? We've all dealt with them - let's see how to create one! What's more is that we'll focus on creating a chatbot that notices trends or sentiment in language, to triage, tag, escalate support tickets (trough Zendesk) better.
What are the requirements?
Knowledge of Python
Interest in NLTK
Knowledge of APIs/SDKs
What is the target audience?
People looking to extend or build on Twilio, Zendesk
Project Outline
The project outline explains what you will learn in each session
Part 1: Setting up Project Environment
1. Python 2. NLTK + Vader lexicon 3. Twilio 4. Zendesk
Part 2: Figuring out Zendesk + Twilio integration
1. Does my Twilio number work? 2. Testing Twilio - 'To:' number 3. Testing Twilio - Zendesk ticket 4. Are we able to tag or assign via Python for Zendesk?
Part 3: Creating, Updating, Replying To Tickets via SMS
1. We'll learn how to have a conversation with our bot via SMS, that's tracked in Zendesk!
Part 4: Installing and Using NLTK and Vader Lexicon for Sentiment Analysis
1. Set it up 2. Test it 3. Pull random text from Reddit to see how effective it is 4. Connect to Google Sheets API for prettier, collaborative output
Part 5: Running Sentiment Analysis on SMSs Recieved and Tagging the Zendesk Tickets with Severity
1. We teach our bot how to have smarter replies and tracking
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