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AI Chatbot
November 6, 2019
Alex G. Lee (geunholee@gmail.com)
Contents
-AI Chatbot for Customer Experience
-AI Chatbot Evolution
-AI Chatbot Use Cases: Travel Industry
-AI Chatbot Use Cases: Food & Beverage Industry
-AI Chatbot Use Cases: Banking Industry
-AI Chatbot Use Cases: Healthcare Industry
-AI Chatbot for Retail Services Innovation
-AI Chatbot Use Cases: Retail & Fashion Industry
-Emotion AI
-Replika: An Emotion AI Chatbot
-Woebot: Robot Therapist
-Emotion AI Chatbot Prototype Demo
-E-Commerce Integration Demo
-AI Chatbot Sentiment Analysis + Big Data Analytics
-AI Chatbot Sentiment Analysis + Big Data Analytics Demo
AI Chatbot for Customer Experience
Chatbots are AI-based conversation agents that are being used in many
different customer-engagement scenarios for optimal customer
experience. Optimal customer experience is achieved when a business
remembers a customer and treats them with attention, respect and
consideration.
Chatbots are designed to simulate human interactions and provide
immediate, personalized responses 24*7.
Chatbots interact directly with customers to provide information, process
support inquiries, or solve simple problems.
Chatbots vary in technical complexity, ranging from being simple scripted
experiences to leveraging state-of-the-art natural language processing
(NLP) and understanding (NLU) techniques.
AI Chatbot Evolution
AI Chatbot Evolution: Level 2 Demo
AI Chatbot Use Cases: Travel Industry
Automating Booking Request for Travel Agency via Chatbot.
Source: BLASTASIA Inc.(https://www.youtube.com/watch?v=A8TVLIE1A9k)
AI Chatbot Use Cases: Food & Beverage Industry
A chatbot based reservation system for Facebook pages is a better way to have
a conversation with your customers.
Source: ADEO WEB (https://www.youtube.com/watch?v=Y84M_7AiJto)
AI Chatbot Use Cases: Banking Industry
Capital One SMS chatbot checks balances and recent payments, looks up
account info (e.g. routing number), transfers money between accounts.
Source: Capital One (https://www.youtube.com/watch?v=jvyHcjZoGJk)
AI Chatbot Use Cases: Healthcare Industry I
Healthcare chatbot helps patients obtain information they require without
having to interact with agents. It uses learned and directed dialog interactions
from historical data to address patient queries, or where necessary, handover to
agents for further assistance.
Source: Avaya (https://www.youtube.com/watch?v=nvOJQ4JttP0)
AI Chatbot Use Cases: Healthcare Industry II
AI Chatbot for Retail Services Innovation
Provide personalized customer experience
Provide customer’s life-style advisor
Increase understanding each customer’s needs & wants
Real time CRM
Customer royalty maximization
Target customer marketing
Maximize customer recognition
Mobile-Online-Offline shopping integration
AI Chatbot Use Cases: Retail & Fashion Industry I
Experimenting for the best use cases to enhance customer experience
Source: Trendbrew (https://www.youtube.com/watch?v=74JEJlpX9w4)
AI Chatbot Use Cases: Retail & Fashion Industry II
Clothing retailer Uniqlo chatbot enables shoppers can search for items, get
recommendations for outfits for different occasions and voice or text chat with
the app itself for more specific information.
Source: Uniqlo (https://adage.com/creativity/work/uniqlo-iq-demo/55129?)
AI Chatbot Use Cases: Retail & Fashion Industry III
Lotte shopping advisor chatbot Charlotte
Source: IBM Korea (https://www.youtube.com/watch?v=VuPBczD2AUg)
Reference: https://blog.naver.com/ibm_korea/221504531163
AI Chatbot Use Cases: Retail & Fashion Industry IV
1-800-Flowers is the largest gifting retailer in the US, $1.2 billion in sales a year.
Gwyn is a personal gift concierge chatbot.
Source: ChatBottle (https://www.youtube.com/watch?v=5WfS93Pgibg)
AI Chatbot for Retail Additional Use Cases I
Tommy Hilfiger: American apparel brand
On opening the conversation on Facebook Messenger, the chatbot greets the
user, then instantly introduces the consumer to the collection and gives them
three options for the conversation: style advice, browsing, or a behind-the-
scenes look at the latest fashion show. The bot reacts to keywords typed by
customers and offers solutions. Customers are presented with an opportunity to
browse by either looks or categories, such as accessories or bags.
Burberry: luxury clothing brand
By sharing their location on Facebook Messenger, users can be informed
where their nearest Burberry store is. The chatbot also introduces customers to
the brand’s latest collection of bags; by clicking the ‘Discover More’ option, the
chatbot lets users browse the collection, get to know more about the
craftsmanship, or find out how to style a bag with Burberry’s apparel and
accessories. Burberry’s chatbot offers pre-made suggestions that guide users
through their shopping experience.
Source: https://www.retail-insight-network.com/features/chatbots-in-retail-ai-
experience/
AI Chatbot Retail Additional Use Cases II
Sephora: France-headquartered international beauty stores chain
The first time a shopper starts a conversation with the chatbot they are invited
to take part in a short quiz that helps the bot learn more about them. Users can
then ask for tips or reviews on specific types of product or application. Each of
these comes with product recommendations that the customer can shop. The
experience aims to mimic the way the shopper might chat with their friends
about products and advice.
Whole Foods: An Amazon company-US-based healthy food supermarket
Customers can enter a zip code or an address, or simply share their location to
get results immediately. The grocer is using the Facebook Messenger chatbot
to make finding the ingredients people want easier. Shoppers can use the
chatbot to ask for recipes and to find where products are positioned in the store.
For those with special dietary restrictions, the chatbot can also consider those
and help them find foods and meals that leave a particular ingredient out. It
aims to improve customers experience in store, not just online.
Source: https://www.retail-insight-network.com/features/chatbots-in-retail-ai-
experience/
Emotion AI Introduction
Emotional Intelligence enhances AI's ability to understand emotional
input, and continually adapt to and learn from information to provide
human-like responses in real time.
Emotion AI, or affective computing, trains AI to recognize, interpret, and
respond to human emotion in text, voice, facial expressions, or body
language.
As customers increased their level of emotional connectedness with a
brand/product/service, their value increased alongside it. And there was
a massive increase in value when they reached the highest level of
emotional connectedness.
Emotion AI Technology I
Humans use a lot of non-verbal cues, such as facial expressions,
gesture, body language and tone of voice, to communicate their
emotions.
Emotion detection – Face
Emotion AI measures facial expressions of emotion, using any optical
sensor. Emotion AI technology first identifies a human face in real time or
in an image or video. Computer vision algorithms identify key landmarks
on the face – for example, the corners of eyebrows, the tip of nose, the
corners of your mouth. Deep learning algorithms then analyze pixels in
those regions to classify facial expressions. Combinations of these facial
expressions are then mapped to emotions (anger, contempt, disgust,
fear, joy, sadness and surprise).
Emotion AI Technology II
Emotion AI uses a combination of a convolutional neural network (CNN)
and long short-term memory (LSTM) that is capable of recognizing
patterns in sequences of images.
Emotion detection – Speech
Emotion AI analyzes how it is said, observing changes in speech
paralinguistics, tone, loudness, tempo, and voice quality to distinguish
speech events, emotions, and gender.
Multimodal Emotion AI combines analysis of both face and speech as
complementary signals to provide richer insight into the human
expression of emotion.
Emotion AI Technology III
Sentiment Analysis
Sentiment analysis analyzes textual data, such as emails, social media
posts, survey responses, or chat and call logs, for emotional information.
Sentiment analysis can transform subtle nuances in textual data into
accurate insights about a customer’s feelings, needs, and wants.
Sentiment analysis can find out when customers are having a specific
issue with a product, which help to take more focused action in a timely
manner.
Emotion AI Use Case
Emotion AI Use Case
Emotion AI Use Case
Emotion AI Use Case
AI Innovation Frontline
Emotion AI Use Case
Replika: An Emotion AI Chatbot
Sentiment Analysis
Sentiment analysis analyzes textual data, such as emails, social media
posts, survey responses, or chat and call logs, for emotional information.
Sentiment analysis can transform subtle nuances in textual data into
accurate insights about a customer’s feelings, needs, and wants.
Sentiment analysis can find out when customers are having a specific
issue with a product, which help to take more focused action in a timely
manner.
Replika: An Emotion AI Chatbot
Replika learns to imitate the user through the emotional conversation.
Source: Bruno Coelho (https://www.youtube.com/watch?v=TyUPHbU3TQ8)
Woebot: Robot Therapist
Woebot is an emotion AI chatbot who can help you track your mood and
manage your feelings. Source: TWiT Netcast Network
(https://www.youtube.com/watch?v=Js_E4ap_zOg)
Emotion AI Chatbot Prototype Demo
Emotion AI Chatbot Prototype Demo
Emotion AI Chatbot Prototype Demo
E-Commerce Integration Demo
AI Chatbot Sentiment Analysis + Big Data Analytics
AI Chatbot Sentiment Analysis + Big Data Analytics Demo
Thank you!
Xanadu Big Data, LLC
Elamachain USA, LLC

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AI Chatbot

  • 1. AI Chatbot November 6, 2019 Alex G. Lee (geunholee@gmail.com)
  • 2. Contents -AI Chatbot for Customer Experience -AI Chatbot Evolution -AI Chatbot Use Cases: Travel Industry -AI Chatbot Use Cases: Food & Beverage Industry -AI Chatbot Use Cases: Banking Industry -AI Chatbot Use Cases: Healthcare Industry -AI Chatbot for Retail Services Innovation -AI Chatbot Use Cases: Retail & Fashion Industry -Emotion AI -Replika: An Emotion AI Chatbot -Woebot: Robot Therapist -Emotion AI Chatbot Prototype Demo -E-Commerce Integration Demo -AI Chatbot Sentiment Analysis + Big Data Analytics -AI Chatbot Sentiment Analysis + Big Data Analytics Demo
  • 3. AI Chatbot for Customer Experience Chatbots are AI-based conversation agents that are being used in many different customer-engagement scenarios for optimal customer experience. Optimal customer experience is achieved when a business remembers a customer and treats them with attention, respect and consideration. Chatbots are designed to simulate human interactions and provide immediate, personalized responses 24*7. Chatbots interact directly with customers to provide information, process support inquiries, or solve simple problems. Chatbots vary in technical complexity, ranging from being simple scripted experiences to leveraging state-of-the-art natural language processing (NLP) and understanding (NLU) techniques.
  • 5. AI Chatbot Evolution: Level 2 Demo
  • 6. AI Chatbot Use Cases: Travel Industry Automating Booking Request for Travel Agency via Chatbot. Source: BLASTASIA Inc.(https://www.youtube.com/watch?v=A8TVLIE1A9k)
  • 7. AI Chatbot Use Cases: Food & Beverage Industry A chatbot based reservation system for Facebook pages is a better way to have a conversation with your customers. Source: ADEO WEB (https://www.youtube.com/watch?v=Y84M_7AiJto)
  • 8. AI Chatbot Use Cases: Banking Industry Capital One SMS chatbot checks balances and recent payments, looks up account info (e.g. routing number), transfers money between accounts. Source: Capital One (https://www.youtube.com/watch?v=jvyHcjZoGJk)
  • 9. AI Chatbot Use Cases: Healthcare Industry I Healthcare chatbot helps patients obtain information they require without having to interact with agents. It uses learned and directed dialog interactions from historical data to address patient queries, or where necessary, handover to agents for further assistance. Source: Avaya (https://www.youtube.com/watch?v=nvOJQ4JttP0)
  • 10. AI Chatbot Use Cases: Healthcare Industry II
  • 11. AI Chatbot for Retail Services Innovation Provide personalized customer experience Provide customer’s life-style advisor Increase understanding each customer’s needs & wants Real time CRM Customer royalty maximization Target customer marketing Maximize customer recognition Mobile-Online-Offline shopping integration
  • 12. AI Chatbot Use Cases: Retail & Fashion Industry I Experimenting for the best use cases to enhance customer experience Source: Trendbrew (https://www.youtube.com/watch?v=74JEJlpX9w4)
  • 13. AI Chatbot Use Cases: Retail & Fashion Industry II Clothing retailer Uniqlo chatbot enables shoppers can search for items, get recommendations for outfits for different occasions and voice or text chat with the app itself for more specific information. Source: Uniqlo (https://adage.com/creativity/work/uniqlo-iq-demo/55129?)
  • 14. AI Chatbot Use Cases: Retail & Fashion Industry III Lotte shopping advisor chatbot Charlotte Source: IBM Korea (https://www.youtube.com/watch?v=VuPBczD2AUg) Reference: https://blog.naver.com/ibm_korea/221504531163
  • 15. AI Chatbot Use Cases: Retail & Fashion Industry IV 1-800-Flowers is the largest gifting retailer in the US, $1.2 billion in sales a year. Gwyn is a personal gift concierge chatbot. Source: ChatBottle (https://www.youtube.com/watch?v=5WfS93Pgibg)
  • 16. AI Chatbot for Retail Additional Use Cases I Tommy Hilfiger: American apparel brand On opening the conversation on Facebook Messenger, the chatbot greets the user, then instantly introduces the consumer to the collection and gives them three options for the conversation: style advice, browsing, or a behind-the- scenes look at the latest fashion show. The bot reacts to keywords typed by customers and offers solutions. Customers are presented with an opportunity to browse by either looks or categories, such as accessories or bags. Burberry: luxury clothing brand By sharing their location on Facebook Messenger, users can be informed where their nearest Burberry store is. The chatbot also introduces customers to the brand’s latest collection of bags; by clicking the ‘Discover More’ option, the chatbot lets users browse the collection, get to know more about the craftsmanship, or find out how to style a bag with Burberry’s apparel and accessories. Burberry’s chatbot offers pre-made suggestions that guide users through their shopping experience. Source: https://www.retail-insight-network.com/features/chatbots-in-retail-ai- experience/
  • 17. AI Chatbot Retail Additional Use Cases II Sephora: France-headquartered international beauty stores chain The first time a shopper starts a conversation with the chatbot they are invited to take part in a short quiz that helps the bot learn more about them. Users can then ask for tips or reviews on specific types of product or application. Each of these comes with product recommendations that the customer can shop. The experience aims to mimic the way the shopper might chat with their friends about products and advice. Whole Foods: An Amazon company-US-based healthy food supermarket Customers can enter a zip code or an address, or simply share their location to get results immediately. The grocer is using the Facebook Messenger chatbot to make finding the ingredients people want easier. Shoppers can use the chatbot to ask for recipes and to find where products are positioned in the store. For those with special dietary restrictions, the chatbot can also consider those and help them find foods and meals that leave a particular ingredient out. It aims to improve customers experience in store, not just online. Source: https://www.retail-insight-network.com/features/chatbots-in-retail-ai- experience/
  • 18. Emotion AI Introduction Emotional Intelligence enhances AI's ability to understand emotional input, and continually adapt to and learn from information to provide human-like responses in real time. Emotion AI, or affective computing, trains AI to recognize, interpret, and respond to human emotion in text, voice, facial expressions, or body language. As customers increased their level of emotional connectedness with a brand/product/service, their value increased alongside it. And there was a massive increase in value when they reached the highest level of emotional connectedness.
  • 19. Emotion AI Technology I Humans use a lot of non-verbal cues, such as facial expressions, gesture, body language and tone of voice, to communicate their emotions. Emotion detection – Face Emotion AI measures facial expressions of emotion, using any optical sensor. Emotion AI technology first identifies a human face in real time or in an image or video. Computer vision algorithms identify key landmarks on the face – for example, the corners of eyebrows, the tip of nose, the corners of your mouth. Deep learning algorithms then analyze pixels in those regions to classify facial expressions. Combinations of these facial expressions are then mapped to emotions (anger, contempt, disgust, fear, joy, sadness and surprise).
  • 20. Emotion AI Technology II Emotion AI uses a combination of a convolutional neural network (CNN) and long short-term memory (LSTM) that is capable of recognizing patterns in sequences of images. Emotion detection – Speech Emotion AI analyzes how it is said, observing changes in speech paralinguistics, tone, loudness, tempo, and voice quality to distinguish speech events, emotions, and gender. Multimodal Emotion AI combines analysis of both face and speech as complementary signals to provide richer insight into the human expression of emotion.
  • 21. Emotion AI Technology III Sentiment Analysis Sentiment analysis analyzes textual data, such as emails, social media posts, survey responses, or chat and call logs, for emotional information. Sentiment analysis can transform subtle nuances in textual data into accurate insights about a customer’s feelings, needs, and wants. Sentiment analysis can find out when customers are having a specific issue with a product, which help to take more focused action in a timely manner.
  • 28. Replika: An Emotion AI Chatbot Sentiment Analysis Sentiment analysis analyzes textual data, such as emails, social media posts, survey responses, or chat and call logs, for emotional information. Sentiment analysis can transform subtle nuances in textual data into accurate insights about a customer’s feelings, needs, and wants. Sentiment analysis can find out when customers are having a specific issue with a product, which help to take more focused action in a timely manner.
  • 29. Replika: An Emotion AI Chatbot Replika learns to imitate the user through the emotional conversation. Source: Bruno Coelho (https://www.youtube.com/watch?v=TyUPHbU3TQ8)
  • 30. Woebot: Robot Therapist Woebot is an emotion AI chatbot who can help you track your mood and manage your feelings. Source: TWiT Netcast Network (https://www.youtube.com/watch?v=Js_E4ap_zOg)
  • 31. Emotion AI Chatbot Prototype Demo
  • 32. Emotion AI Chatbot Prototype Demo
  • 33. Emotion AI Chatbot Prototype Demo
  • 35. AI Chatbot Sentiment Analysis + Big Data Analytics
  • 36. AI Chatbot Sentiment Analysis + Big Data Analytics Demo
  • 37. Thank you! Xanadu Big Data, LLC Elamachain USA, LLC