Computer Vision Basics for Customer Experience (CX) Professionals
Course Overview:
This course equips Customer Experience (CX) and Customer Service Management (CSM) professionals with the fundamentals of Computer Vision (CV). You'll explore how CV technology "sees" the world and its potential applications to enhance customer interactions and experiences within your organization.
Learning Objectives:
Explain the core concepts of Computer Vision (CV) and its role in enhancing customer experiences.
Understand different image processing techniques used in CV applications.
Identify various CV tasks relevant to CX, such as object detection, image classification, and facial recognition.
Explore potential use cases for CV in CX functions like visual search, product recommendations, and automated image analysis for customer support.
Evaluate the limitations and ethical considerations surrounding CV implementation in customer interactions.
Course Highlights:
1. Unveiling the Power of Computer Vision:
Introduction to Computer Vision: Understanding how machines "see" and interpret visual information.
Demystifying Image Processing: Exploring fundamental techniques for preparing and analyzing images in CV applications.
Machine Learning for CV: Learning how machine learning algorithms power CV tasks like object detection and image classification.
Case Study: Utilizing CV for visual search in an e-commerce platform to improve customer product discovery experiences.
Hands-on Session: Working with basic image processing tools to explore image filtering and feature extraction.
2. Exploring CV Applications for CX:
Object Detection in Action: Understanding how CV can detect and identify objects in images and videos, relevant for tasks like product identification or anomaly detection.
Image Classification for CX: Exploring how CV can categorize images into different classes, with applications for content moderation or sentiment analysis from customer photos.
Beyond Images: Introducing applications of CV with video data, including customer behavior analysis in physical stores or video chat optimization.
Guest Speaker Session: Inviting a CX professional who has implemented CV technology in their work to share their experience and insights.
Group Discussion: Brainstorming potential applications of CV for specific CX challenges within your department.
3. Enhancing CX with Advanced CV Techniques:
Facial Recognition for Customer Service: Examining the potential and ethical considerations of using facial recognition for personalized service or security purposes.
Augmented Reality (AR) for Customer Engagement: Exploring how AR powered by CV can create interactive and immersive experiences for customers.
Automating Visual Tasks for CX: Understanding how CV can automate tasks like image quality checks or damage detection in customer-supplied photos.
Interactive Workshop: Experimenting with a pre-trained CV model for object detection or image classification on a sample customer image dataset.
Project Planning: Developing a project plan outlining how you can leverage CV for a specific CX challenge in your role.
4. The Future of CV and Responsible AI in CX:
Emerging Trends in Computer Vision: Exploring advancements in CV technology and its future applications in customer experience.
Limitations and Ethical Considerations: Addressing potential biases in CV algorithms and ensuring fair treatment of customers.
Responsible AI for CX with CV: Developing strategies for responsible implementation of CV technology in CX initiatives.
Course Wrap-up & Project Presentations: Teams present their project plans, outlining the chosen CV application for CX, ethical considerations, and potential impact.
Resource Sharing: Discussing best practices and ongoing learning opportunities for staying up-to-date with CV advancements in the CX field.
Prerequisites:
Strong understanding of linear algebra and calculus
Proficiency in programming with Python and libraries such as NumPy and Matplotlib
Familiarity with basic machine learning concepts and techniques