Questions and Answers
What is the market share value of Himalaya Lip Balm?
25%
What is the estimated size of the Lip Balm category in India?
INR 180 crore
What is the MRP of the regular Lip Balm from Himalaya?
50
Who are the key competitors of Himalaya Lip Balm?
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The product is mainly used during winters to prevent _____ of the lips.
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What is a key benefit of the Himalaya Lip Balm's formulation?
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The regular segment of Lip Balm has a significant opportunity for category penetration.
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What are herbal actives known to provide in Himalaya Lip Balm?
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What is the primary target audience for the Himalaya Lip Balm campaign?
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Which of the following technologies are classified under AI? (Select all that apply)
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What technology does Google Lens utilize for object detection?
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Which AI assistant is NOT mentioned in the content?
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Natural Language Processing is crucial for speech recognition.
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What does Emotion AI recognize and process?
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The system used by PXD diagnoses lung cancer through _____ analysis.
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Which application of AI focuses on personalizing customer experiences in marketing?
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Artificially Intelligent robots perform tasks manually.
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What are the two approaches to the development of AI?
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Match the following AI applications with their examples:
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What is the goal of Reinforcement Learning?
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Study Notes
Campaign Overview
- Campaign Name: Himalaya Lip Balm Activation
- Project Start Date: December 8, 2021
- Launch Date: January 10, 2021
- End Date: February 25, 2021
Market Context
- The lip balm category in India is worth INR 180 crore (Nielsen RMS MAT March 2021).
- Himalaya Wellness holds a leading market share of 25%, valued at INR 45 crore.
- Category underpenetration stands at 9% at All India Urban level.
- Regular segment price is INR 50 and captures significant market opportunity, while the premium segment can enhance value due to higher pricing.
Competitors
- Major competitors include:
- HUL: Market share value of 11%
- Nivea India: Market share value of 14%
- Loreal India: Market share value of 12%
Objectives
- Strengthen brand positioning and improve imagery of Himalaya Lip Balm.
- Enhance relevance by identifying untapped needs while maintaining an ingredient-led narrative.
- Focus on the regular segment, especially during winter months, to increase conversion of non-users to users.
Target Audience
- Primary Audience: Urban females aged 15-24, from NCCS ABC social class.
Consumer Insights
- Seasonal product usage primarily during winter due to dry lips.
- Lip balms address functional needs (moisturization) and emotional benefits (confidence, sensory experience).
Key Campaign Asks
- Explore and identify a unique need-state for enhanced product relevance by focusing on both functional and emotional benefits.
- Address common misconceptions to convert non-users:
- Concerns about lip darkening
- Perception of an artificial look
- Fears of harmful chemicals
- Beliefs about inadequate long-lasting moisturization
- Assumptions regarding frequent reapplication
- Misunderstandings about the absence of natural ingredients
Reason to Believe
- Himalaya Lip Balm is enriched with Wheatgerm Oil, a source of Vitamin E, ensuring prolonged moisture retention.
- Contains 100% herbal actives, highlighting a commitment to natural ingredients.
Overview of Artificial Intelligence in Marketing
- Module three covers the essentials of AI and its impact on marketing, including case studies and foundational concepts.
- Key discussions involve AI classification, the Washington Post case study, and a primer on machine learning and deep learning.
Classification of AI Technologies
- AI comprises multiple technologies, not a singular concept.
- Simplifying AI as strong vs. weak overlooks its complexity.
- AI technologies include:
- Visual recognition
- Voice recognition
- Natural Language Processing (NLP)
- Expert systems
- Emotion AI
- Artificially Intelligent robots
Visual Recognition
- Empowers machines to analyze and interpret images.
- Uses AI to contextualize images, overcoming traditional challenges.
- Example: Google Lens employs deep learning for object detection and context analysis.
- Enables real-time image searches and retrieval of relevant information.
Voice Recognition
- Transforms spoken language into text for machine processing.
- Enhances human-machine interaction through natural language.
- Voice AI assistants like Alexa, Siri, and Google Assistant automate customer service.
- Projected growth in voice shopping to $140 billion by 2022.
Natural Language Processing (NLP)
- Processes and analyzes natural language data for machine understanding.
- Essential for speech recognition and improved comprehension of human language.
- Applied in smart home devices and voice-activated digital assistants.
- Used by companies for services such as transcription and translation.
Expert Systems
- Computer programs that solve complex problems and aid decision-making.
- Derive knowledge from a defined base and apply reasoning to propose solutions.
- Commonly utilized in domains like medicine, such as diagnosing diseases.
- Example: PXD system for lung cancer diagnosis via image analysis.
Emotion AI (Effective Computing)
- Capable of recognizing and processing human emotions.
- Emotions significantly influence complex decisions and subconscious behavior.
- Machines evaluate vocal tones to identify emotional states like stress or anger.
- Example: Companion MX app detects anxiety and mood changes through voice monitoring.
Artificially Intelligent Robots
- Merge AI and robotics for autonomous task execution.
- AI enables robots to navigate and respond using computer vision.
- Companies are upgrading robots to handle more sophisticated challenges.
- Example: Sophia, a highly advanced human-like robot showcasing AI capabilities.
Summary of AI Technologies
- Visual Recognition: Exemplified by Google Lens.
- Natural Language Processing: Illustrated by tools like Google Translate.
- Emotion AI: Utilized in systems for emotional recognition.
- Voice Recognition: Represented by assistants such as Siri and Google Assistant.
- Expert Systems: Diagnostic tools similar to the PXD.
Next Generation Marketing Technologies
- Encompasses AI, NLP, sensors, robotics, augmented reality (AR), virtual reality (VR), mixed reality, Internet of Things (IoT), and blockchain.
- AI is crucial in modernizing marketing practices by mimicking human capabilities.
Artificial Intelligence (AI)
- Influences marketing primarily through personalization, predictive analytics, and automated reporting.
- Grows due to:
- Increased Big Data availability.
- Cost-effective and scalable computational power.
- Advancements in new AI methodologies.
Applications of AI
- Mimics human activities, such as thinking (AI), communication (NLP), sensing (sensors), movement (robotics), and connectivity (IoT and blockchain).
- The Washington Post uses AI to enhance news reporting, boosting article relevance and engagement.
Development of AI
- Divided into two methodologies:
- Human-Centered AI: Emphasizes user collaboration and improvement through interaction and data.
- Rationalistic Approach: Focuses on mathematical concepts and engineering for cognitive tasks.
Machine Learning
- Involves algorithms that allow machines to learn from data independently.
-
Types of Machine Learning:
- Supervised Learning: Uses labeled data for predictions, such as fruit classification.
- Unsupervised Learning: Analyzes unlabeled data to discover patterns, like clustering fruits without prior labels.
- Reinforcement Learning: Learns from experience to optimize outcomes, uniquely lacking an answer key.
Deep Learning
- A specialized branch of machine learning focused on mimicking complex human-like reasoning and learning patterns.
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Description
Explore the details of the Himalaya Lip Balm Activation campaign, including key dates and background information about the lip balm market in India. This campaign highlights the brand's leading position and the potential for growth in a largely underpenetrated category.
