AI-Powered Commerce: Building the products and services of the future with Commerce.AI

دانلود کتاب AI-Powered Commerce: Building the products and services of the future with Commerce.AI

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کتاب تجارت مبتنی بر هوش مصنوعی: ساختن محصولات و خدمات آینده با Commerce.AI نسخه زبان اصلی

دانلود کتاب تجارت مبتنی بر هوش مصنوعی: ساختن محصولات و خدمات آینده با Commerce.AI بعد از پرداخت مقدور خواهد بود
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توضیحاتی در مورد کتاب AI-Powered Commerce: Building the products and services of the future with Commerce.AI

نام کتاب : AI-Powered Commerce: Building the products and services of the future with Commerce.AI
عنوان ترجمه شده به فارسی : تجارت مبتنی بر هوش مصنوعی: ساختن محصولات و خدمات آینده با Commerce.AI
سری :
نویسندگان : ,
ناشر : Packt Publishing
سال نشر : 2022
تعداد صفحات : 256
ISBN (شابک) : 180324898X , 9781803248981
زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 8 مگابایت

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فهرست مطالب :

Title Page
Copyright and Credits
Table of Contents
Section 1:Benefits of AI-Powered Commerce
Chapter 1: Improving Market Opportunity Identification
Identifying market opportunities the traditional way
Big data challenges in market opportunity identification
Using AI for market opportunity identification
Exploring AI-powered market reports
Chapter 2: Creating Product Ideas
Understanding the pillars of AI
Language understanding
Visual understanding
Information extraction
Information organization
Creative AI
Why is product ideation so hard?
Using Commerce.AI for creative AI
Building product ideas
Selecting product ideas
Iterating product ideas
Chapter 3: Understanding How to Predict Industry-Wide Trends Using Big Data
Technical requirements
Why traditional forecasts fail
It\'s impossible to know everything about all products and services
Knowing how products perform today is not a good guide for predicting how they will perform tomorrow
The behaviors of many products are highly correlated and can be difficult to disentangle
Traditional models get overwhelmed by today\'s big data
The data itself keeps changing
Using big data to enable better forecasts
Understanding deep learning
Learning from examples
Demand forecasting with a practical example
Sentiment forecasting with a practical example
Gaining value from data-driven forecasts
Section 2:How Top Brands Use Artificial Intelligence
Chapter 4: Applying AI for Innovation – Luxury Goods Deep Dive
Technical requirements
Understanding the challenges of luxury brands
Brand management
Increasing competition
Social media management
Matching eccentric customer preferences
Understanding unique customer profiles
Understanding the data extraction process
Tumi uses AI for better marketing
Burberry uses AI to improve its clothes
Algorithmic couture
AI runways
Using Commerce.AI for luxury brands
Design and user research
Product development and marketing
Brand management
Trend analysis
Chapter 5: Applying AI for Innovation – Wireless Networking Deep Dive
Technical requirements
Understanding the challenges of wireless networking brands
Growth in traffic
Performance challenges
Increasing complexity
Becoming data-driven
Analyzing product data for wireless networking brands
Analyzing wireless networking product review data
Using Commerce.AI for wireless networking brands
Enter data-driven solutions
Star ratings
Improving best sellers ranking
Time compiling weekly reports
Improving product sentiment
Improving product conversion
Search result ranking
Detail page glance views
Chapter 6: Applying AI for Innovation –Consumer Electronics Deep Dive
Understanding the challenges faced by consumer electronics brands
The needs of the connected consumer
A new reality of short-term attention span
Meeting the demands of the content consumer
The need to become data-driven
Emerging consumer electronics markets
Analyzing product data for consumer electronics brands
Key considerations in the data-driven product strategy
How to collect consumer data
How to integrate data into the product design
Using Commerce.AI for consumer electronics brands
Understanding product positioning
Analyzing the market with consumer electronics AI reports
How does Commerce.AI help with consumer electronics brand research?
Generating consumer electronics product ideas
Extracting insights from Shopify
Sharing insights on Slack
Chapter 7: Applying AI for Innovation – Restaurants Deep Dive
Understanding the challenges of restaurants
Changing guest preferences
Creating profitable menus (and pricing)
Menu engineering
Maintaining online reviews and social media marketing
Analyzing product data for restaurants
Predicting how food items are likely to perform
Predicting how competitors will perform
Predicting customer needs based on previous purchases
New profile discovery
Using Commerce.AI for restaurants
Analyzing restaurant customer data
Mobile surveys
Gauging customer sentiment response based on marketing campaigns
Stay connected with your customers
Finding and predicting trends in the restaurant business
A case study – how a large French pizza chain used Commerce.AI
Chapter 8: Applying AI for Innovation – Consumer Goods Deep Dive
Technical requirements
Understanding the challenges facing consumer goods brands
Competitive consumer goods
Consumer goods market intelligence
Inventory management
Creating the right product mix
Creating consumer goods content at scale
Consumer goods review analysis
Analyzing product data for consumer goods brands
Consumer goods content generation
Analyze consumer goods reviews
Lead time analysis
Demand forecasting
Maintaining adequate cash flow
Analyzing the impact of discounts
Identifying seasonal trends
Social media analytics
Using Commerce.AI for consumer goods brands
Measuring product attributes and trends
Predicting revenue opportunity
Analyzing user personas and customer segments
Analyzing the customer journey
Generating consumer goods product ideas
Section 3:How to Use Commerce.AI for Product Ideation, Trend Analysis, and Predictions
Chapter 9: Delivering Insights with Product AI
Commerce.AI for product concept and development
Market research
Understanding demand
Product ideation
Product launch
How AI is changing product launches
Predicting demand from early signals
AI for the two types of product launches
Using AI for product launches—advantages and disadvantages
Product management
Tracking product wishes
Brand management
Using AI for consumer insights
Using AI for product tracking
Marketing and merchandising
Customer support
Chapter 10: Delivering Insights with Service AI
Empowering your front line
Better understanding customer affinities
Better understanding purchase reasons
Better understanding customer challenges
Turning your next interactions into great brand experiences
Managing your locations
Optimizing your branch
Optimizing your employees
Optimizing your service
Enhancing service offerings
Identifying growth areas
Leveraging AI for creating stronger service offerings
Identifying opportunities to boost customer loyalty
Finding new uses for your store
Getting a picture of bottlenecks before they escalate
Chapter 11: Delivering Insights with Market AI
Analyzing trends and white space discovery
Improving product idea generation with white spaces
The virtualization of everything (VE)
Augmented reality
The rise of social commerce
The rise of influencer marketing
The gamification of everything
The rise of the mass affluent
The rise of authenticity
Gen Z
Demand for sustainable products
Connecting market shifts to brands, products, and services
Gauging product shifts
Recognizing product risk areas
Product risk management with AI
Understand market DNA
Finding market DNA attributes
Finding user wishlists and emerging needs with AI
AI and consumer-generated content
Finding new use contexts with AI
Chapter 12: Delivering Insights with Voice Surveys
Engaging your customers with ease
Product feature prioritization
New service offering
Post-purchase survey
Hotel experience survey
Store experience survey
Post-call survey
Pricing survey
Improving your offerings
Deriving insights into your existing products
How to leverage survey feedback to understand your customers
How to act upon those insights
Coming up with new product ideas
Improving customer loyalty
What drives customer loyalty?
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