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

Description

Learn how to use artificial intelligence for product and service innovation, including the diverse use cases of Commerce.AI Key FeaturesLearn how to integrate data and AI in your innovation workflowsUnlock insights into how various industries are using AI for innovationApply your knowledge to real innovation use cases like product strategy and market intelligenceBook Description Commerce.AI is a suite of artificial intelligence (AI) tools, trained on over a trillion data points, to help businesses build next-gen products and services. If you want to be the best business on the block, using AI is a must. Developers and analysts working with AI will be able to put their knowledge to work with this practical guide. You'll begin by learning the core themes of new product and service innovation, including how to identify market opportunities, come up with ideas, and predict trends. With plenty of use cases as reference, you'll learn how to apply AI for innovation, both programmatically and with Commerce.AI. You'll also find out how to analyze product and service data with tools such as GPT-J, Python pandas, Prophet, and TextBlob. As you progress, you'll explore the evolution of commerce in AI, including how top businesses today are using AI. You'll learn how Commerce.AI merges machine learning, product expertise, and big data to help businesses make more accurate decisions. Finally, you'll use the Commerce.AI suite for product ideation and analyzing market trends. By the end of this artificial intelligence book, you'll be able to strategize new product opportunities by using AI, and also have an understanding of how to use Commerce.AI for product ideation, trend analysis, and predictions. What you will learnFind out how machine learning can help you identify new market opportunitiesUnderstand how to use consumer data to create new products and servicesUse state-of-the-art AI frameworks and tools for data analysisLaunch, track, and improve products and services with AIRise above the competition with unparalleled insights from AITurn customer touchpoints into business winsGenerate high-conversion product and service copyWho this book is for This AI book is for AI developers, data scientists, data product managers, analysts, and consumer insights professionals. The book will guide you through the process of product and service innovation, no matter your pre-existing skillset. Table of ContentsImprove Market Opportunity IdentificationGenerate New Product IdeasUnderstand How to Predict Industry-Wide Trends Using Big DataApplying AI for Innovation – Luxury Goods Deep-DiveApplying AI for Innovation―Wireless Networking Deep-DiveApplying AI for Innovation―Consumer Electronics Deep-DiveApplying AI for Innovation – Restaurants Deep-DiveApplying AI for Innovation―Consumer Goods Deep-DiveProduct AIDelivering Insights with Service AIDelivering Insights With Market AIDelivering Insights with Voice Surveys Cover Title Page Copyright and Credits Contributors Table of Contents Preface 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 Summary 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 Summary 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 Summary 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 RefaceAI Zalando Using Commerce.AI for luxury brands Design and user research Product development and marketing Brand management Trend analysis Summary 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 Sustainability Becoming data-driven 5G 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 Summary 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 Summary Chapter 7: Applying AI for Innovation – Restaurants Deep Dive Understanding the challenges of restaurants Profitability 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 Summary 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 Summary 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 Summary 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 Summary 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 E-commerce 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 Summary 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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