AI Strategy for Sales and Marketing: Connecting Marketing, Sales and Customer Experience
- Length: 288 pages
- Edition: 1
- Language: English
- Publisher: Kogan Page
- Publication Date: 2022-01-25
- ISBN-10: 1398602000
- ISBN-13: 9781398602007
- Sales Rank: #25286419 (See Top 100 Books)
Marketing and sales prioritize AI and machine learning more than any other business department, yet often struggle with how to scale and strategize the opportunities they present.
AI Strategy for Sales and Marketing presents a framework for understanding how AI can boost customer-centricity and sales by creating a connected strategy that delivers value today and into the future. Supported by practical tips and advice throughout, it covers topics including personalization, upskilling, customer experience for both on and offline shopping channels and the importance of using AI responsibly to create consumer trust.
Featuring original research and interviews with leading practitioners, it also contains global case studies from organizations in a range of sectors, including Samsung, PwC, Rolls Royce, Deloitte and Hilton, with insights into the various stages of their adoption journeys. Written by a recognized industry expert, it is an invaluable resource for those wanting to benefit from using AI strategically in marketing, sales and CX.
About the author Acknowledgements 01 AI and the future of work and society Optimism for innovation that benefits society and business Roaring twenties The impact of machine learning Customer focus: smart marketing The personalized experience Driving change A small window of opportunity Is AI worthy of global attention? A global duty to raise living standards Market share The AI race: the US and China AI in the Middle East and South Asia AI in Europe Investment in AI for marketing AI for improved collaboration AI in Australia Beyond the pretty shiny objects AI is not a silver bullet for comms Digital twins Bibliography 02 Strategic AI tools for marketing, sales and CX Which tools are available? Replicate human reasoning AI and events Emotionally intelligent chatbots Start with what you know Accessible for smaller budgets Minimizing daily minutiae in customer service, sales, HR and marketing Smarter social listening Examples from hospitality The human side of AI Replacement versus reshaping Predicting customer needs at scale AI-enabled marketing automation Connecting marketing, sales and CX for long-term advantage The new AI sales landscape Comm tech and decision augmentation Move up the food chain to strategy AI-powered reputation-based decision-making Bibliography 03 How AI is reshaping the world of retail and hospitality Really intelligent retail The digital imperative The rise of me-commerce Elevating customer experiences Driving the future of work: intelligent marketing Reshaping digital marketing How can AI support sales? Bibliography 04 Driving change in the automotive and manufacturing sectors Building trust: AI-powered CX at Kia Motors Conversational AI drives empathy Decision Intelligence: making sense of data Everything as a service AI in manufacturing The environmentally conscious consumer The Rolls-Royce Aletheia Framework™ Trustworthy AI isn’t necessarily good AI Bibliography 05 Optimizing AI data insights in finance, law and insurance Unlocking trust: using AI to develop a mutual relationship between bank and customer Conversational agents for customer support How to create an AI customer service platform Business banking Fraud and compliance Challenging the status quo Where next? How to up-tech your institution for the future How to get started with AI in insurance The UK insurance sector today A snapshot of the industry Underwriting: measuring risk Policy pricing Assessing claims Cutting fraud New business acquisition How insurers can use AI in their marketing and sales The rise of insurtech: friend or foe? Last but not least, people How is AI reshaping the legal profession? Bibliography 06 Revolutionizing customer support in the telecoms sector Six core benefits of AI for telcos Customer-centricity: the defining factor Bibliography 07 New economic model for the robot revolution Lifelong learning and quaternary education Personalized, lifelong learning Societal and corporate responsibility Education and equality Educating the next generation Enhancing education with strategic technology Looking ahead at learning AI lacks emotional attachment Will robots replace creativity in a work setting? Bibliography 08 A framework for AI success Strategy Time Augmentation Need Data Agile Resources Digital Investment Standards Ethics Industry views on AI strategy Business culture Treat AI as an assistant, not a boss Culture change Trust cleans the data Bibliography 09 Flourish or self-destruct? A fork in the road Regulation and compliance enforcement AI in the United States, under Joe Biden Global citizen views of AI AI won’t replace great human leaders Amplifying inequality Lack of oversight and measurement Avoid limiting AI acceleration Responsible citizenship: a view from the United Arab Emirates North America’s approach to AI issues Data security: a view from Canada Concerning knowledge gaps Transition from lab to real world The implications of AI in education Avoiding a digital divide Purpose A four-day working week Digital Darwinism in the 2020s Hybrid workforce Next gen AI: unsupervised learning Misuse of algorithms Landmark ruling: Deliveroo algorithm judged to be discriminatory AI might widen the gap between rich and poor Explainability and trust AI as a force for good The battle for AI dominance Respecting human rights Looking ahead to 2030 Bibliography Index
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