Machine Learning & AI in e-commerce

High-level overview of AI attempting to answer three key questions: 1) Why are people so interested in AI? 2) What is it anyway? 3) What are some examples in eCommerce?

This document introduces artificial intelligence, discussing what AI is, how it differs from traditional machines through cognitive thinking and dynamic analysis of situations, and some key advantages like reducing human error and enabling constant work. It also outlines business applications of AI like virtual assistants, chatbots, and tools for HR, logistics, and e-commerce. While noting future potential, it acknowledges concerns about the impact on jobs, security risks from hacking, and unpredictability.

Amazon was founded in 1995 as an online bookstore and has since expanded into various products and services. It uses a management information system (MIS) to support its business operations such as inventory control, logistics, point-of-sale data collection, and internal communications. The MIS includes features like shopping carts, wish lists, one-click purchasing, analytical reports, and a decision support system. Over time, Amazon has innovated its business model and MIS through strategies like expanding product offerings, implementing affiliate marketing and cloud computing services, and developing expert systems to better predict product success and customer preferences.

Katie King is an expert on AI and its impact on marketing. She discusses how AI is advancing beyond just data analysis to generating data from sights and sounds through machine vision and speech recognition. AI will transform marketers by helping with segmentation, tracking, and keyword tagging to make planning and execution more efficient. While AI can aid content creation, human marketers are still needed for their creativity. New technologies like chatbots and autonomous retail robots powered by AI are also discussed. King emphasizes that to prepare for the future of work with AI, organizations need to focus on retraining, culture, and experimentation.

This document discusses the use of artificial intelligence and chatbots in marketing. It outlines how chatbots can transform traditional sales and marketing funnels by allowing direct two-way conversations with customers. Examples are given of clothing and automotive brands using chatbots for personalized customer assistance and targeted campaigns. Statistics show growing markets for chatbots and their benefits across industries like e-commerce, insurance, and healthcare. The future potential of major companies developing chatbot technologies is also mentioned.

Artificial intelligence is transforming supply chain management by optimizing business processes and establishing agile supply chains. AI can help with inventory control and planning by accessing real-time information on customer demands and inventory levels. It can also help with transportation network design challenges like routing and scheduling through techniques like genetic algorithms and ant colony optimization. Expert systems allow purchasing managers to evaluate suppliers and make more informed make-or-buy decisions. Overall, integrating AI offers competitive advantages through predictive analytics and more efficient supply chain management.

This document discusses how IoT and AI can benefit the retail industry in Indonesia. It notes that online transactions currently only account for 1.4% of the total retail market value. It defines IoT as a network of internet-connected things that can collect and exchange data, and AI as the ability of computers to think and learn. The document suggests IoT can be used for real-time store monitoring and AI can analyze optimal support measures based on conditions. A Walmart executive is quoted saying they are using machine learning to enhance the shopping experience between online and offline. It poses that IoT and AI could help retailers know customers better and make retail great again.

This document discusses artificial intelligence (AI) in marketing. It begins with introductions to AI and marketing. It then outlines the AI implementation process in marketing, including using customer data and machine learning to predict customer actions and segment audiences. The document discusses why AI marketing is important for understanding customers, forecasting sales, and creating personalized experiences. It provides examples of how to use AI for various marketing tasks like content generation, dynamic pricing, and chatbots. It also covers the types of AI applications, key features, and benefits, such as improving customer engagement and working faster. In conclusion, the document argues that AI is a powerful marketing tool that can help create personalized customer experiences and experiences continued marketing success.

Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to natural human intelligence. AI has the potential to change the future of digital marketing by lowering costs, allowing marketing programs to run autonomously, and making it easier for businesses to understand customer interactions on their websites. Implementing AI for digital marketing can provide cheaper marketing, better customer service, automated reports, self-learning capabilities to discover new marketing strategies, and personalized customer experiences through content generation. However, some consumers may be wary of AI monitoring their online activities and could use ad blockers or other means to avoid this. Proper implementation of AI for digital marketing requires hiring AI and marketing professionals to develop the technology and monitor its performance.

Fifth Elephant talk about AI in Retail - An introduction to using Computer Vision in Retail. Hasgeek Talk.

The document discusses various applications of artificial intelligence in business. It describes key areas of AI including cognitive science, robotics, natural language processing, expert systems, fuzzy logic, neural networks, biometrics, and virtual reality. For each area, it provides examples of real-world business applications such as using expert systems for employee performance evaluation, applying fuzzy logic to personnel evaluation, training employees with virtual reality, and implementing chatbots using natural language processing. The conclusion states that AI adoption will help businesses stay competitive and that its applications across organizations continue to grow widespread.

This presentation discusses applications of machine learning in the retail sector. It describes how machine learning can be used for customer segmentation, inventory management, recommender systems, and other applications. Specifically, it discusses how association rule mining and the Apriori algorithm can be used to analyze market basket data and identify related products that are often purchased together. It provides an example of how this could be used to enhance inventory management at a grocery store. The presentation also discusses using a recommender system with Microsoft Azure machine learning services to recommend related products to online shoppers.

Just a few years back, artificial intelligence meant adaptions like Jarvis. Who would have thought that AI would soon become an application of our daily lives? Artificial intelligence has the potential to streamline several business processes, analyze data for insights, and help in building fruitful business strategies. Hence, globally, it is being used to remediate old processes, invent new methods, and improve productivity.

Presentation at NRF Nexus 2023 July 11, 2023 Ananda "Andy" Chakravarty VP, Research, Merchandising and Marketing Analytics IDC Retail Insights #NRFNexus

AI continues to expand into different areas like healthcare, agriculture, scientific research and auditing. AI is still only touching the surface when it comes to its application, especially if AI can work with time-series data.

We are all consumers of financial services more or less. We have bank accounts, possibly life insurance, some of us have credit cards, some of us have fixed deposits, some of us may be doing share trading and investment, some of us are borrowers of loans. These are all financial services. Financial Technology or FinTech is a way of delivering or improving the delivery of financial services using technology and innovation. The use of smartphones and internet to improve the services in banking, investing, lending and borrowing etc are examples of technologies aiming to make financial services more accessible to the people. The use of Artificial intelligence, Machine learning, Blockchain, Cryptocurrency etc are redefining the way we are used to receiving financial services. FinTech is an emerging industry. Startups, established financial institutions as well as technology companies are disrupting this space to replace or enhance the usage of currently existing financial services. In this video we will restrict ourselves to the usage of AI in FinTech. We will learn about different areas where FinTech is already serving a great deal. We will learn about the areas where we look forward to seeing more disruptions and innovations to make financial services more secure and accessible to the general public.

Generative AI: Past, Present, and Future – A Practitioner's Perspective As the academic realm grapples with the profound implications of generative AI and related applications like ChatGPT, I will present a grounded view from my experience as a practitioner. Starting with the origins of neural networks in the fields of logic, psychology, and computer science, I trace its history and align it within the wider context of the pursuit of artificial intelligence. This perspective will also draw parallels with historical developments in psychology. Against this backdrop, I chart a proposed trajectory for the future. Finally, I provide actionable insights for both academics and enterprising individuals in the field.

There is no silver bullet that can get brands to revenue acceleration. Instead, companies have to build a strong revenue operations infrastructure based on empathetic customer experience initiatives, intelligent data ops, and innovative content generation. Once you start with the end in mind, your organization can get to a sustainable — and much more feasible — revenue acceleration solution.

Access to data is what enables AI in marketing. The abundance of available information makes AI necessary for marketing purposes. The biggest potential value from AI applications is in marketing and sales functions, as AI can help personalize customer experiences and evaluate customer conversion probabilities more effectively based on large amounts of customer data.

The document discusses how artificial intelligence and new technologies will transform the accounting profession in the coming years. It notes that accountants will need to shift from a focus on compliance services to advisory services, leveraging automation, analytics, and cloud-based tools to gain insights for clients. This will allow accountants to spend more time developing client relationships and growing their businesses. The future accounting practice is predicted to have integrated apps and data, automated data collection, advisory services, and a focus on client insights and performance rather than basic accounting and compliance.

Understand how AI and machine learning are playing a role in everything from data integration to machine learning to insight generation.

View the slides from Peak, AWS and Footasylum's presentation at NRF 2020: Retail's Big Show in New York City.

Although most marketers would agree that online-to-offline measurement is important for the future success of their business, it’s hard to know what steps to take to adopt this strategic initiative. Ovative/group has found that when done correctly, online-to-offline addresses many of the most complex business problems by providing answers to questions such as: What is the impact of an online visit on offline sales? Does this impact vary by category or product type? What marketing channels influence offline most? And, can I use these channels to drive offline acquisition? But how do you get started and ensure online-to-offline is a success for your organization? After attending this webinar featuring Ovative/group and LiveRamp you’ll understand: – Why online-to-offline is important and how to prioritize it among other strategic initiatives – Who within your organization needs to be involved and how to structure your team – What technology is required to build online-to-offline measurement capabilities – How to make digital marketing decisions based on enterprise metrics

The increasing number of online retailers on one side and slowing growth of online user population on the other side are the driving forces of change in e-commerce. Number of returning customers is in decline as new competitors are entering the market. Cost of advertising is rising. One-time customers are not profitable anymore so online retailers need to shift focus to retention. In this talk we'll walk you through the process of building the new framework. We'll deep-dive into data-driven digital marketing framework, explain how to use CRM data to enhance your segments and finish up with case studies expaining how to use the new metrics to identify top customers and maximize your profits.

The newsletter discusses the growth of online education and marketing analytics. It notes that the global eLearning market is expected to grow from $35.6 billion in 2011 to $51.5 billion in 2016. Drivers of this growth include budget constraints, the need to train dispersed workforces quickly, and changing demographics. Marketing analytics is also in high demand as it allows companies to improve marketing ROI through data-driven decision making. The newsletter explores these topics through several articles and cases.

Organizations, people, and things are generating massive amounts of data every day. In a 24-hour period, we collectively send 294 billion e-mails and 500 million tweets. We plug 3.5 billion searches into Google. Our connected cars generate a whopping four petabytes of data. Even our watches, fridges, and TVs are constantly creating and sharing data. By Optimisator

The document discusses how AI/ML can help deliver business outcomes by moving past hype. It provides examples of how Footasylum used AI to increase digital revenues by 28% and return on ad spend by 10x through personalized marketing, recommendations, and social media targeting. The document also outlines Peak's full-stack AI system and how it supports connected retail through optimizing demand planning, inventory, logistics and more to improve profitability and efficiency. Real customer stories demonstrate how AI can be applied across marketing, supply chain, and operations.

It's time to Focus on the Future. Based on interviews with over 250 global advertisers, we address the biggest trends you need to master in order to be prepared for The New Machine Rules. Download your copy now: http://bit.ly/2AirbwR

This presentation will introduce anyone with a growth hacking mindset in using analytics to grow their business. I will address setting up actionable goals, choosing the OMTM, the conversion funnel, reporting and experimenting.

Explore RedEye's CCO's thoughts on the Customer Data Platform and how it can help you to spend less but achieve more.

It\'s been a bug-bear of mine for many years that the average marketing skill set has not moved on very much from the 1960\'s model of 4 \'P\'s (Product, Price, Promotion, Place). Or that marketing is still largely synonomous with advertising - and spam advertising at that. This is a presentation I did to a marketing forum out in Singapore, where I\'ve tried to outline the new capabilities of the marketer of the 21st century. I also postulate the (controversial) perspective that a chunk of this new capability - especially around data and decisioning - might be better out sourced, leaving the internal marketing skills to be concentrated on strategy and proposition. See what you think. [Sorry you won\'t have my spoken narrative just yet but the slides are reasonably self explanatory]

Webtrekk´s presentation at the Marketing Insights & Big Data event 2014, Utrecht. Be prepared, focus and look for small changes that drive big bucks. E.g. measuring impact TV commercials on online revenue. For more info please contact Fred Pellenaars, Country manager Benelux fred.pellenaars@webtrekk.com +31 6 347 11 500

According to Gartner, each year businesses see 1/5th of their marketing budgets go to waste due to inaccurate data and reporting that leads to ineffective marketing decisions and under-performing campaigns. In this presentation, we will guide you through a proven and efficient process that standardizes the tracking and measurement of marketing campaigns. By eliminating siloes, boosting productivity, and addressing existing and future data accuracy challenges, this approach ensures reliable insights that drive informed decisions and deliver higher marketing return on investment (ROI).