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TECHNOLOGY
Generative AI In eCommerce:
From Personalization To Individualization
By Eleni Stamoulakatou
Originally published on LinkedIn on November 13, 2023 | Generative AI In eCommerce: From Personalization To Individualization
Revised on May 7, 2024 at 6p.m. GR | 11a.m. ET
The generative AI revolution is already happening and this new technology is advancing rapidly making a vertical impact on disparate fields and industries. It has already started to transform many industries, including retail and by extension, ecommerce. Retail executives are reportedly excited by the unique capabilities of this new technology, realizing early, in what seems to be a unprecedented change curve, that it will inevitably go to become a baseline prerequisite for the design of advanced marketing strategies aimed to help transform the way they run their businesses and serve their customers. But let's see why this technology is stirring things up, the benefits it introduces to brands and retailers globally and why retail industry experts are already leaning in on it.
What is Generative AI?
Progress in the AI field is seemingly cyclical as every few years there is a new capability being introduced based on which, something once impossible suddenly puts itself in the list of our 'business as usual' activities and options. This is not quite the case in this instance as generative AI does in fact seem to be able to do things that would once seem unfathomable; and that is to reinvent itself by itself with its impact and progress manifesting at the same vigorous pace in all the industries it has already been applied to.
Generative AI is a type of artificial intelligence that can be used to curate new content such as text, audio, imagery and videos. It uses machine learning algorithms to create outputs based on a training data set. Some widely known examples of generative AI include Google Bard, Bing, ChatGPT and DALL-E 2.
The primary difference between traditional AI and generative AI is rooted in what they are designed to do and their functions. Specifically,
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Traditional Artificial Intelligence enables the imitation of cognitive human functions such as problem-solving, learning, reasoning and adapting via the use of mathematics and logic. Traditional AI models have the ability to learn from data and make decisions and/or predictions based on that respective data so they can essentially be trained to follow specific rules and perform assigned tasks yet they cannot be used to generate new content.
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Generative Artificial Intelligence is designed to generate new content that resembles content created by humans, via the use of algorithms. Generative AI models are trained on a set of data and learn the underlying patterns to generate new data that mirrors the training set.
What Is The Key Advantage Of Generative AI?
Generative AI encapsulates an entirely new set of capabilities both powerful and flexible. Its power lies in the combination of its ability to generate text, speech, images, music, video, and code in combination with how it treats existing information to tailor the coordinates of an interaction. Its benefits are rooted in its adaptability and how it can help companies reinvent the way they run their businesses, serve their customers and perform their operations.
Global Generative AI in eCommerce Market Prediction
Generative AI in ecommerce market globally is projected to reach a valuation of US$ 2.1 Billion by 2032.

Source: Market Research, Yahoo Finance
Some interesting stats:
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In June 2023, Accenture announced an investment of $3 Billion in AI to accelerate clients’ reinvention.
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Per Gartner's report on generative AI, approximately 30% of newly discovered drugs will be developed with the help of AI technology by 2025.
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According to State of AI report, by September 2023, generative audio tools are expected to attract over 1,00,000 developers.
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China’s search engine Baidu announced to invest fund of approximately 1 billion Yuan ($140 million) in nurturing its interest in AI self-reliance (TechCrunch).
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In April 2023, the prime Minister of Japan stated that the country is openly supporting the use of industrial generative AI such as ChatGPT techniques (Thomson Reuters).
References/Useful Links
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Technology Vision 2023, Accenture
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AI for everyone, Accenture
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Total Enterprise Reinvention: Setting a new performance frontier, Accenture
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Accenture CEO Julie Sweet on A.I. investment: All about accelerating clients ability to reinvent, Accenture
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A new era of generative AI for everyone, Accenture
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Generative AI: Navigating Ethics and Accessibility in Algorithmic Creativity, Accenture
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Accenture to Invest $3 Billion in AI to Accelerate Clients’ Reinvention, Accenture
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Responsible Gen AI: WEF 2024 | A New Engine of Economic Growth, WEF
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Google Bard | Bing | ChatGPT | DALL-E 2
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Baidu’s $145M AI fund signals China’s push for AI self-reliance, TechCrunch
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Japan supports industrial use of generative AI, Thomson Reuters
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How Mars, Colgate-Palmolive, Nestle & Coca-Cola are Exploring Generative AI, CGT
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The Amazing Ways Coca-Cola Uses Generative AI In Art And Advertising, Forbes
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Selling To Generative AI: Marketing Strategies For New Algorithmic Customers, Forbes
What Do Retailers Think About Generative AI?
Feedback from retailers has been strikingly positive with the vast majority looking forward to seeing how generative AI will transform the way they communicate with their customers, generate accurate real-time insights, curate personalized innovative experiences, leverage augmented reality to facilitate remote assistance and customer support, and automate processes seamlessly.
Specifically, 9/10 retail executives are feeling excited by the new capabilities offered by foundation models which is the underlying technology of some generative AI applications such as ChatGPT (source: Technology Vision 2023, Accenture).
Eventually, AI operations will shift from building models to building on top of models.
Source: Accenture Technology Vision 2023
What Are The Biggest Challenges Facing eCommerce Today?
The omnichannel ecommerce industry is constantly evolving, forcing businesses to struggle with reimagining ways to deliver an optimum customer experience. Some of the challenges that need to be tackled are:
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Sources: Business News Daily, Forbes
Short-term Sales' Prediction
Global ecommerce sales are projected to reach a valuation of US$ 8 trillion by 2027.

Source: eMarketer
Generative AI Use Cases In eCommerce
Across the e-commerce sector, generative AI can benefit customers, businesses and employees by automating, simplifying and overall improving tasks that pertain to the day-to-day operational lifecycle. Below are some of the most common use cases of how generative AI can supplement the e-commerce workflow across various industries.
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Generative AI Analytics - Generative AI analytics tools offer business executives more contextual real-time customer data across various channels but also in-depth demographic data points. They can collect data available in unstructured formats (e.g., customer service surveys, social media commentary, advertisement engagement etc.) and consider various parameters to provide consolidated insights that have always posed a challenge in capturing. Generative AI-powered tools push analytics to the next frontier by moving from offering accurate insights to providing businesses with a predictive forecast via targeted recommendations on ways to improve products, services and outcomes. Nestlé is one of the companies already using generative AI analytics in an effort to generate market research reports (CGT: How Mars, Colgate-Palmolive, Nestle & Coca-Cola are Exploring Generative AI).
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Generative AI-powered Advertisements and Imagery - Generative adversarial networks are essentially image generator networks that can be trained to create realistic-looking images from scratch via the use of a dataset of existing product images. This is a method that can save businesses time and allow human resources to altogether skip the editing phase and focus on the creative and strategic facet of their operations. Coca Cola is one of the companies already using generative AI in advertising (Forbes: The Amazing Ways Coca-Cola Uses Generative AI In Art And Advertising).
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Customer Service Chatbots - With generative AI-powered chatbots, businesses can manage conversations 24/7, aimed to provide a real-human, thus more engaging, customer experience. Content creation and predictive capabilities can help regular chatbots move away from pulling from a fixed repository of responses, that often don't effectively facilitate or encourage an engaging ''conversation'' with customers, to enabling unique customer problem solving by leveraging generative AI-powered agents to help assess a case and further train the human 'help desk' on how to effectively handle each case based on its special needs and particularities. Expedia is already exploring the enhancement of its ''Trip Planner'' app with generative AI-powered chatbot capabilities (CIO: Expedia poised to take flight with generative AI).
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Product Recommendations - Generative AI can help generate personalized product recommendations for customers. A customer data analysis is performed using various historical data and parameters, such as purchase behavior over time, search trends and patterns and browsing history and with the use of generative AI algorithms, tailormade personalized product recommendations can be curated to match their customers’ identified needs and budgets. This can help businesses maintain their customer base and avoid fluctuation in sales. eBay is already using generative AI algorithms as a basic component of its marketing strategy (Forbes: Selling To Generative AI: Marketing Strategies For New Algorithmic Customers).
OpenAI’s GPT-3, released in 2020, was the largest language model in the world. It taught itself to perform tasks it had never been trained on and outperformed models that were trained on those tasks. Since then, companies like Google, Microsoft, and Meta have created their own large language models.
Source: Accenture Technology Vision 2023
Examples of International Retailers Leveraging Generative AI
AI enables retailers to use customer data and their behavioral patterns to design personalized marketing campaigns founded on the concept of computer vision, (i.e., the process of acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information that equals the transformation of visual images into descriptions of the world that make sense to thought processes and can elicit appropriate action) rather than a plain search analysis. Below are some of the international retailers that are already leveraging generative AI to give their businesses greater technological capabilities:
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Zara - is currently using generative AI to manage its inventory processes. Microchips have been installed in security tags to help monitor products throughout their lifecycle, from production, to shipping, to display, to on-sale.
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Hanesbrands - is currently using a generative AI assistant to optimize its supply chain. With the use of algorithms, the tool applies parameters that help users’ free-form questions be interpreted and accurately addressed. This information is stored in a virtual repository where it becomes available to employees across the organization.
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Amazon - is currently using generative AI for the assessment and review of online products. It uses it to summarize key themes available for each product to offer a succinct synopsis. This is a form of in-advance screening that saves customers time from reading a long description about products they may be interested in learning more about.
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Sephora - is currently using generative AI as part of their augmented reality strategy. Via facial recognition, it contours and then allows customers to accurately apply the virtual make-up in a realistic way from the comfort of their home.