Simple guide to AI in eCommerce

By Vamsi Thatikonda

The ecommerce industry has experienced significant changes in recent years, thanks to the advanced applications of artificial intelligence (AI). Leading retailers such as Amazon, Walmart, and Chewy have effectively utilized AI to enhance personalization, streamline operations and inventory management, and provide better customer service. 

As a result, the use of AI has transformed the online shopping experience to be more efficient, customized, and seamless. In fact, according to the recent IDC study, up to 40% of global retailers are already experimenting with generative AI to provide customers with better-tailored experiences. This text aims to show AI use cases in ecommerce and how these tools increase their income and reduce costs, keeping the matter as simple and straight-to-the-point as possible.

Providing recommendations

An essential application where leading ecommerce players have tapped into the power of AI is providing personalized recommendations. Sophisticated machine learning algorithms like logistic regression and neural networks analyze enormous volumes of customer data, including past purchases, browsing clicks, wish lists, and more, to determine an individual shopper’s likely preferences and interests. 

This allows Amazon, for example, to customize its product recommendations, including the familiar “frequently bought together” and “inspired by your shopping trends” suggestions shoppers often see. Amazon has revealed that its recommendation engine drives 35% of sales on its platform. 

Similarly, Walmart and Chewy can tailor product suggestions based on pet breed and other characteristics, providing a service-oriented experience. The impact of AI in ecommerce business including personalized recommendations is tangible results – increased average order value, customer satisfaction, and loyalty.

The power of chatbots

Chatbots and virtual assistants have made significant advancements using conversational AI. Instead of going through various layers of menus, shoppers can now ask intelligent chatbot questions, just as they would with a customer service representative. Major retailers like Walmart and Chewy offer customers access to an AI-powered chatbot on their apps and websites. 

This allows them to obtain product-related information, track orders, find store locations, and more, resulting in improved customer convenience. Moreover, virtual assistants help to reduce the number of routine customer service inquiries handled by human agents, leading to cost savings and quicker responses. According to the data gathered by Forbes, 81% of customers say that positive experiences increase their likelihood of making another purchase. 

Gathering insights

AI solutions for ecommerce gives retailers an edge when it comes to gaining insights into their operations. From predicting inventory needs to automating warehouse functions, AI has helped optimize supply chains, reduce waste, and keep popular items in stock. Advanced clustering algorithms group customers into segments with common attributes and behaviors, allowing for more targeted marketing campaigns.

Retail giants like Amazon and Walmart have utilized this technology to improve their operations. Additionally, robotic warehouse automation has helped retailers meet consumer demand faster and more efficiently. For instance, Amazon has deployed 200,000 warehouse robots across its logistics network.

Reducing risk

As online transactions become more prevalent, retailers face a growing risk of payment fraud and cyberattacks. However, AI technology has emerged as an effective approach to minimize this risk. By using advanced machine learning algorithms, retailers can identify patterns, anomalies, and potential threats that evade traditional rule-based fraud systems. 

This technology provides a more accurate and efficient method of fraud protection, preventing good customers from being declined while minimizing risk exposure. According to the recent Veriff report, ecommerce is one of the most fraud-prone industries in the world, with a 20% rise in overall fraud year-on-year.

The use of AI can help tackle this challenge. For example, despite its high volume of payment transactions, Amazon experiences a meager fraud rate thanks to its effective AI fraud-fighting technology.

Tools of transformation

We see how AI is transforming nearly all aspects of ecommerce, including personalization, chatbots, inventory management, anticipating demand, and risk management. We see this transformation accelerating with the surprising effectiveness of generative AI and Large Language Models (LLMs) and their unique suitability to ecommerce applications. The key to leveraging these innovations is an integrated data platform approach, architecting unified data infrastructure and building pipelines as a foundation to power advanced algorithms applied across business functions. 

The following categories show the specific methods ecommerce players use to deploy AI:

  • Predictive Models: Algorithms that "learn" from data to make decisions without explicit programming. Used for customer segmentation and predictive analytics.
  • Natural Language Processing (NLP): Parsing of speech and text to understand human languages. Powers conversational interfaces and analyzes product reviews.
  • Computer Vision: Computer vision algorithms can automatically detect defects in merchandise, enable cashierless checkout through object recognition, and even gauge customer engagement by analyzing facial expressions
  • Recommendation Engines: Systems that predict customer preferences from past behavior to provide personalized, conversion-focused product suggestions.

The Future of Ecommerce AI 

Upcoming innovations like multi-channel conversational platforms, autonomous warehouses, drone delivery, and augmented reality shopping experiences promise to revolutionize further ecommerce powered by progress in AI.

While first-mover advantage in AI innovation can provide competitive edge, concerns exist around job losses from automation and algorithms controlling critical decisions. Processes relying on generative AI and LLMs need governance and care to manage accuracy issues. However, with adequate planning, AI can remove mundane tasks from staff, improve knowledge worker productivity, and create new opportunities for roles managing AI systems.

Summary - how to use AI in Ecommerce

AI adoption continues to accelerate as one of the most transformative technologies across industries - according to the McKinsey’s “The state of AI in 2023” report, one third of companies are already using AI-powered technologies. And we expect generative AI and LLMs to further boost that acceleration, making AI a more ubiquitous presence. Ecommerce companies stand to gain tremendously from capitalizing on these innovations. Leaders today have a timely opportunity to lay integrated foundations to unlock AI capabilities that will drive rewards for years to come.

Artificial intelligence has empowered top retailers to provide personalized and efficient customer experiences while streamlining internal operations. Ecommerce giants such as Amazon, Walmart, and Chewy continue to enhance their AI capabilities. We can anticipate further innovation that will benefit economic and consumer satisfaction. The future of retail looks bright, with AI taking it to new heights.

By Vamsi Thatikonda, Senior Software Engineer at Chewy

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