AI in E-Commerce: The Best Tools for Your Business


Artificial Intelligence (AI) has revolutionized the way companies operate, especially AI in e-commerce is worth it being mentioned. With the increasing competition and the need to offer personalized experiences to customers, more and more brands and retailers are turning to AI to optimize their operations and improve customer satisfaction. From product recommendations to chatbots and customer segmentation, there are numerous AI tools available to help companies achieve their goals. Over the past five years, artificial intelligence (AI) has gained significant traction in the e-commerce industry. A Statista study revealed for example that slightly over half of the respondents indicated that they were actively attempting to implement AI. Meanwhile, nearly 30 percent said they were beginning to consider this relatively new technology, and 11 percent reported that they were already making progress in working with it.

In this article, we’ll explore some of the best AI tools for your e-commerce business, and how they can help you improve your customer experience, increase sales, and streamline your operations.

What Are AI Tools?

AI tools are software programs that leverage artificial intelligence algorithms and techniques to perform various tasks autonomously, efficiently, and accurately. They use machine learning, natural language processing, computer vision, and other AI techniques to learn from data, analyze patterns, and make predictions or decisions.

AI tools can be used across various industries and domains, including e-commerce and marketing. They can perform a wide range of functions, such as automating routine tasks, optimizing processes, providing personalized recommendations, detecting fraud, and improving decision-making.

Examples of AI tools include chatbots, virtual assistants, predictive analytics, recommendation engines, fraud detection, natural language processing (NLP), and more. These tools can be integrated into existing applications, platforms, or systems to enhance their capabilities and provide additional value to users.

The graph below highlights the areas of adoption of AI in e-commerce, indicating that “Personalization,” “Site search,” and “Forecasting” are the most commonly adopted areas, based on data from Europe and North America.

AI tools used in e-commerce
Image credit: Statista.

AI in E-commerce: The Best Tools per Type


Chatbots have emerged as a popular solution for handling customer inquiries, complaints, and providing real-time assistance. With their AI-powered capabilities, they are able to simulate human-like conversations and assist customers with finding products, answering questions, and guiding them through the purchasing process.

A key advantage of chatbots is their availability 24/7, allowing customers to receive assistance at any time of the day, reducing wait times and improving the overall customer experience. Additionally, chatbots can handle multiple inquiries simultaneously, reducing the workload of customer service representatives and improving efficiency.

Brands and retailers have several chatbot solutions available, each with its own unique features and capabilities:

  • Tars enables businesses to create custom chatbots without coding experience,
  • while Intercom is a customer messaging platform with a chatbot feature for automating customer support and sales processes.
  • iAdvize, on the other hand, is primarily a conversational platform that enables businesses to connect with customers in real-time through messaging, chat, voice and video, it also offers AI-powered chatbots as part of its suite of services.

Personalization Engines

Personalization engines are becoming increasingly popular in e-commerce as a way to deliver tailored experiences to customers based on their past behavior and preferences. These AI-powered engines can analyze customer data, such as browsing history, search queries, and purchase history, to provide personalized recommendations, promotions, and content.

One advantage of personalization engines is that they can scale personalization across a large customer base, which can be difficult to achieve manually. Personalization engines can also help businesses stay up-to-date with changing customer preferences and behavior, which can be challenging to do without AI-powered tools.

Some examples of personalization engines for e-commerce include:

  • Optimizely allows brands and retailers to create personalized experiences across various channels, including web and mobile.
  • Emarsys is a Vienna-based marketing platform that offers a suite of personalization tools based on AI and machine learning.
  • Evergage is a personalization and customer data platform that allows businesses to deliver real-time personalized experiences across multiple channels.

Visual Search

Visual search is a rising technology in e-commerce that aids customers in finding products based on images rather than text. AI-powered tools use machine learning to analyze images and identify similar products within a catalog, enhancing the user experience and boosting sales by quickly finding products that match preferences.

Visual search helps customers find products they may not find using text-based search. It allows uploading an image of a product that a customer might not know the name of or how to describe. Visual search also reduces abandoned searches and increases conversions.

E-commerce companies have access to a variety of visual search tools, each with unique features and capabilities:

  • Visii is a visual search platform that uses AI to help customers find products that match their preferences. It is based in London, UK.
  • Slyce (now part of Syte) is a visual search platform that allows businesses to integrate visual search into their mobile apps and websites.
  • ViSenze provides intelligent visual recognition and search functions for e-commerce, including Search by Image, Product Recommendation, Out of Stock Alternatives, and Automated Product Tagging.

Predictive Analytics

Predictive analytics can be used to forecast future trends and identify opportunities for growth. This can help brands and retailers make better decisions and stay ahead of the competition.

Predictive analytics is an AI-powered technology that uses statistical algorithms and machine learning to analyze historical data and forecast future trends. In e-commerce, predictive analytics can help companies make better decisions by identifying opportunities for growth and helping them stay ahead of the competition.

Predictive analytics can help identify patterns and trends that may not be evident through manual analysis. With predictive analytics, customer behavior can be analyzed, and patterns indicating potential successful products can be identified.

E-commerce companies have access to multiple predictive analytics tools:

  • Netrivals is an AI-powered pricing and product intelligence tool that uses machine learning to analyze large volumes of data and provide businesses with real-time insights into the market and their competitors.
  • Google Analytics is a web analytics service that provides companies with insights into their website traffic and user behavior.
  • Hootsuite Insights is a social media analytics tool that uses AI to provide brands and retailers with insights into their social media performance.

Recommendation Engines

Recommendation engines can be used to suggest products to customers based on their past behavior and preferences. This can increase sales and customer satisfaction.

AI-powered recommendation engines analyze customer behavior to personalize the shopping experience and suggest products likely to be of interest, boosting sales and satisfaction. They help overcome choice overload by suggesting a smaller set of products, increasing the likelihood of a purchase.

There are various recommendation engines available for brands and retailers:

  • Amazon Personalize is an AI-powered platform that provides businesses with real-time personalized recommendations.
  • Boomtrain is a machine learning platform that allows companies to deliver personalized content and recommendations across multiple channels.
  • Reflektion is a platform that uses AI to deliver personalized content and product recommendations across all touchpoints.

Fraud Detection

Fraud detection tools can be used to identify and prevent fraudulent activity, such as chargebacks and identity theft. This can protect e-commerce companies from financial losses and damage to their reputation.

Fraud detection is an essential aspect of e-commerce security, as it helps businesses protect themselves and their customers from fraudulent activity. Fraud detection tools are AI-powered technology that uses machine learning algorithms to analyze data and identify patterns that indicate fraudulent behavior. By using fraud detection tools, brands and retailers can protect themselves from financial losses and damage to their reputation.

Numerous fraud identification tools are accessible to e-commerce enterprises, each with unique characteristics and abilities:

  • Signifyd is a platform that provides e-commerce businesses with real-time fraud detection and prevention.
  • Sift is a platform that uses machine learning to analyze user behavior and detect fraudulent activity.
  • Riskified is a platform that uses machine learning to analyze data and identify patterns that indicate fraudulent behavior.

Inventory Management

Inventory management tools can be used to track and manage inventory levels, orders, and shipments. This can improve operational efficiency and reduce costs.

Inventory management is a crucial aspect of running an e-commerce business. The ability to track and manage inventory levels, orders, and shipments in real-time is essential to ensure that customers receive their orders on time and that the business can operate efficiently.

By using inventory management tools, companies can monitor inventory levels and reorder products when needed, reducing the risk of stockouts or overstocking. These tools can also help businesses track sales trends and forecast demand, enabling them to make informed decisions about future inventory levels and product offerings.

Two real-life examples from the report “Emerging AI and Data Driven Business Models in Europe“: Otto, a German retailer and marketplace, accurately predicts 90% of products sold within 30 days. Schneider Electric uses an AI model to forecast optimal acquisition and transportation methods, reducing needs significantly for 240 manufacturing facilities and 110 distribution centers worldwide.

There are various inventory management tools available for brands and retailers:

  • Skubana is a platform that provides e-commerce businesses with real-time inventory management, order fulfillment, and shipping management.
  • Fishbowl is a platform that integrates with popular e-commerce platforms to provide real-time inventory management and order fulfillment.
  • Cin7 is a platform that provides e-commerce businesses with centralized inventory management, order management, and accounting integration.

And What About ChatGPT and E-commerce?

ChatGPT is a language model that is designed to simulate human-like conversations and generate responses based on the input it receives. While it can be used for various purposes, including e-commerce, it is not a standalone AI tool that is specifically designed for e-commerce applications.

In e-commerce, chatbots are typically used to provide customer support, answer product-related questions, and guide customers through the purchasing process. While ChatGPT can simulate conversations and generate responses, it is not optimized for these specific use cases and may not be as effective as a dedicated e-commerce chatbot solution.

That being said, ChatGPT can still be useful in e-commerce for generating product descriptions, customer reviews, and other content. Additionally, it can be integrated into other AI tools and e-commerce platforms to enhance their capabilities and provide a more personalized experience for customers. Learn everything in this article.

Get in touch with e-commerce experts!

Adrian Gmelch

Adrian Gmelch is a tech and e-commerce enthusiast. He initially worked for an international PR agency in Paris for large tech companies before joining Lengow's international field marketing & content team.

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