AI in Ecommerce: Personalization, Fraud Detection, and More

The advent of AI in eCommerce has transformed how eCommerce businesses feature and sell their products online and interact with customers. In this article, we explore how using AI in eCommerce has opened up new possibilities that allow businesses to gain insights, optimize operations, offer exceptional and personalized experiences, and drive growth. We'll also unravel some of eCommerce's most impressive AI use cases, its benefits, and eCommerce AI tools businesses can use.

Until recently, the term Artificial Intelligence (AI) has long been used to refer to a novel technology often featured in movies and books, set in a dystopian future where advanced technology dominates every aspect of human life. However, with each passing day, AI is increasingly becoming an integral technology that affects our personal lives and how businesses operate, and the commerce sector is no exception. The advent of AI in eCommerce has transformed how eCommerce businesses feature and sell their products online and interact with customers.

In this article, we explore how using AI in eCommerce has opened up new possibilities that allow businesses to gain insights, optimize operations, offer exceptional and personalized experiences, and drive growth. We’ll also unravel some of eCommerce’s most impressive AI use cases, its benefits, and some of the eCommerce AI tools that businesses can use.  

6 benefits of using AI in eCommerce

The use of AI for eCommerce has opened up many opportunities and brought convenience to customers who rely on online shopping platforms in many ways. From personalized product offers to fraud prevention, here are some benefits businesses can get from using AI in eCommerce.

1. Improves product recommendations and offers

A typical online shopper is shown hundreds‌ to thousands of products across different online eCommerce platforms, social media, ads, and other platforms. Without product recommendations, it’d take a customer a couple of hours to skim through the many products you’re offering just to find one that matches their needs and preferences. Recently, recommendation systems have become indispensable tools in the eCommerce industry, allowing businesses to make personalized recommendations.

Users are more inclined to ‌buy an item ‌if the product they seek is displayed immediately. This can translate to more sales for your business and increased return customers.

2. Increased customer retention and loyalty

There are many ways eCommerce businesses can leverage AI to reduce customer churn rates. To begin with, using AI personalization in eCommerce allows businesses to offer personalized experiences, directly improving customer satisfaction. ‌Besides AI personalization in eCommerce, Natural Language Processing (NLP) will enable businesses to automate customer support, answer inquiries, and provide information in real-time through AI-powered chatbots. 

Through data analysis, businesses can also predict demand and prepare inventory and shipping to avoid customer frustrations when demand surges.

3. AI has made eCommerce safer

As the eCommerce industry grows, so does the number of malware and security breaches targeting millions of users who rely on online shopping. The use of AI in eCommerce has shown great promise in countering cybersecurity threats that plague the eCommerce industry. Here’s how: 

  1. AI-powered tools can analyze massive data points precisely, making them more effective in identifying potential threats that may disrupt your eCommerce software. Sometimes these threats may not be obvious to the human eye.
  2. AI has also improved basic authentication and authorization capabilities such as email and password authentication. Businesses can now identify their customers more accurately using advanced AI authentication methods such as facial recognition, biometrics, and voice recognition.
  3. Using AI, businesses can now identify and prevent malicious communications such as spam emails with attachments likely to cause a susceptibility. Using AI for eCommerce also allows Cybersecurity teams to manage and resolve threats faster.

4. Enhanced customer service

The new era of AI has ushered in a set of AI-powered tools that have enhanced customer service.

  1. Intelligent chatbots: AI-powered chatbots can answer frequently asked questions and inquiries, improving the overall response time. Chatbots can also provide personalized product recommendations and help with orders, returns, and refunds.
  2. Sentiment analysis: using AI-powered tools, businesses can now analyze customer data at scale, understand customer preferences, and make data-driven decisions to improve service.
  3. Virtual assistants: Virtual assistants are voice-enabled and AI-powered applications that allow customers to make inquiries, track orders, and make purchases using voice commands. This promotes accessibility and convenience.

Through AI eCommerce, businesses can personalize customer interactions, provide real-time order tracking and notifications, automate returns and refunds, and more.

5. Increased productivity

With AI, eCommerce businesses can offer 24/7 availability and support, allowing their employees to shift focus from mundane tasks to high-value ones. 

  1. Automation of repetitive tasks: AI has allowed businesses to automate tasks such as data entry, inventory management, and order tracking.
  2. Streamlined logistics: Using AI-powered logistics systems allows eCommerce businesses to improve operational efficiencies by optimizing delivery and allowing them to track shipments more accurately.

Automated AI tools such as chatbots and virtual assistants enable businesses to handle customer inquiries automatically, reducing the need for an army of customer support agents.

6. Reduction in operating expenditure

Reducing expenses incurred in running an eCommerce business from day to data can save money and boost profits. With AI, businesses can cut expenditures in many ways: 

  1. Automating routine tasks: Automating repetitive tasks, such as data entry, inventory management, order processing, and customer support, can help businesses reduce labor costs.
  2. Efficient inventory management: optimizing inventory management using AI for eCommerce can save businesses storage costs, stockout costs, obsolescence costs, and ordering costs.

Using AI, businesses can identify inefficiencies in their logistics and supply chains. Fixing bottlenecks in the supply chain can reduce expenses such as warehousing and transportation.

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Highly effective use cases of AI in eCommerce

1. Personalized product recommendation

Personalization in eCommerce refers to curating your product offering listing to match every customer’s specific needs and preferences. While personalization isn’t entirely a new concept in eCommerce, using AI in the process has made the entire process much easier and possible at scale.

AI personalization in eCommerce refers to using AI technologies to understand customer characteristics based on past behavior. Here’s how AI personalization in eCommerce works:

  • Businesses leverage the power of machine learning algorithms to analyze huge amounts of customer data such as browsing activity, past purchase data, customer feedback, and reviews.
  • Based on this data, the algorithms establish correlations, patterns, and similar characteristics among users.
  • Through continuous learning, evaluation, and improvement, the algorithms can segment users based on their preferences and needs.
  • Recommendations are then tailored and presented to ‌users based on their interests and preferences.
  • AI personalization in eCommerce enables users to easily discover products they like increasing the probability of them making a purchase.
  • AI personalization in eCommerce also enables businesses to increase conversion rates, customer shopping experience, and loyalty.

Amazon recommendation system

Amazon, the world’s largest online retailer, is one of the brands using personalization in their eCommerce platform. The feature duped “customers who bought this item also bought” offers personalized product recommendations based on a user’s purchase history and activity. 

2. Dynamic pricing

Dynamic pricing is a strategy that involves adjusting the prices of products and services based on certain prevailing market conditions. Before the adoption of AI for eCommerce, dynamic pricing was possible within a limited scale through time-based pricing, rule-based approaches, and promotional offers. With the advent of AI eCommerce, it is now possible to implement dynamic pricing at scale based on many parameters. Here’s how it works:

  • Machine learning algorithms analyze huge amounts of data such as market trends, sales data, competitor data, and many more, drawing key insights.
  • Based on the analysis, the algorithms recommend and predict the best pricing strategies for your business.
  • Unlike traditional dynamic pricing strategies, AI algorithms have the ability to learn and adjust pricing in real-time.
  • Dynamic pricing algorithms are more flexible and can be adjusted to fit different strategies.
  • Dynamic pricing allows eCommerce businesses to personalize pricing by offering different prices, promotional offers, and discounts to different customer segments.
  • AI dynamic pricing also allows eCommerce brands to maximize profits when demand is high.
  • Through dynamic pricing,  eCommerce businesses can adjust prices to remain competitive and boost customer loyalty.

Besides the Airline industry, dynamic pricing is now increasingly popular in the eCommerce industry. Amazon has one of the most robust dynamic pricing strategies, with some credible sources reporting that Amazon changes 2.5 million times a day. Amazon’s dynamic pricing strategy is based on different factors, including shopping patterns, inventory, profits, and competitor prices.

Amazon dynamic pricing

3. Smart chatbots and virtual assistants

Traditional means of offering customer support via emails and calls are flawed. First, offering support when your product scales to thousands of users is almost impossible without hiring an army of customer support agents. Secondly, it is impossible to offer personalized support to customers needing an instant and unique response to their inquiries. 

The advent of AI-powered smart chatbots and virtual assistants has revolutionalized customer support. Unlike traditional means, these AI systems can offer instant and personalized customer support on inquiries. Here’s how they work:

  • AI-powered chatbots and virtual assistants use Natural Language Processing to understand human input and respond in a human-like manner.
  • Unlike human beings, they can offer 24/7 support,  significantly increasing response times and improving customer satisfaction.
  • Based on recent customer data, such as recent purchases and feedback, chatbots and virtual assistants can offer personalized interactions.
  • They have abilities beyond answering customer queries like making orders, providing recommendations, offering track orders, and other post-purchase support.
  • Smart chatbots and virtual assistants can help eCommerce businesses improve customer satisfaction and retention.
  • Using these AI power support systems can also save eCommerce platforms human labor costs. 

Sephora, a leading French beauty and personal care products brand, is one of the early adopters of AI-powered chatbots. Customers can get instant support or instantly book a makeover in a Sephora store through its Sephora chatbot for Messenger.

Sephora chatbots

4. AI-enabled inventory management and demand forecasting

Proper management of inventory is key to the success of any eCommerce business. Demand forecasting is also key as it allows you to understand what and when to restock a given product and by what amounts. Poor management of inventory ultimately leads to losses and frustrations for customers. AI-enabled inventory management is a popular AI use case in eCommerce that helps brands forecast demand accurately and avoid overstocking or understocking. Here’s how it works: 

  • Machine learning algorithms analyze data, including sales data, market trends, weather, and other economic factors, and predict demand accurately.
  • Based on the insights and predictions made from the data, businesses can then make data-driven decisions on how to manage their inventory.
  • Real-time analysis of data and changes in demand allows businesses to respond in time to avoid issues such as stockouts.
  • AI-enabled inventory management and demand forecasting enable eCommerce businesses to avoid wastage, increase operational efficiency, and reduce storage costs.
  • With AI, eCommerce businesses optimize product sorting and supply chain operations, increasing customer satisfaction.

Walmart, a leading multinational retail store, leverages AI heavily to enhance its inventory and supply chain operations. For instance, using Brain Corp’s AI-powered autonomous scrubbers, Walmart can take millions of images of items across its stores, guaranteeing that items that customers want to buy are always in stock.

Brain Corp’s AI-powered autonomous scrubbers in Walmart

5. Fraud detection and prevention

The rising popularity of eCommerce platforms, especially during the Covid-19 pandemic, has also led to the rise of fraud in eCommerce platforms. These fraudulent activities have particularly targeted new users and those not so tech-savvy on these platforms. Different types of fraud occur on eCommerce platforms, including credit card fraud, account takeover, affiliate fraud, triangulation fraud, etc. 

Due to the sheer volume of these activities, eCommerce platforms are turning to AI to help curb them. Fraud detection is one of the common AI use cases in eCommerce. Here’s how it works:

  • AI algorithms, unlike human beings, can analyze huge amounts of data, including transaction data, customer behavior, historical data, and device information, and identify legitimate transactions
  • Similarly, AI can watch and analyze data and flag transactions that could‌ be anomalies or fraudulent.
  • ECommerce businesses can use AI eCommerce to set up notifications whenever fraudulent activity is detected.
  • By using AI to counter fraudulent activities, eCommerce businesses reduce financial losses and protect their customer data and brand reputation.

Tips for AI personalization in eCommerce

AI personalization in eCommerce has become a crucial technology that businesses rely on to deliver personalized shopper experiences. Regardless of your AI use case in eCommerce, AI eCommerce has the potential to drive sales, improve customer satisfaction, and promote brand loyalty. However, if done poorly, it can also harm your eCommerce brand.

Here are some tips to help you kick-start your AI personalization journey in your eCommerce business.

Collect as much customer data as possible

Without enough data, creating a personalized experience for your customers is almost impossible. Data forms the basis for understanding your customers’ behaviors, needs, and preferences. Many sources can be used to gather different data points about your customers.

Some sources that eCommerce businesses can use to collect customer data include social media interactions, demographics, website interactions, purchase history, customer feedback, and many more. Remember that data collation isn’t a one-off excise but a continuous process that requires tracking to ensure that data remains accurate and relevant.

Show items that your customer will like

Personalized product recommendations are one of the key concepts of the eCommerce industry. Using AI in eCommerce has made it possible to use customer data to precisely understand every customer’s preferences.

Showing your customers products that they’re more likely to be interested in increases the likelihood of conversions and repeat purchases and increases customer satisfaction. 

Leverage predictive analytics and machine learning

Besides using data to understand the current needs of your customers, you can also leverage the power of machine learning algorithms in predictive analytics to anticipate customer needs. With predictive analytics, eCommerce businesses can make personalized changes beforehand in anticipation of new customer needs.

Predictive analytics can also help you predict future purchase intent and know which products to recommend. Businesses can also predict customer churn risk and take the necessary steps to avoid this. With predictive analytics, eCommerce businesses can also estimate the potential lifetime value of every customer, optimize pricing, and analyze sentiments to offer personalized support. 

Test and refine your personalization strategies

To stay ahead in the ever-competitive eCommerce industry, you must continuously test and refine your personalization strategies. The eCommerce industry is very dynamic, which means that the customer preferences of the modern customer change from time to time, and it’s also important you adjust your strategy to ensure that you’re delivering the right experience to the customer.

You can employ several tactics to evaluate and optimize your personalization‌. For instance, you can conduct A/B tests, listen to customer feedback, measure key performance indicators for your strategies, and use these insights to iterate and optimize.

Implement personalized customer loyalty programs

Customer loyalty programs can increase customer loyalty and encourage repeat purchases. Using customer data such as purchase history, preferences, feedback, and engagements, you can create personalized customer loyalty programs, discounts, and rewards for your customers. 

Once you’ve collected and analyzed data to understand what your users want, you can segment them into groups based on their preferences.

Based on these groups, you can offer rewards, discounts, and exclusive perks. For instance, you can incentivize customer reviews or repeat purchases. With these programs, you can establish long-term loyal customers and drive business growth.

5 eCommerce AI tools: from chatbots to fraud detection

1. Kimonix

Kimonix Homepage

Kimonix is an all-in-one AI-powered eCommerce merchandising software that enables businesses to execute an ROI-based merchandising strategy. With Kimonix, your business can access key metrics, manage customer preferences, and inventory all in one place. 

Key use cases:

  • Tailoring product displays, collections, and landing pages to your shoppers’ unique preferences.
  • Monitor sales data, inventory, and customer engagement statistics to understand your products better.
  • Built-in A/B testing feature to test your strategies and product collections to optimize profitability.
  • Built smart, automated collections with templates for new arrivals, sales, best sellers, and more. 
  • AMS sorting engine to create a sorting strategy for your collections.

2. Homepage

An AI eCommerce and marketing software that enables businesses to personalize their user’s shopping experience. With Clerk IO, businesses can automatically analyze behavioral and transaction data and trends and provide real-time recommendations to help them grow sales.

Key use cases:

  • Intelligent search engine for eCommerce.
  • Personalized product recommendations.
  • 1:1 personalized communication via email with high-converting email triggers.
  • Powerful and easy-to-use customer segmentation to help you find the perfect product for your audiences.
  • Next-gen personalization AI dubbed ClerkCore, designed for modern eCommerce sites.

3. Insider homepage

Trusted by over 1200 leading brands, Insider is the leading AI eCommerce platform for creating individualized, cross-channel customer experiences. With Insider, brands can use data across different channels to predict future customer behavior.

Key use cases:

  • Optimize customer onboarding to make a good first impression.
  • Build one-to-one engagements through SMS.
  • Integrate with popular CMR and email marketing solutions.
  • AI-powered smart recommender to help you improve conversion and click-through rates.

4. Sniffie

Sniffie Homepage

Sniffie is an AI-powered eCommerce dynamic pricing and price optimization software. Using Sniffie, eCommerce businesses can determine the most effective product price points based on historical data and sales volume.

rack competitor prices and optimize and automatically adjust their prices in bulk to maximize profitability.

Key use cases:

  • Optimizing prices for higher profit margins and revenue.
  • Automated price monitoring and price changes to stay ahead of competitors
  • Easy-to-use dashboard for managing all your pricing-related data.
  • AI-driven tool to help you manage pricing and discounts during a sales campaign.
  • Integration with popular eCommerce platforms, product information management systems, or ERP.

5. ClearSale

ClearSale Homepage

ClearSale is the leading eCommerce solution that aims to help businesses protect their revenue in online businesses and create better customer experiences. ClearSale works for both small businesses and large enterprises alike. 

Key use cases:

  • Integrates with proprietary eCommerce software solutions such as Shopify.
  • End-to-end chargeback management services.
  • AI technology that analyzes and reviews orders and flags suspicious activities.
  • Expert consulting services for eCommerce.
  • Custom fraud solutions for enterprise clients. 


AI use cases in eCommerce have no doubt revolutionized the eCommerce industry. The use cases are limitless, from personalized product recommendations to smart inventory management, fraud detection and prevention, personalized communication, and more. However, as AI usage in eCommerce continues to grow, businesses should also recognize the importance of the human touch and transparency in how they handle customer data as key factors in establishing customer trust. While at it, you can also unlock the potential of your online store by embracing the 10Web WooCommerce automated hosting solution for smooth performance, high cart performance, and scalability. Reach out to us and learn how we can help you migrate your store to 10Web hosting.


What are the potential security and privacy risks of using AI in eCommerce?

The use of AI in eCommerce presents limitless possibilities but also many security and privacy concerns. Some security concerns when deploying AI for eCommerce include data breaches, potential bias, and unethical use of data.

How much does it cost to integrate AI into your online shop?

The cost of integrating AI into different AI use cases in eCommerce depends on many factors. Some costs involved may include ‌infrastructure, labor, tools and software, regulation, and maintenance costs.

What is the future of AI in eCommerce?

The future of eCommerce holds immense potential. Some trends to look out for include advanced hyper-personalization, Augmented Reality (AR), and Virtual Reality (VR).
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