Learn the benefits and challenges of applying AI to online businesses to prepare for the future of online shopping.

1. Some types of AI commonly used in E-commerce

AI is not a single technology, it includes many different models. In e-commerce, there are 4 leading types of AI used: 

• Natural language processing: A type of artificial intelligence that focuses on understanding and generating human language. E-commerce businesses are using this type to improve chatbots. This helps customers get answers to product questions faster and more accurately. 
• Machine learning: Uses statistical techniques including algorithms to allow computers to filter data to make predictions or decisions without being explicitly programmed. 

• Computer vision: Is an artificial intelligence technology that allows computers to recognize and interpret information from images and videos. 
• Data mining: Most of these businesses have rich data sources to mine. AI tools can help collect, analyze, and leverage this data to generate actionable information.

2. Benefits of businesses using artificial intelligence

While AI is still in its infancy, the potential business applications are becoming clear. For e-commerce businesses, as the online shopping experience continues to evolve, the use cases for AI are becoming more numerous and clearer.

• Better targeting in marketing and advertising: AI can mine data to understand the type of customers you are reaching and how best to connect with them. By creating better customer portraits, marketing content and product descriptions can improve, and sales can increase.
• Customer retention: AI can help businesses better understand who their online shoppers are and what motivates them to take action. This will also help shape how businesses engage with existing customers in the future. Customer support and customer satisfaction are common areas where AI is helping online retailers improve the user experience. 

• Automation: Adopting automation means optimizing your business operations. Identifying routine tasks that can be solved with digital solutions allows employees to perform more specialized tasks. AI opens up new avenues for automation to support manual tasks that were previously untapped.

• Efficient sales process: AI can be used to identify sales trends and modify predictions as appropriate for the business. AI goes beyond historical data and extends to real-time predictions, where machine learning then refines and perfects the process.

Read more: What Companies Need to Know Before Investing in AI Technology

3. 7 applications of AI in e-commerce 

3.1 Personalized product recommendations

Using AI trends is revolutionizing the e-commerce, websites can personalize the customer shopping experience by recommending products based on their purchase history, preferences, and behavior.

This not only helps improve customer loyalty but also increases sales. AI can also look at search engine queries to better engage new, potential customers. 

3.2 Chatbots and virtual assistants

Act as customer support agents for your e-commerce business. They help you resolve customer queries and facilitate online shopping by advising customers. Businesses should use chatbots and virtual assistants to:

• Create efficient interactions with customers: They can handle simple transactions, process orders and provide offers to customers, making it easy to address various requests from customers quickly.
• Collecting data from customers: Chatbots and virtual assistants can collect data from customers to provide information for businesses to improve product development and customer service.

• Speed ​​up the checkout process: Businesses can integrate a checkout page into their chatbot so customers can easily ask for product details, quantities for popular items, or shipping information without leaving their shopping cart.
• 24/7 Customer Service: Customers can get quick responses 24/7 from chatbots, allowing live support staff to spend time solving more complex issues. AI can help your business reduce costs by automatically resolving disputes and processing refunds.

3.3 Fraud Detection and Prevention

AI can assist in detecting and preventing fraud by analyzing data, detecting anomalies, and monitoring transactions in real time. The technology can detect unusual transactions, such as high-value transfers or multiple transactions in a short period of time from unfamiliar locations, and flag them for further investigation.

Additionally, businesses can also use machine learning models to create user profiles based on behavioral data such as browsing habits, transaction history, and device history, and then compare current consumer behavior with historical data to verify fraudulent behavior.

3.4 Inventory Management

AI tools can analyze sales data and predict future customer demand, helping you be more proactive in inventory management. It can also automate the inventory replenishment process by integrating with suppliers to ensure on-time shipping. 

3.5 Flexible pricing

Dynamic pricing allows you to adjust prices and offers based on real-time user behavior, supply and demand, and competition. With AI predictions, you can optimize discounts and determine the minimum discount needed to drive a successful transaction.

AI brings more flexibility to product pricing. By leveraging AI, businesses can dynamically adjust prices based on observed supply and demand or price match their competitors to ensure customers always get the best deals.

3.6 Predicting customer loyalty

AI opens new doors for e-commerce businesses to gain deeper insights into their customers and uncover new trends. Analyze how customers interact across sales channels and provide insights for optimization when there is more data from consumers.

Machine learning can help businesses predict and reduce churn by identifying these risks early. First, AI can collect data on customer churn metrics like abandoned carts, incomplete product information, or website bounce rates. Then, you can automate purchase completion emails, loyalty discounts, and abandoned cart follow-ups, making it easier to encourage customers to complete their purchases. 

Read more: 5 IT Outsourcing trends businesses need to pay special attention to

4. Some challenges when integrating AI into e-commerce

Besides the benefits for e-commerce, when businesses integrate the use also brings many challenges such as:

• Protecting personal data: AI algorithms need a lot of customer data to make personalized suggestions and predictions. Collecting this data raises concerns about customer data privacy. There is also a risk of data security loss, information leakage and intellectual property infringement when attacked by hackers.
• High initial investment costs: Implementing AI integration into business operations requires a significant amount of cost, ranging from investment in infrastructure to recruitment and maintenance. If not applied effectively, these solutions sometimes do not bring as high economic benefits as expected.

• Poor customer service: When using AI in business operations, chatbots will take on the role of customer support, so sometimes they cannot provide support and empathy like humans. If not implemented well, this service can backfire, causing customer dissatisfaction and damaging the reputation of the business.

Artificial intelligence is evolving but is not yet fully developed. E-commerce companies that adopt AI technology may be leading the trend, but they still need to prepare for the challenges they may encounter.

Regardless, in the long run, AI solutions could fundamentally change the way e-commerce works. Understanding this now will help you be better prepared for the future of online shopping, no matter where it goes.