What Is AI in Ecommerce?
AI in ecommerce is the use of artificial intelligence in ecommerce businesses. Ecommerce is not just about having an online store today. It is about creating a smooth online experience and a smooth purchase experience — from the moment the customer lands on a website till the after-sales services.
Artificial intelligence is taking part in every customer touchpoint in ecommerce and retail. It processes large amounts of data, recognizes patterns, responds to customers' needs, and helps customers in every step of their journey. Retailers and ecommerce shop owners are seeing cost reduction, higher conversion, and better customer satisfaction scores with the introduction of this technology.
AI-Powered Customer Support
One of the biggest challenges of ecommerce businesses is handling customer queries. Customers often contact for trivial issues, which are expensive for businesses to handle with manual efforts. For example, they ask about order status, returns, refund policies, product availability, and more.
AI chatbots are solving this problem effectively. Chatbots are available 24 hours a day without any break. They answer all kinds of repeat questions from customers, which is saving at least 70% of human work hours. Below are ways chatbots impact retail:
Giving updates about order tracking and status
Initiating return and refund requests
Providing product information and availability checks
Store location and hours information
Queries about discounts and coupons
FAQ handling
Shipping and delivery information
Chatbots are intelligent enough to connect customers with a live agent if the query is complex. They also provide the agent the full context of the conversation so that the agent can provide better service.
Personalized Shopping Experience
Today's ecommerce is no longer one size fits all. We experience personalized product recommendations on ecommerce platforms. Ecommerce marketplaces remember our behavior, our interaction pattern, and provide recommendations based on this. That is AI working in the background to provide better support.
It considers data to provide better personalized support. For example:
Browsing history
Past purchases
Search behavior
Time spent on a certain page
Therefore, the recommendations today's ecommerce websites and platforms are providing us are much better and personalized. For example, a customer who regularly searches for running shoes may be shown a fitness tracker in the recommendation section. AI already recognizes that there is a high chance that the customer might be interested in this kind of product.
Personalized Recommendations
AI personalization is not limited to recommendations only. Below is how AI is providing better personalization in ecommerce:
Personalized communication — Sending the right message to the right customer at the right time
Pricing — Adjusting prices based on demand, purchase history, and customer type
Homepage — Showing different content to different visitors based on their behavior
Instant discounts — Offering discounts instantly to the right customers for better conversion
It all happens automatically, within seconds, without involving any human labor.
AI Voicebot for Better Customer Service
Not every customer prefers chatting online. People in Bangladesh often prefer calling when they have a problem. AI voicebots can play a big role here. Voicebots are AI-powered systems that can understand spoken language and respond just like a human agent.
Below is how a voicebot can impact ecommerce and retail:
Greeting callers and understanding their needs
Providing updates about orders using the phone number and order ID
Processing simple refund requests
Transferring calls to the right department
Imagine a customer calls a fashion seller about a return. The voicebot receives the call and requests the order number after understanding the needs of the customer. The customer responds and provides all necessary information. The voicebot pulls the details from the backend data and initiates the return process. It saves time, and human agents can focus on more complex issues.
Inventory and Supply Chain Management
Running out of stock can cause lost sales for ecommerce businesses. AI helps businesses prevent out-of-stock situations and provides better forecasts. It uses historical sales data, seasonal trends, promotional calendars, and many other factors to forecast how much stock the retailer needs.
For example, an electronics retailer uses AI to predict demand for headphones. AI predicts that the retailer needs three times more products before the holidays. The system automatically alerts the procurement team two months before the season starts.
Below is how AI helps in inventory management:
Identifying slow-moving products
Providing better forecasts on inventory
Tracking supplier performance
Flagging upcoming delays
Reducing overstock and wastage
Fraud Detection and Secure Transactions
Ecommerce fraud is a growing problem worldwide. Fake accounts and stolen credit cards are becoming challenges for online retailers. AI is helping to detect fraudsters and monitoring transaction patterns. AI can flag suspicious activities by using different internal and external factors.
For example, if a customer's account suddenly places high-volume orders from an unusual city, a fraud detection system can flag this as unusual behavior. It blocks the transaction and sends a verification request.
AI fraud detection is faster and more accurate than rule-based systems. AI learns from new fraud patterns and provides a personalized algorithm for each customer based on their buying behavior and activities. It protects both the retailers and the customers and helps build long-term trust.
Smarter Product Discovery
Finding the right product online sometimes becomes difficult due to the large number of products available. We sometimes get lost because there are many options. It becomes more difficult if the customer does not know the exact name or category of the product.
AI provides visual search to solve this problem. A customer uploads a photo of a product they like, and AI finds a similar one from the retailer's catalog by analyzing the picture.
For example, a customer sees a pair of shoes on social media. They take a screenshot of the shoe and upload the photo on the retailer's app. AI suggests similar options available. The customer gets the discovery instantly without spending much time searching.
Post-Purchase Customer Support
The customer journey does not end at checkout. After the purchase, customers may need help on different issues. AI plays a critical role here. It helps retailers stay connected with customers so that they can have a better experience. Below are a few ways AI helps here:
Sending automated and personalized order confirmations
Providing shipping updates from time to time
Proactive notification of delays before the customer reaches out
Collecting post-purchase feedback through automatic surveys
Identifying customers at risk and providing them personalized offers to prevent churn
For example, a customer bought a coffee machine a few months back. AI recognizes that the customer may need a refill pack. It sends the customer an automated email with a special discount offer. The customer has a high chance of accepting the offer because it is fully customized based on their actual need.
Conclusion
We have covered a few key uses of AI in ecommerce and retail. It is still evolving and reshaping the whole process. Generative AI, virtual try-on, and shopping assistants are a few examples that are also creating a better purchase journey for customers.
In today's landscape, retail businesses that want to grow, reduce costs, and keep customers happy — AI is no longer optional. It is essential for contact centers, ecommerce processes, and ecommerce systems for building better relationships with customers and creating memorable customer experiences.
