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Get ready to explore cutting-edge AI technologies that can transform your workflow!
eCommerce emerged as one of the fastest-growing segments in the last few years, as many people preferred online shopping over visiting malls or physical marketplaces.
eCommerce has been growing steadily over the years, with new players entering the market every year. However, global giants like Amazon, eBay, and Alibaba still hold a significant share of the ecommerce space.
Artificial intelligence is making its presence felt in all walks of life, whether in defence, healthcare, aviation, or eCommerce. From virtual reality to artificial intelligence, technology keeps pushing the limits of what eCommerce can offer.
Let’s dive straight in to find how AI is transforming user experience in ecommerce platforms and core use cases.
eCommerce platforms are thriving like never before, and they make use of the latest technology for building their mobile application, for logistics, payments, and customer service. Here, we focus on the use of AI technology by eCommerce apps to improve User Experience(UX).
AI tools can collect and process customer data about their online shopping journey. This can be used to offer personalized product recommendations based on past behavior and lookalike customers.
eCommerce stores that recommend items based on purchase history & profile, use Machine Learning to deliver a personalized experience and generate customer insights.
With the advancement of Artificial Intelligence technology, deep levels of personalization have started revolutionizing the eCommerce world. AI engines, like Boomtrain, keep a watch on top of multiple customer touch points.
No matter whether it is a mobile application, website, or email campaign, the AI engine continuously monitors all devices and channels to create a universal customer view. This customer view helps eCommerce firms in delivering seamless customer experience across all channels.
More Reading: DoorDash uses Machine Learning and Optimization Models To Enhance Customer Experience
Virtual Assistants & Chatbots are transforming User Experience on eCommerce platforms. These bots cannot completely replace customer care executives as of now, but they take care of routine queries & complaints. This can free up time for executives to deal with more complex tasks.
These AI-enabled bots are available 24X7 and can handle thousands of customers at the same time, improving Customer satisfaction.
Natural Language Processing(NLP) is another AI technology that can interpret voice to interact with customers.
Other alternatives, such as contact forms, emails, and phone calls, are not as efficient as chatbots. As the latter option is the fastest and more convenient way for customers to get answers.
Efficient inventory management is all about maintaining the right level of stock that can meet consumer demand without adding to idle inventory.
While earlier, inventory management was based on current stock levels, AI-enabled Inventory management is based on:
Along with managing inventory levels, AI is also being used for warehouse management. Automated robots are also being increasingly used as they can be used 24X7, unlike human employees, to store or retrieve stocks.
Digital humans are human-like personas powered by AI technology who create a dynamic and life-like experience to connect with consumers. They are capable of conversing like real humans using Deep Learning and Natural Language Processing.
Digital Humans imitate the personality, voice, and nature of brands they have been created for. These bots are capable of emoting happiness, warmth, friendliness, and empathy. They can crack jokes and even show support through their body language.
For example, if a user logs in for the second time for his/her purchase, it can recognize current user emotion with what it was earlier.
The advantage they provide is they create a human touch, which is necessary to build lasting relations with consumers.
Any eCommerce platform will not like fake reviews to show up on their web pages and apps. Here is when AI can help them in weeding out fake reviews.
Fake reviews are known as ‘astroturfing,’ and it is widespread on eCommerce, including Amazon. It is defined as the practice of creating or spreading false reviews that a potential customer would trust as a neutral, third-party testimonial.
Customer reviews have become the benchmark of trust in eCommerce, where customers cannot physically see the products before purchase. Thus, customer reviews and ratings, who have bought and used the product, play a significant role in the success of the product.
Amazon uses AI to tackle fake product reviews and the inflation of their star ratings. AI machine-learning system is used to boost the prominence and weight of verified customer purchase reviews.
Like fake reviews, attributes such as product, brand, and category can be used to spot counterfeit products. For a consumer, it will be difficult to identify counterfeit products in an eCommerce store.
However, if the customer buys a fake product by mistake, it can leave him disgruntled and with a negative perception of the eCommerce store.
Machine Learning Algorithms can be used to spot counterfeit products. eCommerce AI systems can collect data from multiple online stores and analyze it to spot counterfeit products.
Factors such as the posting rate of an account, the kind of items on sale, and even fake reviews of listed items, can be used to identify counterfeiters.
Genuine clients can submit claims with eCommerce companies to get counterfeit products removed.
AI can be used to identify the location of consumers and accordingly suggest products or services. This prevents the customer from getting overwhelmed with recommendations.
As a result, consumers can make faster decisions and with more confidence. So, it is a win-win situation for both the consumer and the eCommerce company itself.
AI-enabled eCommerce platforms are also expected to answer questions of customers like “Where can I go for rock climbing on my birthday?”
AI systems can make personalized recommendations based on your profile, history, and previous purchases for points of interest that you never knew existed.
Sometimes shoppers don’t know the right words to search. They may see a product on Instagram, in a movie, or on the street, but can’t describe it properly. This is where AI-powered visual search improves the ecommerce user experience.
With visual search, users can upload an image or click a photo. AI analyzes the image, understands patterns, colors, shapes, and styles, and then shows similar products instantly. This removes friction from the buying journey.
For ecommerce platforms, visual search:
AI in ecommerce visual search is especially useful for fashion, furniture, and lifestyle brands, where visuals matter more than text.
Pricing plays a big role in user experience. If prices feel unfair or outdated, customers leave. AI-driven dynamic pricing helps ecommerce platforms adjust prices in real time based on demand, user behavior, competitor pricing, and market trends.
Instead of fixed pricing, AI analyzes large data sets and suggests the best possible price at that moment. This benefits both businesses and users.
With AI-powered dynamic pricing:
This use of artificial intelligence in ecommerce helps platforms stay flexible while offering better value to users.
Writing product descriptions for thousands of products takes time. AI solves this by creating AI-generated product descriptions that are clear, consistent, and user-focused.
Using natural language processing, AI understands product features and converts them into easy-to-read descriptions that highlight benefits, not just specifications. These descriptions can also be optimized for ecommerce SEO.
Benefits of AI-generated descriptions include:
This directly improves the shopping experience by helping users understand products faster and make confident purchase decisions.
Not all users behave the same way. Some browse, some compare, some buy instantly. Predictive customer segmentation using AI helps ecommerce platforms understand these patterns better.
AI analyzes user data such as browsing history, purchase behavior, time spent on products, and preferences. Based on this, it creates smart customer segments automatically.
With predictive segmentation, ecommerce platforms can:
This makes the user feel understood, not marketed to. And that’s a big win for the ecommerce user experience.
AI in ecommerce is not just a future concept. It is already being used by leading platforms to improve user experience, increase conversions, and reduce operational effort. Here are a few practical use cases that show how artificial intelligence is shaping modern ecommerce platforms.
Many ecommerce platforms use AI to recommend products based on user behavior. AI analyzes browsing history, previous purchases, search patterns, and even time spent on product pages. Based on this data, it suggests products that match the user’s interest.
For example, Amazon uses AI-driven recommendation engines to show personalized product suggestions across its homepage, product pages, and emails. This helps users discover relevant products faster and reduces the effort needed to search manually.
For ecommerce businesses, AI-powered product recommendations lead to higher engagement, better conversions, and increased average order value.
AI chatbots are widely used in ecommerce to handle customer queries in real time. These chatbots can answer common questions related to order status, returns, payments, and product details without human intervention.
Many Shopify merchants use AI-powered chatbots to manage customer support, especially during high-traffic sales periods. These bots provide instant responses, even outside business hours.
By offering real-time assistance, AI chatbots improve the overall shopping experience. Customers get quick answers, and businesses reduce support workload and response time.
Visual search is commonly used in fashion and lifestyle ecommerce platforms. Users can upload an image or click a photo, and AI finds similar products available on the platform.
Platforms like Amazon and Pinterest use AI-powered visual search to help users find products based on images instead of text. This is especially useful when shoppers don’t know how to describe a product accurately.
Visual search improves product discovery and helps users reach purchase decisions faster, leading to better satisfaction and higher intent to buy.
Large ecommerce platforms use AI-driven dynamic pricing to adjust product prices in real time. AI considers factors such as demand, user behavior, competitor pricing, and market trends before suggesting price changes.
For instance, Amazon frequently uses dynamic pricing to update product prices based on market conditions. This allows the platform to stay competitive while offering relevant pricing to users.
For customers, this creates a sense of value and transparency. For businesses, AI-based dynamic pricing improves revenue optimization and pricing efficiency.
At Techugo, we help ecommerce businesses turn advanced technology into real user value. As a leading ecommerce app development company, we combine AI expertise with deep product understanding to build user-focused ecommerce platforms.
Since 2015, Techugo has successfully delivered 1,400+ mobile and web applications across industries. We have also developed 50+ AI-powered solutions. Our experience spans global markets, including the UAE, USA, Australia, and other regions that allow us to build ecommerce apps that align with diverse user behaviors and market expectations.
Techugo designs ecommerce solutions that are future-ready, secure, and built for growth, whether its AI-driven product recommendations or smart chatbots.
Get a FREE roadmap for your AI-powered ecommerce app. Talk to Techugo today.
The cost of building an AI-powered ecommerce app depends on multiple factors. These include the type of ecommerce platform, number of features, level of AI integration, data complexity, platform choice (iOS, Android, web), and long-term scalability needs.
For basic AI features like chatbots, personalized product recommendations, or smart search, the development cost usually starts lower. Advanced AI capabilities such as visual search, predictive analytics, dynamic pricing, and custom AI models increase the overall investment.
A well-defined AI roadmap helps control costs, prioritize features, and ensure long-term return on investment.
AI in ecommerce will continue to grow beyond basic automation. In the coming years, ecommerce platforms will use AI to deliver even more personalized and predictive shopping experiences. Voice-based shopping assistants and real-time hyper-personalization will be common. AI will help brands understand user intent more accurately.
We will also see greater focus on ethical AI, data privacy, and transparent recommendations. As AI becomes more advanced, ecommerce platforms will shift from reactive systems to proactive experiences. It will help users find products even before they start searching.
If unsure, get a 45-min free consultation with our experts. Contact us now.
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