AI-Powered E-Commerce The Top 10 Apps to Enhance ROI
In recent years the impact that transformative technology has had on Artificial Intelligence (AI) and Machine Learning (ML) in the world of e-commerce is now evident. AI/ML systems enable marketers to analyze large quantities of data, make precise predictions, and streamline processes. In the end, AI/ML has discovered a variety of applications in marketing in eCommerce that range from personalizing user experiences to enhancing supply chains.
Presently, we are witnessing the rapid introduction of AI/ML, as technologies are evolving and users get more familiar. With the availability of these tools and their easy usage, the widespread adoption of AI and ML-driven software is becoming unavoidable.
Types of Commonly-Used Technologies
We have grown accustomed to hearing and imagining AI as an all-in-one tech. It’s a popular term for a variety of models. However, that’s not the scenario. When it comes to eCommerce there are four most prominent AI/ML-based technologies which are commonly employed:
- Natural Processing of Language (NLP): This kind of AI enables computers to recognize, help, and alter written or spoken words in the same way that humans can.
- Machine Learning (ML): Machine learning is a general term used to describe the problem-solving capabilities of computers that imitate human are taught to “discover” their algorithms.
- Computer Vision (CV): Computer vision is a branch of artificial intelligence that aids computers in processing, acquiring, analyzing, and comprehending video or digital images.
- Mining of Data: Data mining collects data and discovers patterns within large data sets to provide AI algorithms and systems.
- Deep Reinforcement Learning: It’s a subfield of ML that integrates reinforcement learning (RL) and deep learning. RL is a study of a computer-aided agent learning to make choices through trial and trial.
The Top 10 Ways AI Transforms eCommerce
Utilizing AI/ML for e-commerce marketing can provide a broad variety in competitive benefits that could boost the productivity and effectiveness of retail stores that operate online.
As technology improves the benefits of AI/ML will be more apparent and AI/ML will become an indispensable tool for eCommerce companies seeking to succeed in a highly competitive market.
Below are the top ten methods of using AI/ML to improve the performance of your online business.
Personalized Product Recommendations
The most prominent use of AI/ML in the world of eCommerce that we have personally experienced is personalizing product suggestions. According to a Forbes Insights report personalization has a direct impact on the effectiveness of sales, basket size (the amount of products that a customer purchases within a transaction), and profit margins in D2C distribution channels.
AI/ML algorithms can be used to analyze a user’s purchasing and browsing historical data, demographic information, and real-time behavior to recommend products that are most suitable for their needs. This personalized approach enhances the shopping experience and dramatically increases conversion rates and sales.
Flipkart for instance utilizes AI/ML to improve the efficiency of its business in many ways including algorithmic use to provide personalized recommendations for products to customers. This improves customer engagement and increases sales.
In the same way, BigBasket employs AI/ML to make custom shopping lists for its users, i.e., Smart Basket which offers suggestions based on past purchases and your preferences regarding the price and quality.
Powerlook used the WebEngage Recommendation as well as Catalog Engine to solve for the absence of specific recommendations for users on their site. Based on a user’s purchasing information, their outfits and other preferences for clothing recommendations were made to customers 15 days after the date of their last purchase. The products and options were recommended based on their shopping record. The results, a 30% increase in unique conversions, speak for themselves.
Similar to how it was able to aid Powerlook and WebEngage, the WebEngage Catalog Engine and Recommendation can bring value to your company by allowing you to create specific recommendations for your customers.
Predictive Analytics for Inventory Management
AI/ML-powered predictive analytics assist eCommerce companies in optimizing the management of their stock. It is able to analyze the historical data on sales as well as seasonality, market trends as well as external factors such as weather. The algorithms can use these analyses to forecast demand with incredible precision. This assists retailers in reducing the problem of understocking and overstocking and results in cost reductions and increased customer satisfaction.
The industry of fashion eCommerce has to keep up with fashion trends to be successful and thrive, will greatly benefit from predictive analytics. AI/ML systems can provide important information to fashion brands by identifying patterns and offering greater insight into fashion trends and purchasing behavior, as well as inventory information.
One great example could be Myntra. Utilizing AI/ML to analyze the data of fashion websites as well as social media and Myntra’s database of customers they were able to determine which products were most popular and make sure that they were accessible in their application. This is why Myntra launched collections more quickly than its competitors.
Chatbots and Virtual Assistants
Artificial Intelligence (AI/ML)-powered chatbots and virtual assistants are gaining prominence in customer service in the world of eCommerce. They can answer commonly asked queries, provide suggestions for products, and can even handle orders. The AI-powered systems work 24/7, providing better customer service, decreasing the time to respond, and boosting customer satisfaction.
For example, Flipkart’s Decision Assistant chatbot makes use of a variety of methods to comprehend what is “human thinking” behind a customer’s inquiry and respond to the customer’s needs. The chatbot has improved the company’s metrics for business by decreasing the number of chats transferred to human agents and decreasing the abandonment rate for carts.
Similar to that, Nykaa’s virtual assistant is named one of India’s top AI chatbots, and aids customers make purchases by providing personalized suggestions based on the preferences that the user has expressed. They can avail the benefit of video-chatting with a professional and can help the user locate the appropriate product by itself.
Recently, Myntra’s latest artificial intelligence chatbot, MyFashionGPT, enables users to find, using natural language, the answers to questions such as “I will be going to Goa for a holiday. Let me know what I could dress in .”
Dynamic Pricing
Dynamic pricing is also referred to as demand price or surge pricing also known as time-based pricing is a technique that allows companies to alter the prices of their products or services according to the current market conditions. Utilizing a catalog can facilitate rapid price changes based on variables like competition, demand, and the behavior of customers. For instance, if certain products are sought-after and market conditions alter, the catalog can adjust prices as needed. This allows businesses to remain at a competitive level, boost revenue, and ensure a pleasant shopping experience by coordinating prices with the current market conditions and the preferences of customers.
MakeMyTrip, a travel online retailer, makes use of AI/ML to alter prices in real-time. Customers can get pertinent price information that improves the customer’s engagement. This results in higher retention, lower loss of customers, and more conversions.
Customer Segmentation and Targeting
AI/ML systems help online marketers to divide their client base more efficiently. AI/ML-powered solutions for segmentation remove human bias, uncover patterns that are not obvious, and boost personalization. They’re also highly expandable. Through the analysis of the data of customers, it is able to discern distinct segments of customers under the way they behave, their interests, and demographics.
The predictive segmentation feature can be used to distinguish a suitable customer’s target audience and distinguish them from other customers. This AI/ML feature lets users create segments based on a user’s propensity to take an action.
Predictive segments employ machine learning to determine the likelihood of users undertaking specific actions, such as buying something or leaving. This approach is far more efficient than the traditional method of classifying users as it extends beyond the information and attributes that allow marketers to make more precise predictions about the behavior of users as the world goes non-cookie.
Businesses can design specific marketing campaigns. This kind of lead nurturing will be more likely to lead to conversions than general segmentation that is based on age or area.
To use the segmentation tools for MyGlamm customers, segmentation of their customers based on personas of the users (for instance, the segment that includes all registered users with more than 150 GlammPOINTS on their accounts, but didn’t make a purchase) Utilizing WebEnage’s segmentation tools enabled them to create several different routes for the segments. Affecting their marketing and messages to users, based on what stage they were in, enabled users to engage with their customers effectively.
This led to enhanced user experience, and engagement on the web and in apps as well as the result of a 13.5 percent increase in conversions from customers who received a customized email regarding an item that was in their cart, as well as an increase in 166% in purchases from users who had previously left their cart.
WebEngage’s knowledge of the segmentation of customers was instrumental in helping MyGlamm to achieve these amazing results. WebEngage can assist you as well to gain more insight into your company’s performance using customer segmentation.
Visual Search and Image Recognition
Artificial Intelligence-powered search engines and recognition software allow people to find items by examining images instead of text. The technology can identify and identify products based on images. This makes shopping easier since it lets customers find products they might not be aware of the exact name.
Lenskart for instance, helps customers shop for eyeglasses. The site allows customers to test out frames to determine which pair suits their needs most. This eliminates the requirement for customers to travel to a physical store. The virtual, augmented reality application uses AI to recognize a person’s facial characteristics and create an individual list of glasses that the customer can choose from within 10 minutes. They can try out the styles and give them to their acquaintances for another opinion.
In the same way, Pepperfry allows users to search for furniture as well as furniture items and also provides virtual demonstrations of products. Users can view furniture they have in their homes virtually, allowing them to make informed choices about purchasing.
Fraud Detection and Prevention
eCommerce companies are susceptible to different types that are fraud including account takeovers and fraud on payments. AI algorithms can analyze patterns of transactions and identify irregularities that may be indicators of fraudulent activity. By automatically identifying suspect transactions AI assists in reducing losses, and protects both businesses as well as customers. This usage of AI helps build trust between customers and brands which leads to better customer experiences and increased customer satisfaction.
A good example of a firm that uses AI to detect fraud as well as prevention of fraud is Flipkart. If, for example, the seller chooses to scam the platform manipulate images on the listing, or use fake pictures, the AI algorithms can spot and flag that. This will ensure that buyers get an accurate representation of what they’re looking for.
Email Marketing Optimization
AI/ML-driven email marketing automation tools are game changers for email campaigns. These tools study the preferences of customers and their behavior and can personalize the content of emails and the time to deliver. AI/ML-powered predictive analytics may provide suggestions for products that customers might like, thereby increasing the effectiveness of marketing via email campaigns.
WebEngage’s Generative AI feature lets you design custom emails in no time! Generative AI allows you to create custom-designed templates for messages that take into consideration the preferences of your target audience as well as demographics and behavioral information. This will ensure that your emails resonate with all recipients which results in higher levels of engagement and more conversions.
WebEngage helped Saudi Arabia’s most popular eCommerce label, HNAK, reach a 67% opening rate for abandonment emails from carts. Utilizing features like a drag-and-drop editor for emails assisted HNAK in creating beautiful emails that are mobile-optimized. Additionally, they were able to cut down on the manual work involved in personalizing emails.
Another fantastic illustration of how AI/ML could be utilized to improve the effectiveness of email marketing is from the tale that is Juicy Chemistry which is a D2C Organic skincare line. Collaboration with WebEngage enabled Juicy Chemistry to experiment with segments, channels as well as timings and messaging. This resulted in better engagement as well as more inboxing within non-promotional folders. All in all, Juicy Chemistry was able to attain a 4.5X increase in conversions to email and an increase of 2X in opening rates.
Voice Search and Voice Commerce
With the rise of devices that can be activated by voice, such as Amazon Echo and Google Dot Echo, AI is also helping to facilitate voice-based commerce. By using voice commands, customers can search for items ordered, place orders, or track their order’s status.
One of the ways that Flipkart made use of voice commerce was by introducing ” Hagglebot,” which was a chatbot that let customers bargain to find a better deal during the Big Billion Days Sale promotion. It was a massive success, as the total profits from the products available via Hagglebot exceeded $1.23 million. The average engagement time for the experience was six minutes 5 seconds, which makes it the most engaging Google Assistant experience of the moment.
MakeMyTrip as well is a plan to help make travel planning more accessible and inclusive through the use of voice-assisted bookings for bookings in Indian languages.
Supply Chain Management and Logistics
AI/ML is dramatically improving the effectiveness of logistics and supply chain management for eCommerce businesses. AI helps with the process of route planning and inventory management as well as forecasting demand. This means faster delivery with lower operational costs, better management of inventory, and increased customer satisfaction.
Flipkart’s AI-powered bots called AGVs (Automated Guided Vehicles) for instance, allow human workers to process 4,500 per hour of shipments at double the speed and with 99.9 percent accuracy. The bots also enable the expansion of warehouse capacity and throughput.
Conclusion
As we’ve seen in the above examples, AI has revolutionized the market for eCommerce by offering new, innovative solutions that are geared toward customers. AI helps businesses improve efficiency and increase ROI. From personalized recommendations for products to optimization of supply chain The AI/ML top 10 applications reviewed in this article have evolved into essential tools for eCommerce companies seeking to stay ahead of the pack.
WebEngage has been at the cutting edge of this groundbreaking technology and has made use of the effectiveness of its marketing automation tool to help businesses in eCommerce such as yours attain remarkable outcomes. Request a demo today to learn what WebEngage can do to help you make the most of the game-changing power of AI in the field of eCommerce marketing.
