Artificial intelligence solutions continue to transform all types of businesses (legal, financial, agriculture, transportation, and logistics). However, retail and e-commerce have the highest adoption rates for AI products.
Chatbots, computer vision, machine learning, NLP, and image and speech recognition solutions are some examples of AI in e-commerce that help companies in various ways. Businesses earn more, keep costs down, and automate multiple processes. This article is about the market for these products and the 15 best examples of their practical use.
Table Of Contents:
- AI In E-Commerce: 15 Examples You Should Know
- Current State Of AI in the E-Commerce Market
- 15 Best Examples Of Using AI In E-Commerce
- 1. Customer Support
- 2. Personalized Shopping
- 3. Improved Content Creation
- 4. Lead Generation
- 5. Voice Search
- 6. Visual Search
- 7. Sentiment Analysis
- 8. Demand Forecasting and Management
- 9. Price Optimization
- 10. Logistics Optimization
- 11. Customer Segmentation
- 12. Fraud Detection
- 13. Image Recognition
- 14. Virtual Fitting Rooms
- 15. Retention Strategies
- Conclusion
Current State Of AI in the E-Commerce Market
In 2022, e-commerce, fintech, and online media platforms were the biggest adopters of AI solutions. The latest Statista findings show that 84% of this sector either seriously considers or actively works to use artificial intelligence products. According to a report published by Precedence Research, in 2022, AI in the e-commerce market reached $5.81 billion and is expected to rise to $22.60 billion by 2032.
Businesses cite increased revenue as one of the primary reasons for implementing AI products. 79% of the latest McKinsey survey respondents said that adding tech into sales and marketing made them more money. Among them, 50% claimed to have used AI to improve at least one business area. While the results vary, enterprises look at an average of 20% additional revenue through AI integration.
15 Best Examples Of Using AI In E-Commerce
1. Customer Support
Most modern platforms invest in generative AI e-commerce products like chatbots and virtual assistants to deliver around-the-clock customer support. Advanced AI solutions answer questions about products, services, and company processes, letting support agents handle only the most complex tasks.
Companies invest in adding AI chatbots and virtual assistants due to compatibility with existing products and systems. These products improve the overall customer satisfaction, allowing them to increase sales over time. According to the latest survey by Salesforce, 23% of companies already use chatbots, with another 31% planning to do so.
2. Personalized Shopping
Modern artificial intelligence solutions gather data about the customer shopping experience. The most popular AI in e-commerce examples find information about website browsing history, purchase logs, and favorite product categories to deliver product recommendations specific to a buyer’s current and future needs.
Understanding a person’s tastes and preferences allows e-commerce companies to improve their chances of cross-selling and upselling items. Statistics published by Zipdo show that personalized recommendations provided by AI tools account for up to 30% of all revenue of e-commerce platforms.
3. Improved Content Creation
Companies use artificial intelligence solutions to make different types of creative content. They mimic the brand voice, words, and phrases the company uses. One of the most common examples of AI in e-commerce is products that tailor marketing content, such as web ads, emails, and social media posts, to keep the talk going about the business.
Advanced AI products have multilingual support, allowing them to localize content for international markets. They also help optimize search engine company rankings. Having the AI tools make content with the right keywords saves time and resources for e-commerce businesses.
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4. Lead Generation
Artificial intelligence solutions collect information on all visitors, new and old. They see how these people behave on the platform and their favorite products to create tailored advertising content. A timely recommendation with a generative AI e-commerce tool makes a person more likely to buy.
In addition to monitoring website engagement, AI tools scan social media platforms for conversations about the company and its products. This data is later used to engage customers the next time they visit the platform or approach them with offers based on the nature of their posts or conversations.
5. Voice Search
Many e-commerce businesses rush to equip their platforms with voice assistants. These AI-in e-commerce examples offer a more personal and efficient shopping experience. Customers use their smartphone or webcam microphones to search for the items. This way, they have a better chance of finding suitable options and making more informed decisions.
Amazon, Walmart, and Google Shopping have this feature and have seen great results from its integration. The use of voice assistants has drastically affected the field of e-commerce. Among e-commerce clients, 22% prefer using voice assistants instead of typing, with another 26% of respondents claiming that these tools are easier to use.
6. Visual Search
Image search provides an additional opportunity for clients to find the right items. People upload pictures and photos of related items, and the power of AI guides them through the search. It also raises the chances for cross-selling and upselling, as visual search results may offer previously undiscovered alternatives. Using another input type makes users more engaged in the selection process and spend more time on the platform. This leads to higher conversion rates and chances of them purchasing.
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7. Sentiment Analysis
Artificial intelligence solutions help e-commerce companies better understand the opinions customers have about their products. These tools scan client reviews, blog posts, and social media entries to find keywords and descriptions for items or the online store.
This information gathered using AI in e-commerce is divided into neutral, favorable, and hostile. Businesses in the e-commerce sector use this data to address problems with the quality of their products, services, or experience using the online platform.
8. Demand Forecasting and Management
The power of AI makes it easier for e-commerce companies to optimize spending on restocking inventory. Advanced artificial intelligence products analyze market trends and historical buying data. This ensures an adequate stock that meets customer demands based on seasonal trends and helps avoid over or understocking the inventory.
The best examples of AI in e-commerce allow companies to understand when to order items and in which quantity. This leads to happier customers and more profit while saving costs on restocking. McKinsey’s experts have found that AI helps reduce forecasting errors by 30-50%.
9. Price Optimization
Online stores seek to outperform each other by offering the best price on the market. AI technology streamlines this process by automatically evaluating the competition. It looks at the current inventory, market conditions, rivals, and other factors to find prices that will improve sales and profits.
This process leads to better conversion rates, optimizes profitability, improves profit, and keeps customers engaged. According to McKinsey, E-commerce companies can get 3-5% higher revenue from the practice. The figure goes higher, as the price is often a high-priority factor for 60% of clients.
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10. Logistics Optimization
E-commerce companies need to ensure timely delivery of all products. AI products can be integrated into internal systems to track orders better and improve logistics. These solutions provide real-time tracking information and find the best routes for delivery trucks to make faster deliveries.
Their input helps optimize shipment schedules and keep transportation costs to a minimum. Using AI also helps find anomalies and potential logistics disruptions, allowing companies to address emerging issues before they become a problem.
11. Customer Segmentation
Modern AI solutions analyze customer information to better segment the audience of e-commerce companies by demographics, behavior, and preferences. This information allows companies to create more tailored marketing campaigns for different parts of the client base and show them the most relevant promotions with the help of generative AI e-commerce products.
12. Fraud Detection
AI products help e-commerce companies detect fraudulent activities. They scan for payment irregularities and suspicious actions, allowing businesses to quickly identify potentially high-risk transactions, prevent them, and notify clients about these suspicions.
Doing so helps companies avoid losing money and shows that they care about the financial safety of their customers. This allows businesses in this area to save around $40 billion a year in funds lost on fraudulent chargebacks.
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13. Image Recognition
The image search capabilities of AI products go beyond scanning entire images. Some solutions allow selecting areas in photographs and using them to find similar products. In addition to finding matching products, AI algorithms provide buyers with recommendations based on color, size, shape, brand, and fabric.
14. Virtual Fitting Rooms
Advanced AI solutions allow customers to try items before buying them. Products with AR technology get their measurements and overlay items on users’ videos and photos. This shows buyers how these items will look on their figure and if they fit. It also helps e-commerce companies reduce returns.
US retail chain Walmart offers this virtual fitting experience through its mobile app. With its help, clients upload their photos to get personalized virtual fits. In addition to Walmart, Amazon, Zara, and even Nike offer this immersive experience to their clients.
15. Retention Strategies
Modern AI solutions conduct client analysis to provide e-commerce companies with better retention strategies, such as promotions and loyalty programs. With the help of AI tools, it's possible to identify users who are about to stop shopping with the company and reduce churn risks.
Businesses also use AI analysis for client reviews, feedback, and surveys. Information gathered from these sources helps improve the quality of daily services and offered products, leading to higher retention rates.
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Conclusion
AI will continue to be one of the main driving points in the e-commerce market. Its applications have become integral to various company processes, and users will demand to see more of this technology in the future. In the meantime, businesses will continue to invest in having the best types of AI products across all of their selling channels.
