Top 20 AI in eCommerce Use Cases & Applications in 2024
The global market of AI in Ecommerce is expected to hit $45.72 billion by 2032. Artificial Intelligence is tremendously reshaping our daily shopping experience. Gone are the days when customers had to wait in queue for the customer support executive to attend to their query. Now, AI chatbots can literally solve them anytime, anywhere, within just a few clicks.
Not just this, customers no longer need to search for their offline favourite product online manually. All they need to do is click a picture of the product and use AI’s visual search feature to get a list of the exact product along with some similar products.
Furthermore, there are offline stores with absolutely zero staff. Sounds surprising, right? But, it's true. What are the top use cases of AI in Ecommerce? This detailed blog post on the top 20 applications of AI in Ecommerce is all you need to know how AI is transforming the Ecommerce industry for both businesses and customers.
20 Best AI in eCommerce Use Cases and Applications
Below listed are the top 20 use cases of AI in Ecommerce.
1. Personalised Search
One of the best use cases of AI in eCommerce can be seen in how Amazon uses AI to provide personalised search. If a customer attempts to shop by using the Amazon search bar, there's as much as 42% probability that a successful purchase will happen. AI-powered search engines, also called insight engines, carry out this kind of conversion in a finger's snap.
AI can easily record a customer's on-site behaviour and product of interest. Using the recorded data and past purchases, AI-native search engines reflect customers with the products that they exactly or closely want to buy. By prioritising such individual preferences, AI can turn a bounce into a sale.
Through AI-first search, brands can multifold their sales and customer retention rate by providing customers with selective products driven by real-time customer behaviour.
2. Personalised Product Recommendations
Around 67% of American citizens expect brands to send them relevant product recommendations. AI can fulfil this customer demand without sweat. By collecting tons of user data like online customer behaviour, past orders, cart products etc., AI can send attractive and personalised product recommendations to people. Companies like Decathlon use AI algorithms to send emails and offer alerts and pop-ups to customers to direct them towards a purchase.
AI-run chatbots can lead customers to explore similar products related to their current interests so as to let them explore a wide variety of products across a company’s page. Product recommendations through these chatbots increase RPV (Revenue Per Visitor), and profit margin and also prioritise cart abandonment rate.
3. Ai-Optimised Pricing
One of the best customer-oriented use cases of AI in eCommerce is price optimisation. Around 60% of customers go for the products with the best saving offers. Therefore, many companies use AI to record and compare their products to that of their competitor's pricing strategy.
Further, using AI, companies like Relex predict the demand of their products and change their prices accordingly to increase their sales. This entire process is called dynamic pricing. Using AI for price optimisation, a brand can also predict at a certain price range, which of its products will sell more and which of its products will demand a price cut. This kind of advantage through AI tools gives companies an extra edge over their potential competitors.
4. Image Tagging and Recognition
AI-powered image tagging and recognition represent a breakthrough in artificial intelligence, enabling systems to identify and classify objects and scenes within images with remarkable accuracy. Through training on extensive datasets of labelled images, AI algorithms achieve proficiency in recognising and categorising visual content, paving the way for a multitude of applications.
According to a recent report by Grand View Research, the global AI-powered image tagging and recognition market is expected to reach $25.1 billion by 2028, growing at a CAGR of 23.5% from 2022 to 2028. The increasing use of AI-powered picture tagging and identification technologies by a variety of industries, such as e-commerce, social media, healthcare, and security, is responsible for the market's expansion.
One of the best use cases of AI in Ecommerce is how social media giants like Facebook and Instagram leverage AI to automatically tag people, objects, and scenes in photos and videos. This streamlines content sharing and discovery, enriching user experiences on these platforms.
Furthermore, in the field of medical imaging, AI-powered image tagging and recognition are revolutionising diagnostic tools. Algorithms can accurately identify tumours and abnormalities in MRI scans and X-rays, surpassing human capabilities and improving diagnostic accuracy.
5. AI-Generated Product Descriptions
Customers buy products being influenced by their descriptions, and hence, creating quality content describing a product is one of the primary priorities of almost all eCommerce companies. However, it takes around 18 months to create 10000 product descriptions, but with the help of AI, 18 months can be reduced to just a few hours.
AI-powered content generation tools can provide attractive and informative descriptions with potential to push customers to make a purchase. It is also possible for a brand to create dynamic descriptions of its products that appeal to individual interests to a great extent. AI-generated descriptions almost contain all the valuable data like a product’s features, benefits, lifespan and many more. In fact, Amazon saves a lot of time and makes a huge profit out of AI-generated product descriptions.
6. Self-Checkout Systems
One of the most advanced use cases of AI in eCommerce takes us to the recent popularity of self-checkout systems at many retail stores. Using Ecommerce chatbots, stores are now going for self-checkout systems to regulate crowds easily and, at the same time, increase the scope of sales. Walmart has already installed many AI-handled self-checkout systems at its stores.
These systems are well-equipped with webcams, card readers, facial recognition and digital payments which makes shopping easier and quicker for the customers. These systems can also recognise any kind of fraud activity during the checkout process.
7. Conversion Rate Optimisation (CRO) Testing
E-commerce sites undergo various data-driven tests to optimise their conversion rates. The methods involved in this testing, such as multivariate testing, A/B testing, and multi-armed bandit, can be operated by AI. Global Market Insights, in its recent report, forecasted the CRO market to exceed $61 billion by 2025. This growing market offers opportunities for all e-commerce businesses by incorporating AI.
AI can efficiently handle these tasks using its data analysis and predictive capabilities. Manual optimisation of conversion rates is less efficient and has limited potential for scalability. AI-enabled CRO testing can perform better by testing multiple variations and predicting future performance more accurately.
8. AI-Based Retargeting
Remarketing in Ecommerce is an unavoidable marketing strategy as it contributes to brand awareness and conversion rate optimisation. In retargeting, AI can take the lead in reaching targeted ads to customers who have previously visited your website but have not converted yet.
It is surprising that only 2% of online visitors complete their purchase on their first visit to an ecommerce store. According to SharpSpring, there is a 70% chance that retargeting ads will bring back a completed purchase. Incorporating AI will streamline the process. AI can interpret browsing patterns, shopping behaviour, and past visit records to create more effective retargeting ads. The data-driven approach of AI can deliver more personalised retargeting ads to customers, which increases ROI and conversion rate.
One of the biggest players who use AI for ads and retargeting is Airbnb. Their AI studies the user behaviour and targets personalised ads for their non-converted visitors.
9. Customer Service
Hubspot stats say that almost half of customer service experts trust AI and chatbots in understanding and responding to customer queries effectively. The best part about integrating AI chatbots for Ecommerce customer service is their 24/7 availability; customers can get their queries resolved anytime, anywhere, without waiting in a queue for a human agent.
Moreover, with conversational commerce and AI agents, customers feel like interacting with a real human. Besides humanised interactions, these AI-powered chatbots and conversational AI agents are now enhanced by emotional intelligence, ML, NLP, and NLU capabilities.
Now, chatbots can handle complex customer queries efficiently thus providing them instant solutions to their problems. They offer personalised support in multiple languages.
The sports goods retailer giant, Decathlon faced a tremendous increase in customer queries by 4.5 times during Spring 2020. With the integration of conversational AI, Decathlon created and launched its own virtual assistant. This digital assistant was capable of handling over 1000 customer questions thus automating 65% of them and reducing support costs for the business.
10. Retail Analytics
With AI in analytics, Ecommerce businesses are gaining a deeper insight into customer behaviour, preferences and needs, which is crucial for the success of a business. AI not just provides customer insights but focuses on all aspects of a business including inventory and supply chain management too.
Today, human analysts no longer need to spend hours decoding data and coming up with valuable insights. Artificial Intelligence is there to help them out and make their tasks easier, efficient and more accurate. Instead, it analyses the various dimensions of a particular data set, thus coming up with multiple unique and valuable real-time insights.
This is especially useful for Ecommerce businesses for tailoring their marketing efforts and strategies accordingly to increase sales and revenue. It's also crucial to identify loopholes, pain points, and opportunities that affect the decision-making process of a business.
One of the best examples of this use case of AI in Ecommerce is Zara using AI-generated retail analytics to align its production stats along with the demand forecasts. This helps this Ecommerce clothing giant produce sufficient goods while avoiding overproduction and prolonged out-of-stock situations.
11. Campaign Analysis
Gartner’s report states that AI-powered campaign analysis is projected to have a global market of $3.2 billion by 2025. AI can easily analyse campaigns and their results, thus providing businesses with valuable insights into the effectiveness of marketing strategies.
One of the best applications of this use case of AI in Ecommerce is Google Analytics. It's the most common web analytics platform that uses AI to analyse website traffic and identify insights into campaign performance. Google Analytics assists companies in monitoring the effectiveness of their marketing initiatives and pinpointing opportunities for enhancement.
12. Review and Forum Moderation
Almost 93% of customers find it mandatory to check reviews before making an online purchase. Reviews are marketing tools; however, negative and fake reviews can hugely affect the sales of a business. The catch here is that managing tons of reviews is a daunting task, where AI can be a helping hand.
AI-Powered tools can be used to detect harmful content, review it and help to remove them. A similar application of AI in Ecommerce can be seen in Google PlayStore. Google uses AI to detect fake ratings, bad content and incentivised ratings. Google's anti-spam machine learning systems can enable users to receive genuine ratings and reviews for an application.
13. Marketplace Moderation
Fake products of original brands are always flooding the market. Almost every big brand is suffering from this issue. Artificial Intelligence can contribute its role in spotting fake products and help the customer to choose the genuine one. Big brands like Nike, Adidas and many other luxury brands are losing billions of dollars every year due to counterfeit products.
Alibaba is one of the biggest Ecommerce marketplaces for many luxury brands. They have incorporated AI to verify product authentication. They claimed their A technology can detect the logo of a luxury brand in less than 50 milliseconds. AI can check the logo of a product under multiple parameters like shapes, colour, size, spelling angle, etc.
14. Inventory Planning
Artificial intelligence in Ecommerce can be used to automate inventory management effectively and productively. From providing real-time data analysis to effortless demand forecasting by understanding current trends and customer behaviour, they are dominating the sector in various ways.
Besides, predictive analytics helps decision-makers to detect loopholes and opportunities, thus helping them make better decisions. Not just this, AI in Ecommerce for inventory planning can be used to automate the routine tasks thus reducing human labour and freeing up employees for more creative tasks.
According to a report by McKinsey, businesses with AI in their operations and inventory management reported a reduction in their logistics costs by 15%. They also improved their inventory level by 35% and service levels by 65%.
The well-known Ecommerce player, Amazon, uses this application of AI in Ecommerce for demand forecasting, production and optimising the storage and delivery of products. This has helped them by reducing their delivery times significantly, thus leading to improved customer satisfaction rates.
15. Automated Warehouses
One of the best use cases of AI in Ecommerce is automated warehouse management. Artificial intelligence in Ecommerce helps optimise and streamline the routine and monotonous warehouse operations thus reducing human labour and chances of errors associated with it.
Furthermore, AI offers cloud-based communication, which facilitates real-time and faster communication in comparison to human operatives. It also optimises inventory planning and management, thus ensuring that the right amount of resources are utilised in the right amount.
Not just this, it also automates the employee training and logistics processes thus improving their productivity and efficiency. Automated vehicles, drones and online employee training programmes are some of the common applications of AI in Ecommerce.
AI robots and automated systems can easily locate and navigate various warehouse aisles and automate ground processes such as picking and sorting basic inventory within the warehouse.
16. Customer Segmentation
Customer segmentation allows businesses to offer personalisation as they have categorised their customers. According to a report, treating a segmented customer can lead to a conversation rate of 50%. AI can manage a huge pile of data and segment them under various categories.
Artificial Intelligence can help to select a particular target group for a specific goal of a marketing campaign. It is easy to manage real-time data of customers under AI supervision without any hassle. The data segmentation will also help AI to analyse the data to identify patterns and behaviours of customers.
Starbucks, Netflix, Amazon and KFC, like big brands, use AI for customer segmentation. It helps them to track them, and personalised marketing.
17. Lead Generation
Brands can really take the help of AI tools to identify, engage and nurture leads at a large scale which will help them connect with more prospects and that too with a greater efficiency than the former times. AI can easily automate data analysis, lead nurturing and many other time-consuming tasks that were earlier done manually. Companies like Sephora are, therefore, saving a lot of time to focus on other high-value activities by leaving lead generation on AI.
As AI is capable of generating high-quality leads, companies can expect a better return on investment from their lead-generation efforts. AI filters these high-quality leads from other leads by carefully analysing demographics, behaviour and previous communications. In the current marketing segment, using AI-powered chatbots is probably the best way to generate promising leads.
18. Lead Scoring
AI-driven lead scoring method accurately uses loads of data and algorithms which omits any chances of error. By assessing leads continuously, AI ensures that only promising leads are taken into account and no low-rank lead is pursued in the meantime. Also, by processing customer interactions, historical data and demographic details, AI creates successful lead conversions.
On top of that, by seamlessly integrating with CRM (Customer Relationship Management), AI ensures that lead scores are always available to the marketing team. AI lead scoring also reduces the gap between sales and marketing departments. Lastly, as AI lead scoring accurately identifies the most promising leads, it indeed increases the revenue of a company. Companies like Salesforce Einstein take advantage of such AI tools to multiply their conversion rates.
19. Improves Cybersecurity
The average cost of a data breach is close to 4 million USD and that's why many companies are investing in AI-powered Cybersecurity systems. AI can easily detect, analyse and take necessary actions against any cyber threat. By sifting through tons of data, AI can precisely locate any kind of abnormal activity like a new zero-day attack.
On top of that, AI can also help in automating many security processes like rerouting traffic or alerting the IT team in case of any potential issue. As AI functions faster than any human security system, it reduces the response time to security incidents, which in turn lowers the cost of defence against cyber attacks. No doubt Amazon invests significantly in AI for data security purposes.
20. Interactive in-store experiences
Do you find AI chatbots and assistants just in online stores? You must have seen them in offline stores too. Today, we have shopping malls and stores with absolutely zero ground staff and maximum customer satisfaction. How is this possible?
The answer to the above question is AI. From assisting customers in their offline buying journey via robots or digital assistants to self-checkout systems, this is how AI is revolutionising the Ecommerce industry. Besides personalised product recommendations, it can easily provide product descriptions along with a detailed comparison with similar products.
Nevertheless, if your favourite product is out of stock, you can reorder it right from the store with a few clicks and grab it from the counter seamless and simple! Thus, the use cases of AI in Ecommerce extend beyond online shopping to create a more interactive experience for shoppers in offline stores too.
Conclusion
In today's Ecommerce industry, AI has been a truly tremendous driving force. From automating routine customer interactions to providing valuable customer insights based on collected data, the list of use cases of AI in Ecommerce is never-ending. With big industry giants such as Amazon and Etsy leading the adoption of various use cases of AI in Ecommerce, it's not more a trend but a crucial business integration for maximising efficiency and productivity.
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