14 Best Examples of AI in eCommerce [+ Use Cases]

  • 10 min read

The best examples of AI in eCommerce demonstrate how retailers use advanced AI-powered tools to enhance customer experience, optimize data analysis and automate the creation of high quality content. Any task or process made more efficient by artificial intelligence showcases the significant impact it can have on the retail sector. 

In this article, we explore some of the best examples of AI in eCommerce with real use cases, providing inspiration on the benefits of using AI to enhance your business. 

  • Learn how AI-powered tools are changing the eCommerce landscape
  • Get inspired with 14 AI in eCommerce examples, along with use cases
  • Read the benefits that artificial intelligence tools have on eCommerce retailers

How AI is changing the eCommerce landscape

AI tools can be used to speed up and automate processes, significantly lowering costs and efficiently handling tasks that were once managed by humans. As a result, the integration of artificial intelligence is transforming many eCommerce businesses. 

Here are the main ways AI is impacting the eCommerce landscape for retail:

  • Customer interaction

The way consumers interact with retailers has been influenced by AI tools, with intelligent technology that’s now able to have conversations using machine learning. 

A tool that many are familiar with are chatbots, which communicate with consumers and answer questions using a database of pre-programmed responses. While a chatbot may not fully replace customer service reps, they do reduce the need for direct human interaction.

AI voice recognition software also enhances customer interaction through listening and dictation. This also provides retailers with an opportunity to speed up processes, boost user experience and reduce the time needed for an employee to service a customer query.

The list goes on, from personalized content creation to product recommendation and discovery, all of which we explore later on using examples. 

  • Data analysis 

Another way in which AI has massively impacted the retail sector is through data analysis. AI algorithms have the ability to analyze enormous amounts of data quickly and accurately - much quicker than a human. 

The main benefits this has on eCommerce is streamlined reporting and predictive sales forecasting, better understanding different customer segments, and using data on customer behavior to shape strategy. 

Through data analysis, ecommerce businesses can uncover valuable insights to help optimize the business. Whether it’s stock management, marketing budgets or expanding into new areas, AI tools help inform strategic decision making.

  • Content creation

No matter what industry you are in or the type of content you need support with, AI can assist you in writing it. While clear and well-thought-out prompts are necessary, and human oversight is still required to check and refine AI-generated content, AI offers a fast and effective solution for almost all content needs.

Some of the most popular ways retailers use AI content tools are for writing SEO content, product titles and descriptions, advertising copy and organic social content. 

  • General operations

The use of AI in retail can support many other business processes and operations as well. As we will discover, this could include robots in warehouses that help build, sort and pack products. Or visual recognition tools to tackle counterfeiting. Even dynamic pricing tools that considers competitor prices, manufacturing costs and product demand to automatically alter prices in real-time. 

AI integration in retail continues to evolve with new tools that are constantly being developed, offering useful solutions for eCommerce. It's essential that retailers grow with this changing landscape to find solutions that are suitable for them. 

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14 best examples of AI in eCommerce

Let’s explore the best examples of AI in eCommerce, showcasing how new and exciting AI-powered tools and technologies are transforming the industry.

  • Personalized recommendations

The first example of AI in eCommerce in our rundown is personalized recommendations. Recommendation engines use algorithms to analyze large datasets, purchase history and patterns in consumer behavior. Using learnings from the data, retailers can automatically recommend relevant products to consumers, which are personalized to each individual. 

It’s a clever way for ecommerce businesses to spark interest by predicting what a user will be interested in, as well as improve the upselling and cross selling of products. It also helps product discovery by surfacing items that may have been missed by the consumer. 

Online retailer SHEIN, a global fashion brand that sells clothing, accessories and shoes, uses AI to tailor product recommendations to consumers. It happens automatically and users are strategically shown relevant products as they browse. 

 

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For fashion retailers like SHEIN, it’s a great way to increase engagement as well as boost product sales, by showing users items that align with their interests and online behavior. 

  • Product discovery 

Product discovery can be enhanced by AI tools, helping to connect online shoppers with relevant products. This is why it’s a great example of how eCommerce can leverage the power of AI. 

Rather than using consumer behavior to personalized recommendations, product discovery is about making the browsing experience intuitive and engaging. This is so consumers can easily explore and uncover products they might not have initially considered.

Lily AI is a tool that facilitates this function, using artificial intelligence to boost product discovery and conversions for eCommerce. The tool is specifically designed for fashion, home and beauty retailers and Lily AI claims to be the “first vertical AI platform purpose-built for retail”. The sophisticated technology works by using product attributes and matching them with what consumers are looking for.

 

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For example, for fashion retailers this could include analyzing attributes such as fabric, style, detailing and even neckline, to surface relevant products. So if a user is browsing white t-shirts that have a crewneck, Lily AI can show other white crewneck t-shirts that are similar. Similarly for homeware, attributes like product type, color, color family, wood tone and home style can be used. 

  • Image recognition

Number 3 on this list of AI in eCommerce examples is image recognition and tagging. AI tools can be used to analyze images supplied by consumers, in order to provide product recommendations that look similar to the image that’s been supplied. 

A great example of this is social networking site Pinterest, one of the more well known platforms that offers image recognition. It’s possible to select an item that’s shown within an image and use image recognition software to search for similar items. This is particularly handy for consumers because it helps them discover and purchase items they are interested in, but don't necessarily know where to find them. 

 

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For example, a consumer could use a photo of a cream lamp in a living room to find similar lamps from a selection of retailers, purchasing the one they like the most. 

Google Lens is another tool that uses image recognition to help users search using images rather than text. It’s possible to search by uploading an image or by taking a new picture in Google Lens. In the same way Pinterest does it, Google Lens will show similar images to what you have uploaded.  

  • Product descriptions

Generative AI can be used in retail to write and optimize product description text. For large ecommerce businesses that have an enormous inventory of products, this has the potential to save a lot of time and effort in writing them manually. As well as that, AI tools can do it well, writing unique product descriptions that factor in keywords and product details needed to make them relevant and stand out.

This can benefit retailers who need to optimize product descriptions for SEO, for feed-based advertising or to help with the purchase decision. 

There are numerous tools out there that can automate the writing of product descriptions, such as ChatGPT, Ahrefs and Copy.ai. 

  • AI product images  

Another great example of AI-powered tools in eCommerce is AI product images. Although AI tools are not yet advanced enough to produce final product image designs that are ready to go, they are helpful in accelerating the design process. They can give designers a new perspective, the ability to make large edits as well as make small touch-ups to perfect them. 

Specifically for retailers, AI can be used to change up product backgrounds, place products in a new setting or even create lifestyle images to accompany standard product photography. 

 

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One AI product image tool to consider testing out is Dall-E, which is able to generate images from text prompts. Image outputs may need adjusting and refining, and they can be abstract at times, however, the responsiveness of text prompts is highly effective. 

  • Custom Marketing Messages

Another example of how ecommerce businesses can benefit from the power of AI is through customized marketing messages. There are numerous channels in which brands and consumers communicate via message and consumers have grown to expect a customized experience. 

This could include standard marketing communications, such as tailoring email newsletters and SMS updates to individual interests. However, it could also include more sophisticated communications like customizing ad experiences and adding conversational ads into the mix. 

 

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A smart tool that allows retailers to customize SMS messages is Emotive. As well as customizing SMS messaging to consumers, Emotive uses AI to track the engagement of the messages, in order to improve them overtime. 

Emotive claims that their SMS messaging technology can boost conversion rates and ROI, making it worthwhile for retailers looking to nurture and engage their customers. 

  • Pricing Optimization

AI-powered tools can be used to optimize product pricing, something that ecommerce businesses are increasingly bringing into their pricing strategy. Pricing tools are designed to automatically adjust product pricing based on a number of real-time factors, such as competitor prices, changes to manufacturing costs and consumer demand. 

For example, if a competitor selling the same product suddenly drops prices, AI tools recognize this and react to it by automatically lowering your prices, to prevent missing out on a sale. 

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There are also AI tools that facilitate limited-time promotions, which can pop-up on the screen of consumers that show high intent. This type of tool uses statistics and analyzes online behavior to determine who should receive a promotion and when. 

Pricing optimization is another great example of how AI helps to improve the responsiveness of retailers in order to boost sales. 

  • Counterfeit product detection

Counterfeit products are common in the world of retail, which can be extremely damaging to a brand. Not only does it result in the loss of sales, it can also impact reputation since the quality of counterfeit products can be poor. Tackling this by identifying counterfeit products and then removing them has been made easier thanks for AI. Which has earned Counterfeit product detection a spot on this list of the best AI in eCommerce examples. 

 

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One tool in particular is Corsearch, which can be adopted by retailers to detect and remove counterfeits across all online channels using AI, along with their industry expertise. Corseach can quickly find counterfeit products, faster than manually searching for them, and automatically have counterfeit goods removed.

This is a great example of how AI in eCommerce can help retailers safeguard revenue, uphold reputation and maintain the trust of consumers.

  • Inventory management

This next example of AI in retail feels futuristic. Retailers can use AI for inventory management, using it to review and record real-time data on stock levels, whether it’s raw materials or packaged goods. This is achieved through the use of robots and image recognition. 

 

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One tool that offers this service is Fellow AI, using robots kitted out with image recognition technology to provide real-time inventory management. 

The robots travel up and down warehouse aisles and use data-capture cameras to analyze stock levels. Fellow AI operate in the automotive, electronics, healthcare and retail sectors and it’s a great example of how AI can automate and streamline supply chain operations. 

Speaking of robots, another way in which AI robots can be used to enhance the productivity of an ecommerce business is by automating distribution and the supply chain. Again, robots can be incorporated into the distribution process, alongside humans, to help with manual labor and speed up the entire process. 

 

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InVia Robotics offer “award-winning Goods-to-Person warehouse automation” and specialize in automating tasks in the warehouse, claiming to increase productivity by 5 times. The robots are autonomous and they are able to pick products and transport them around the warehouse, working around the clock and reducing the number of staff needed to manage warehouse operations. 

Distribution robots also feel rather futuristic, however, expect to see more of this in the not so distant future. 

  • Product intelligence

Gone are the days of spending hours manually researching industry trends, monitoring competitors, and surveying customers to get insight into buying behavior. Instead, data analytics platforms can do this for you, using artificial intelligence to aggregate and analyze data, providing you with the important insights. 

This is great news for quickly getting product intelligence, for example, knowing what the latest trend is, what influencers are promoting, competitor products and pricing, and so much more. 

ai analytics example

 

Trendalytics offer a product intelligence solution for ecommerce businesses, describing themselves as a personal data scientist helping with strategic decision making. Trendalytics scrape 4 million SKUs on a weekly basis, monitor 20 thousand social profiles and 2.4 million search terms, all of which help create its prediction engine.

All of this insight can be used to help retailers decide what products to invest in and when. In fact, it can help streamline inventory and the entire operation.

  • Customer service chatbots 

Chatbots are powerful customer service tools that use conversational AI, such as natural language processing (NLP), to understand customer queries and automate responses quickly and effectively. 

 

ai powered customer service example

 

They are great for responding to queries, benefitting retailers by operating during non-office hours, handling routine tasks and reducing the workload of customer service teams. 

Popular Chatbot tools include Zendesk, Service Cloud by Salesforce and IBM, all of which use AI to boost customer satisfaction and maximize service efficiency.

  • Fake reviews identification

There are many scenarios whereby fake reviews can get mixed up with real ones, whether it’s ill-natured competitors, unhappy customers or consumers who get brands mixed up. The AI-powered solution to this is fake review identification software. 

 

ai powered fake review detection example

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Fake review software can be used to identify fake reviews through AI technology that analyzes and scrutinizes text patterns, writing styles, and formatting. They are a great way for ecommerce businesses to maintain the integrity of customer feedback, minimizing the harm caused by fake reviews. 

  • AI retargeting 

The final example of some of the best AI tools used in eCommerce is AI retargeting. Retargeting is an age-old advertising strategy that works by reaching past customers, website visitors, or those that have interacted with the brand in some capacity. The aim is to show ads to this warm audience to encourage them to revisit the site and purchase.

AI retargeting takes things one step further. Rather than just using one large segment of users, AI retargeting can build and maintain audiences that are narrower and more defined using customer behavior, browsing history, and other data points. This enables retailers to personalize retargeting ads, which are then more likely to lead to a conversion. 

 

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An example of a retailer that uses AI-powered retargeting is Carrefour Taiwan, onboarding Appier’s AI retargeting solution, which ended up increasing conversion rate by +20%. One of the tactics Carrefour Taiwan used was tailoring coupons based on what a user was browsing, which helped encourage them to convert. 

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Benefits of using AI-powered tools in retail

Here are the main benefits that all of these AI tools have in relation to eCommerce:

Enhanced customer experience

One of the main benefits of adopting AI tools is the enhanced customer experience that comes with it. The personalization from AI algorithms, whether it’s for customer service, product recommendations or content, can impact customer experience in a positive way. An improvement in customer experiences will directly result in happier customers, higher retention and positive reviews and referrals. 

Strategic decision-making

Another benefit to using AI in retail is the vast amount of data that gets analyzed in real-time, providing businesses with actionable insights. This empowers businesses to make strategic decisions around supply chain, operations, marketing and aftercare, as well as help with accurate predictions. 

Analysis of customer data also helps retailers to define accurate customer segments and further personalize marketing campaigns. It links back to enhancing customer experience in that brands can make decisions that have their customer interests in mind. 

Reduce costs and increase ROI

Another benefit AI tools have on eCommerce is the automation of routine tasks that would otherwise have been carried out by a human. This includes things like industry research, data analysis, customer service automation, inventory management and content creation, amongst other things. 

AI-powered tools allow retailers to boost operational efficiency. The streamlining of routine tasks reduces the manual workload that’s required and it also speeds up the completion of many tasks.

Tasks can be completed to a high standard thanks to AI, in a timely manner as well. This results in saving costs, reducing errors, preventing financial losses and ultimately boosting ROI. 

Increased security

Finally, another benefit to adopting AI tools in retail is the increased security that comes with it. Whether you decide to implement fraud detection software, fake review systems or utilize counterfeit product detection, what all of these tools have in common is increased security for your business. 

While there are a vast number of benefits to using AI tools, it’s still important to consider the dangers of AI in advertising as well. Recognizing them can help retailers to avoid these dangers and successfully integrate AI into their advertising strategy. 

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Final word 

AI tools replacing the role of humans can be a scary prospect, especially if it starts to encroach on your job function. However, there will always be a need for real humans to manage AI tools and to handle situations that technology can’t. 

The most important consideration for AI eCommerce businesses is how can these tools be smoothly integrated into the business, and what the potential benefits are. Like the examples in this article demonstrate, it’s about using AI to your advantage. 

As well as enhancing the day to day running of eCommerce businesses, AI can also be used by retailers to disrupt the advertising space, using it to boost advertising strategy

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