How to Use AI for eCommerce Industry: Use Cases & Benefits

How to Use AI for eCommerce Industry: Use Cases & Benefits-feature image
April 4, 2024 9 Min read

The incorporation of Artificial Intelligence in the ecommerce industry has changed the way businesses interact with their customers, it has simplified operations, and boosted the overall operational efficiency. By leveraging AI in your ecommerce business, you can easily create personalized shopping experiences, optimize supply chain operations, and even boost sales through predictive analytics.

From creating chatbots to providing customer support and offering tailored product suggestions, AI has become an integral part of the eCommerce landscape. In this article, you will learn more about the applications of AI for e-commerce businesses and how they can help improve your business.

What is the Use of AI in Business?

With AI, you can mine the data to comprehend what type of customer you are reaching out to and how to best connect with them. This will help you to create more customer-centric marketing and advertising campaigns to boost sales.

Moreover, with AI-based software, a business can automate multiple repetitive tasks such as sending emails, entering customer information, creating customer interaction journey, etc. This boosts operational efficiency and saves a business’ valuable time.

In addition to that, AI can analyze the historical data to discover sales trends and forecast future sales. By leveraging this data, you can easily reformulate your sales strategies to increase revenue.

Technology Used in eCommerce

Technology Used in eCommerce Industry

Multiple technologies are used in eCommerce to streamline everyday operations. Some of the popular technologies include Data Mining, Machine Learning, Natural Language Processing, Computer Vision, etc. Let’s look at each of these technologies in detail in below:

  • Data Mining: Many eCommerce companies deal with bulk data including customers’ information, sales data, inventory data, etc. By leveraging data mining technology, businesses can easily collect and interpret this data to provide actionable insights. For example, by analyzing sales behavior, you can produce an optimum quantity of products.
  • Machine Learning: Machine learning can be used to improve inventory management, predict sales trends, create customer interactions, etc., and offer an enhanced customer experience.
  • Natural Language Processing (NLP): It is a type of technology that focuses on comprehending and interpreting human responses. NLP is used by eCommerce businesses to improve their chatbot functioning and address customer queries in a better way.
  • Computer Vision: Computer vision is a type of AI technology that helps computers in classifying and analyzing visual images. It can help in improving product search and recommendations. For example, a customer can capture a product’s picture and use an app with image recognition to find the product quickly.

How to Use AI for eCommerce Industry?

The use of AI in ecommerce is diverse, such as it helps in providing personalized product recommendations and creating chatbots to handle customer queries. Moreover, it can also help in managing inventory and developing dynamic pricing for customers.

Let’s look at these use cases in detail below:

1. Personalized Product Recommendations

The key AI application in e-commerce is sending personalized product recommendations to customers. For that purpose, AI comprehends data like past customer behavior, purchase history, and browsing history to suggest products.

2. Chatbots and Virtual Assistants

These are types of virtual representative for your business and help in resolving customer’s complaints and queries. Chatbots utilize AI and NLP to comprehend and reply to customer’s requests. Virtual assistants can help you with enhancing customer checkout, providing 24/7 assistance, and streamlining customer interactions.

3. Inventory Management

Artificial intelligence in e commerce is used in managing inventory by interpreting historical sales data and forecasting future inventory demands.

For example, by collecting the real-time inventory data via sensors and RFID tags, you can identify types of products that are selling, where these products are going, and whether they are coming via a physical store or a distribution center.

4. Dynamic Pricing

Dynamic pricing lets you to adjust the product’s pricing and offerings depending on the real time user behavior, supply chain, product’s demand, etc. By leveraging AI, you can easily anticipate discounting needs and minimum discount that you need to offer for a successful sales drive.

For example, if you are selling products on your website and Amazon, you can set product discounts on Amazon when there is influx of purchasing activity.

5. Prediction of Customer’s Churn

Machine learning can assist in identifying and reducing the customer churn by forecasting when your customers might leave your website or platform. For that purpose, AI will gather and analyze data from multiple customer churn indicators like abandoned carts, website bounce rate, browse abandonment, etc.

After that, you can automate tasks like purchase completion emails, follow-up abandoned cart inquiries, loyalty discounts, etc., to prompt customers to complete their purchase order.

6. Generating Marketing Content

E-Commerce is using generative AI tools like ChatGPT to create marketing content based on the prompts provided. By using these tools, you can create marketing collateral catering to the targeted audience.

For example, a copywriter can generate a marketing email and customize it via generative AI tools for different customers’ segments. Marketers can use these tools to create compelling marketing copies that align with your targeted customer personas.

AI Application in eCommerce Examples

Many eCommerce businesses are leveraging AI to improve their customers’ shopping experience and boost sales. Here are some popular artificial intelligences in e commerce examples to help you understand how an eCommerce company uses AI in their day-to-day business operations.

1. eBay Image Clean-UP Feature

In 2020, eBay released an AI-based image-processing feature to separate a picture’s foreground from the background while cleaning the latter.

This has helped eCommerce businesses in improving the listing visuals without any need of a third-party image editor. This has helped eBay retailers in attracting more customers and generating higher revenue.

2. LoweBot by Lowe

In 2016, Lowe released LoweBot, a retail robot to handle store tasks and assist customers in navigating the store. Customers looking for a particular product can add the questions through the touchscreen front and then LoweBot will guide them with the right directions.

3. Uber Matching

Uber Matching is a feature in Uber that uses machine learning to connect drivers and riders depending on geographical factors such as traffic. The matching algorithm performs batch matching by clubbing together drivers and riders within the same area rather than clubbing them via distance.

In this way, riders and drivers’ waiting time is reduced. Uber Matching can also connect a driver with a rider who wants to travel on the same route, to make the trip more effective and cost-effective.

4. Alexa Shopping

Amazon Alexa is now used as a voice shopping medium on the Amazon website. All you need to do is enable the voice purchasing feature and set up payment methods within the Alexa app. With the voice command, you can easily purchase items directly from the Amazon website.

Moreover, by using machine learning and Natural Language Processing, Alexa can also create shopping lists, shop products, and complete transactions.

Benefits of AI in eCommerce for Business

Leveraging AI in your eCommerce can come with several benefits in creating better product visuals, developing customer retargeting strategies, and filtering out fake reviews to improve brand image:

  • Enhance Product Visuals: To help customers with their purchase decisions, it is important that product visuals are accurate. You can use AI image generator to create HD images of the listed products that accurately showcase their features.
  • Create Retargeting Shoppers’ Strategies: Creating strategies for retargeting shoppers is important to boost conversion rate and engage your customers. For that purpose, you can use AI to analyze your existing customers data, build customer interactions and target your customers down the sales funnel.
  • Improve Personalization for Customers: Providing personalized product recommendations has helped multiple businesses to improve their customer’s shopping experience and boost sales. By leveraging AI-based conversational marketing, you can offer personalized recommendations to your shoppers based on the answers they provide to your questions.
  • Filter out Fake Reviews: By going through product reviews, customers form their opinion whether they want to buy a product or not. Therefore, to streamline this process, you can filter out fake reviews by cross verifying the reviewer ID. This will ensure that only genuine reviews are on the website.

Challenges While Implementing Artificial Intelligence in eCommerce

Although AI provides many benefits for the eCommerce industry, it comes with its own set of challenges. For example, using these tools can lead to data privacy issues and implementing them comes with higher initial investment. Here are some of the common challenges of implementing AI in an eCommerce business:

  • Data Privacy Issues: AI relies on the consumer’s data to provide personalized product recommendations and predictions. Collecting this data raises issues about privacy and data protection. Many Generative AI tools store the data provided by users that might lead to data breaches.
  • Higher Initial Investment: Implementing artificial intelligence could be a bit costly for eCommerce businesses initially. This might involve investment within the infrastructure, personnel training, and AI product maintenance. Moreover, AI-based tools may not always provide positive ROI as expected by businesses.
  • Potential for Poor Customer Service: As the AI-based customer service depends on chatbots, it might fail to provide the same empathy and support as a human customer service representative. This can lead to customer dissatisfaction and a poor brand reputation.

Artificial Intelligence in eCommerce: Conclusion

Machine learning and artificial intelligence has completely transformed the eCommerce industry as we can see businesses leveraging them. Product recommendations, virtual assistants, and personalized shopping experience are some of the most distinctive uses of AI.

You can use multiple AI-based software to boost productivity, increase sales, and enhance customer experiences. However, make sure to consider your requirements before selecting any of them.

AI Application in eCommerce: FAQs

  1. How to implement AI in website?

    To implement AI in your website, you need to identify areas where you can use AI like website creation, product recommendations, or customer support. After that, look out for AI-powered tools that align with your requirements and follow their direction to integrate them into your website.

  2. How to increase e-commerce sales by using artificial intelligence?

    Leveraging AI in your business can help you increase eCommerce sales. With AI, you can analyze your market and customers data to gain insights. These insights can then be used to formulate strategies to boost sales.

  3. How is AI reshaping the future of ecommerce?

    It's permeating the customer journey, making its mark from initial product searches to personalized product recommendations to customer support when things go wrong. It provides powerful features such as Customer-centric online shopping experiences. AI-aided chatbots and virtual agents.

  4. How can AI be used in industry?

    AI can be used in any industry to perform multiple tasks. For example, in Healthcare, AI can help with providing personalized treatment plans and developing medical imaging. Similarly, in Retail and e-commerce, it creates personalized customer interactions, forecasts product demand, and creates chatbots to handle customer queries.

Written by Varsha

Varsha is an experienced content writer at Techjockey. She has been writing since 2021 and has covered several industries in her writing like fashion, technology, automobile, interior design, etc. Over the span of 1 year, she has written 100+ blogs focusing on security, finance, accounts, inventory, human resources,... Read more

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