How AI and Machine Learning Is Shaping Ecommerce Industry

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Published on: February 17, 2022 Updated on: March 28, 2024 views Icon 299 Views

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  • Ecommerce

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Sakshi Arora
Sakshi Arora LinkedIn

Assistant Manager- Content Marketing

Sakshi Arora is a seasoned content writer and marketer specializing in B2B topics such as marketing automation and website development. Leveraging her journalism background, she infuses her work with clarity and creativity, captivating audiences. Beyond her professional pursuits, Sakshi finds joy in writing about personal emotions, showcasing her introspective side and adding a unique touch to her portfolio.

Article Reviewed By: Rahul Saini LinkedIn

Table of Contents

The eCommerce industry has grown exponentially over the last decade. From a $680 billion industry back in 2011, it crossed $5 trillion in 2021. Back in the day, it commanded 3% of the total retail share and current estimates suggest it would be near a 20% market share by 2023. Though the Covid-19 pandemic has given a major push to this segment, the growth of the eCommerce business space can be primarily attributed to the evolution of technology. 

Technology & Ecommerce 

The eCommerce industry has a symbiotic relationship with technology and its evolution. Without the internet, there would have been no eCommerce. Without the mass adoption of computers and smartphones, e-commerce wouldn’t have been a $5 trillion industry. Technology has been the enabler and the driving factor behind the growth of eCommerce businesses.

Ecommerce on its part has been an early embracer of technology. Talking about technology in the eCommerce business, artificial intelligence, and machine learning would immediately strike your mind. As someone who is part of this industry or an observer, you would have heard and read a lot about these technologies. While eCommerce came as a major disruptor in the retail business, AI and machine learning are disrupting the eCommerce industry itself. It is estimated that by 2025, 95% of all customer interactions on eCommerce stores would be managed by AI.

What Are AI and Machine Learning and How Are They Different?

Machine learning and artificial intelligence are often mentioned interchangeably in common parlance, but they aren’t the same. Before we dive further into how AI and machine learning are shaping the eCommerce industry, let us look at what they are and how they are different from one another.  

Artificial Intelligence

Artificial intelligence uses the computing power of machines to imitate the human mind’s problem-solving and decision-making abilities. This is a technology that is known for exhibiting human behavior. Unlike traditional computer programs that are built to perform tasks based on inputs, AI tools can reason with data, sense opportunities, and adapt to different scenarios like the human mind. 

Machine Learning

Machine learning depends on data and algorithms to perform actions and make predictions. It is a continually learning tool that comes up with more accurate outputs when it is exposed to more data. The more information it gathers the better it becomes in predicting outcomes. It performs analysis based on the input data independent of any human interference. 

Technically, machine learning is a sub-branch of artificial intelligence. AI is the technology whereas machine learning is the process. AI empowers machines to imitate human behavior such as reasoning, sensing opportunities, threats, etc. The main goal of AI is to make computer systems smarter whereas machine learning is focused on learning from data and analyzing trends to give the most accurate outputs. 

Benefits of AI & Machine Learning for Ecommerce Business

Artificial intelligence and machine learning are revolutionizing eCommerce and helping online stores in many ways. Let us look at some of the benefits deploying AI and machine learning will provide to you: 

Increased Conversions

Conversion is the most important parameter to measure the success of an online store. It is measured using the ratio of transactions to user sessions on a store. Globally, online stores have an average conversion rate of 2.58%

AI and machine learning can boost conversion rates through smart search results instead of generic ones. For instance, a user who has been reviewing an Apple iPhone in a store is more likely to buy flagship Android phones instead of budget ones. Hence, their product recommendations on the store or social media feeds should have offers on premium phones instead of budget phones.

Streamlined Search Function

Not all eCommerce customers are great with keywords and searches. While your store may be stocked with products, your success rests on how easily customers can find the products they are looking for. Searches cannot be keyword-based alone and AI allows you to enable smart searches such as predictive text, autocorrect typos, and search results based on customers’ demography and past buying habits. 

Personalized Store Experience

Your customer doesn’t want to be treated as an ‘average customer’ but expects personalized services and offers just how they receive at retail outlets. The main thrust in the eCommerce business has been personalization. AI and machine learning are helping stores adapt to the unique needs and demands of customers. For instance, a customer who has recently bought an iPhone would expect the store to suggest the best cases for an iPhone whenever he or she is looking for a case. The better your store is with product recommendations, the more are your odds of increased sales. 

Improved Customer Service

Did you know an average eCommerce store has only 25-30% returning customers? The real fight in this business is to earn customer loyalty and AI and machine learning can help. AI-powered chatbots can be employed to offer the first line of support services to your customers and optimize the use of human resources. Modern chatbots can communicate with customers in natural language and answer a majority of their queries. 

Advanced Forecasting

eCommerce stores need to strike the right balance between demand and supply to optimize their warehousing capacity. AI helps store owners make data-backed decisions. Sales trends and future demands are automatically processed by AI tools and help you with accurate forecasting. These tools can also detect anomalies in the sale of products or spot products that are losing customer interest. 

Steps to Adapt AI and Machine Learning in Ecommerce 

1. Price Optimization

Ecommerce shoppers are price-sensitive and more than 50% of customers do price comparisons before placing an order. If the products cost more or are the same as retail stores, customers are likely to prefer physical shopping with the touch and feel experience. Dynamic pricing or price optimization is employed to offer the same products at different prices based on demand, supply, competition, etc. AI and ML can be employed in price optimization to take this a step further as they factor buyers’ intent, time of the day, urgency, and other factors that influence buying decisions. 

2. Predictive Analysis

AI and machine learning can tell you more about your customers than you can think of. Based on their activity in your store, these technologies can predict whether the customer is likely to buy the product or simply window shopping. They can give you insights on the other products customers might need based on their overall search activities. AI algorithms can offer you meaningful insights that let you target the customer more proactively such as with tailored offers or discount coupons. 

3. Visual and Voice Search

Ecommerce stores have traditionally relied on text-based searches and hence, the focus in the past had always been on SEO. However, we are seeing a shift toward visual and voice searches. Google Lens and other similar tools let users shop for products they can take pictures of. Similarly, Apple’s Siri and other voice assistant tools are allowing users to shop online using voice commands. Integrating machine learning helps in improving voice and visual search on stores and thereby increases conversions. 

4. Product Recommendation

Product recommendations are the best way to increase sales and retain customers in a store. When you suggest to customers the right products your store would see increased sales. For instance, when customers buy a printer from the store, they are likely to need printing paper and ink supplies. Use machine learning to understand the frequency at which customers shop for ink supplies and use email marketing or display products on the recommended list to ensure more sales. 

5. Inventory Management

Inventory management is complex and when stores sell thousands of different products, it can become a herculean challenge for the team managing the stocks on the store. Inventory management is the job where machine learning can help. They can track the demand of products during different seasons, change in sale trends, etc. and manage your inventory accordingly. 

Final Thoughts

Ecommerce is evolving from being just various digital commerce touchpoints with product listing, carts, and payment gateways, to a wholesome shopping experience. Stores are increasingly interacting with customers at multiple levels. In addition, artificial intelligence and machine learning are shaping the future of eCommerce from offering tailored products to predicting customers’ needs. 

These technologies empower you to offer more personalized services to your customers. Combining these with other technologies such as AR (augmented reality) and VR (virtual reality), you can now also replicate in-store shopping experiences for your customers. If you are not leveraging these technologies for your eCommerce business, you will soon fall behind in the race. Fasten your seatbelts and deploy AI and machine learning into your eCommerce business today. 

If you wish to leverage the true power of AI and machine learning in eCommerce but don’t know where to begin, Growth Natives can help you. As experts in the eCommerce domain, we help clients deploy AI-based algorithms in their online stores. From integrating virtual assistants to enabling smart search, we can power your store to improve conversions and profits. To discuss the details of your project, write to us at or visit our website. 

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