Artificial Intelligence today is completely transforming eCommerce, making the shopping experience much more personal, searches more intuitive, and managing inventory and sales easier. AI has also made it mandatory for eCommerce businesses to harness AI's power to ensure their business's growth and success in a fiercely competitive online marketplace.
Studies show that by 2025, 95% of customer interactions are expected to be driven by Artificial Intelligence, marking its significant impact across industries, including the realm of eCommerce.
In this post, we will explore how AI is revolutionizing eCommerce, highlighting key technologies, benefits, and top use cases for online retail while offering actionable insights for eCommerce brands to harness AI's power effectively.
Understanding the Evolution of AI in Online Retail and eCommerce
AI in eCommerce essentially guides various applications of artificial intelligence technologies such as machine learning (ML), natural language processing (NLP), data analytics, and more.
The growth and adoption of artificial intelligence technology in the retail and eCommerce landscape have been nothing short of phenomenal. Today, AI has become integral to modern eCommerce marketing and sales, offering both a competitive advantage and unlimited opportunities to businesses across the board.
Unlike earlier, when retailers were using past sales data and human intuition to forecast trends, AI algorithms help online retailers analyze massive amounts of data to be able to predict consumer behaviors with great precision.
There are several other ways that eCommerce businesses have been working on their operational methodologies and getting the most out of artificial intelligence technology.
Some of these are discussed below:
Positive ROI with AI-enabled eCommerce
The robust features of AI allow eCommerce businesses to generate more leads and sales and receive positive ROI for businesses in the long run. The technology also allows you to earn a distinct competitive edge over your competitors in the rapidly evolving eCommerce space.
For instance, MakeMyTrip, a prominent travel eCommerce brand, uses AI/ML to adjust pricing in real-time dynamically. This lets consumers get relevant and contextual pricing information and contributes to customer engagement. This, in turn, leads to more sales, greater retention, more conversions, and higher ROI.
Data analytics in AI
AI can be instrumental in comprehending and discovering the most important and relevant consumer trends. This can help online retail brands find their target audience and segregate them as per their specific business requirements.
An example of this is how Netflix utilizes AI for sentiment analysis to identify pain points and implement enhancements for a better viewing experience for users.
AI-enabled recruitment
AI brings several use cases in eCommerce recruitment and helps in screening candidate resumes, analyzing candidate body language, performing online candidate assessments, and assisting in hiring quality candidates. This helps increase the overall operational efficiency of a business and can be particularly beneficial for eCommerce businesses when interviewing candidates remotely or even hiring internationally using a global HR platform.
For example, take how IBM provides AI-enabled recruitment solutions to help businesses in recruitment, talent management, and overall career development. The company uses AI technology to enhance hiring decisions by applying predictive analytics and natural language processing.
AI for business cybersecurity
The use of AI applications in eCommerce can help prevent fraudulent business transactions, safeguard businesses, and overall ensure higher customer trust.
For instance, take how Flipkart uses AI for fraud detection, especially when a seller misuses the platform or uses manipulated pictures in the listings. AI algorithms swiftly detect and flag such instances, which ensures customers receive accurate information.
Data management with AI-enhanced efficiency
Data management is another area where AI-powered eCommerce can be of great help. It allows eCommerce businesses to build powerful connections with their customers.
This is especially helpful for businesses where managing vast amounts of data is one of the biggest challenges, and AI here can help by easily integrating and segregating that data.
For example, take how Apple uses AI/ ML technology for the FaceID feature in iPhones or in products like the Apple Watch, enabling the smart assistant Siri to help build customer connections.
Key Technology Advancements Changing the Face of Online Retail
Several key technologies in the AI landscape drive online retail's growth and evolution. Among these are:
1. Machine Learning
A subset of AI technology, machine learning leverages real-time data to make predictions or perform desired actions. The higher the amount of data the algorithms get over time, the more accurate the outputs become.
With the machine-learning market reaching a CAGR of 44% to $9 billion by 2022, it is today's most popular and widely used eCommerce AI technology.
The eCommerce industry uses machine learning in several different ways, including accurate real-time forecasting, optimized search results, advanced product sorting, dynamic real-time pricing, and more.
2. NLP for eCommerce
NLP is another AI technology that makes it easier for machines to understand speech and patterns. Widely used in chatbots and voice assistance, NLP technology is expected to be worth $48.46 billion by 2026.
There are several applications where NLP can play a critical role in eCommerce. These include voice-activated payments, voice searches, eCommerce automation mechanisms, and a variety of tools such as customer chatbots, automatic language translations, product categorization, and more.
3. Deep Learning for eCommerce
Deep learning AI refers to an important machine learning subfield that imitates how humans gather certain knowledge types. For instance, Amazon's voice assistant, Alexa, uses this technology in eCommerce.
The deep learning technology and its latest techniques have completely changed how people shop. This is also why eCommerce giants such as Amazon or eBay have put a lot of money into client recommendation systems.
The key idea here is to make use of deep learning systems to woo users to shop and buy more things. This is why businesses are working towards building great teams to improve the overall accuracy of their recommenders.
4. Computer Vision for eCommerce
Computer vision is the newest subset of AI that enables computers to see things as well as users do. In other words, the technology collects and uses data from various visual inputs such as photos and videos. Augmented reality is a great example of this technology being used in eCommerce.
Another application of this technology is facial recognition, with data suggesting that leading European retail brands have seen a phenomenal 90% increase in customer insights simply by harnessing facial recognition.
Advantages of Using AI in eCommerce
Below are the major advantages of leveraging AI in eCommerce in 2024:
Higher Customer Engagement and Satisfaction
The importance of a powerful marketing strategy to define the success of an online business is huge. AI helps you better analyze your customer data to identify key trends and patterns to understand customer requirements.
The biggest benefit of AI-driven eCommerce here is that it attracts customers and keeps them invested and content due to personalization. AI algorithms enable eCommerce companies to gauge specific user preferences and accordingly showcase products specific to each person's liking based on their past purchases or browsing history.
This kind of targeted approach helps eCommerce brands maximize customer engagement as it makes them feel personally catered to, leading to much higher satisfaction rates.
AI and Visual Search
AI-powered visual search has emerged as one of the most innovative tools transforming how customers shop online today. The technology allows users to conveniently search for their preferred products using images instead of text-based queries, thus making their shopping experience simpler and more interactive.
In the context of eCommerce especially, this technology is a complete game-changer. AI allows online retail companies to easily integrate visual search into their online platforms, giving customers the option to upload images of products they're interested in. Brands can then present to customers matching or similar items in their inventory for enhanced user engagement and a more intuitive shopping experience.
An excellent example of this is Google. The tech giant has been harnessing AI to make their image search more accurate and powerful. The company utilizes a machine learning model known as deep neural networks to both process and understand a massive number of images on the web.
The model can then recognize relevant patterns and features in images, thus allowing users to search with images taken from their devices and find similar products online.
Predictive Inventory Management
The eCommerce landscape today is rapidly evolving, making it essential for online brands to master their predictive eCommerce sales and inventory management process. This is also essential as managing the different variables involved in supply chains can quickly get overwhelming, leading to issues such as increases in costs, inaccurate demand forecasting, and more.
Artificial Intelligence presents an excellent solution, allowing brands to utilize various AI models based on artificial neural networks (ANN), leading to accurate demand forecasting.
The advantage of these AI-driven models is that they can easily adapt to rapid changes in evolving customer demand, thus minimizing the supply/demand mismatches associated with manual processes, saving a great deal of cost for businesses.
A recent McKinsey & Co.report also suggests that businesses that invest in machine learning technology to manage demand forecasting can achieve as high as 90% accuracy as compared to a mere 60% with manual forecasting.
AI Chatbots in eCommerce
AI-based chatbots have become integral to eCommerce platforms, playing an important role in engagement and satisfaction. The benefit of these AI-powered bots is that they can easily interact with customers 24/7 answer their queries, offer product recommendations, and do much more to enrich the overall customer shopping experience.
For the eCommerce industry specifically, AI chatbots can be useful in multiple ways. For instance, AI chatbots are equipped to handle a large volume of customer queries without any human intervention, thus significantly reducing customer response time.
For example, a communication platform such as Crisp leverages AI to match customer queries with relevant helpdesk articles, often enabling customers to access the information they need without having to speak to a human support agent.
In addition, these chatbots are also designed to learn and improve over time through machine learning. This enables them to offer more accurate responses and better customer service as they interact with more customers.
AI chatbots also play a key role in personalization. For instance, they can recommend products to customers based on their browsing history or individual preferences, thus making the shopping experience more targeted and efficient.
Cross-Selling and Upselling Opportunities
AI-driven algorithms allow eCommerce businesses to offer discounts, promotions, and other giveaways in a very planned, strategic, and customized way.
For instance, sales professionals can use AI algorithms to offer various complimentary products that customers require by analyzing the customers' preferences and past shopping patterns. The artificial technology evaluates data and comes up with a robust strategy that is most suitable for the target audience.
Likewise, AI algorithms in eCommerce exceed personalization by processing massive raw data, enabling brands to discover better insights into individual likes and preferences. It helps you segregate customers based on aspects such as demographics, past purchasing history, and more to facilitate targeted upselling and cross-selling.
Omnichannel Presence
Yet another benefit of integrating AI in eCommerce business is the advantage of omnichannel presence. The technology allows eCommerce businesses to easily reach their customers on multiple platforms, thus offering them a smooth and consistent experience across various channels.
There are several ways that this integrated methodology can help eCommerce brands. For instance, it allows users to access more products, offer personalized experiences, and much more.
Besides, businesses can also keep records by allowing customers to shop, compare, and get uniformly consistent services using various business models like inventory management and sales.
Artificial intelligence also helps eCommerce businesses ensure websites are user-friendly, relevant emails, social media is engaging, and customer journeys are well-planned. With the assistance of an omnichannel marketing approach, eCommerce businesses can increase their lifetime value, thus positively impacting ROI.
Seamless Automation
The key goal of the automation process is to accomplish any given task with minimal or no human intervention. This could be applied in a range of aspects, such as scheduling emails in a CRM or leveraging advanced technology to help with the process of hiring.
In the context of eCommerce trends specifically, machine learning and robotics are some of the most commonly used automation areas. AI can be instrumental in helping online retail brands automate the manual, time-consuming, repetitive tasks that keep the online store functioning.
For instance, AI allows you to automate a range of things, including product recommendations, low-level support, and much more.
Efficient Sales Process
Another advantage of using AI in eCommerce is that the technology helps you build a much more successful and efficient sales process. This is done by gathering data about your customers, automating abandoned cart inquiries, and more.
Every eCommerce brand wants its customers to have a smooth and enjoyable shopping experience. AI is one technology that helps you optimize your website design and layout based on individual user behavior and enhance their shopping experience.
Likewise, eCommerce brands can help move their customers through the funnel by having them more engaged in the conversation with chatbots for simple queries.
Top 5 AI Use Cases in eCommerce
Apart from the benefits listed above, there are several use cases in eCommerce for AI. Some of the common ones are discussed below-
1. Optimized Dynamic Pricing
AI-enabled dynamic pricing refers to a strategy of changing the product price based on several factors, such as competitors' prices, manufacturing costs, and existing supply and demand.
If given access to the right data, AI technology is equipped to predict when and what to discount, thus dynamically coming up with the minimum discount required for the sale. Further, AI is also equipped to change the prices for a large number of retail products in your stores, thus saving time on manual adjustments.
Example
Amazon is an excellent example of a store here that fully utilizes a dynamic pricing strategy. Whenever the retail giant's competitors offer any sort of promotions or discounts, they keep on adjusting their own product prices by up to 20%.
However, it is important to remember that they do such price adjustments gradually to ensure maximum profitability for their brand based on sales forecasts. This enables them to remain the most affordable for customers and maintain control over their profit margins at the same time.
2. Personalized Product Recommendation
Artificial intelligence technology in eCommerce is also being used to offer personalized product recommendations based on aspects such as past customer behavior and similar-looking customers.
These online retailers that recommend products you might like based on past purchases use machine learning algorithms to analyze your purchase history and use it to deliver a more personalized customer experience.
Example
Netflix is an excellent example of this. The streaming giant's AI-powered recommendations engine NRE (Netflix Recommendation Engine) is worth $1 billion per year. NRE uses AI algorithms to filter content based on an individual user's profile and is capable of filtering over 3,000 titles at a time using 1,300 recommendation clusters to come up with the exact titles that a user might be interested in.
By analyzing data from individual customer visits and clicks, the recommendation engine can understand their preferences and create hyper-personalized recommendations for each of them.
3. Customer Segmentation
A survey done recently highlights that as many as 80% of customers prefer going to business with a brand that personalizes their user experience. In such a scenario, segmenting your audience is most important to delivering personalized marketing communications.
In addition, if followed properly, segmentation tactics can increase the effectiveness, productivity, and ROI of your marketing campaigns' manifolds. A report also suggests a staggering 760% increase in revenue from properly done segmented campaigns.
However, creating groups for customers manually could be a very long and time-consuming process, which is where AI comes into the picture. AI algorithms can analyze the data, and AI-based tools can easily create customer segments for your business based on the similarities they notice.
The highlight here is that they can analyze vast amounts of data without any prior biases or assumptions, thus giving you a more accurate picture of your audience.
4. Sales and Demand Forecasting
An increasing number of eCommerce companies today use forecasting techniques better to manage their inventories, logistics, and warehouse space, to be able to determine pricing strategies.
However, predicting demand with great accuracy gets very challenging as historical and seasonal sales data are no longer enough.
AI plays a key here in sales predictions to help companies make their demand forecasts much more accurate and reliable. Instead of just using historical data, AI ensures making sales and demand predictions using real-time data, such as demographics, performance of similar items, online reviews, and more.
Example
Danone is a great example of companies that have implemented a machine learning system to improve their demand forecasts.
Apart from creating more accurate estimates for their short-life products, their AI-based machine learning system also helps them improve planning between different departments such as sales, marketing, supply chain, and finance.
5. Smart Logistics
Similar to other industries, logistics businesses can significantly benefit by leveraging AI-powered devices and automating several manual, time-consuming, and repetitive tasks.
This kind of smart or intelligent logistics mainly uses real-time information gathered through sensors, RFID (radio-frequency identification tags), or more to smoothly manage inventory levels and accurately predict demand.
An excellent example of AI-powered logistics is using smart warehouse shelves that are equipped to sense weight and pressure followed by sharing this information with warehouse management systems.
With RFID tags or barcodes, eCommerce brands can keep their inventories updated by closely tracking when items are received, stored, picked, and shipped.
Likewise, AI can also help retail companies keep track of all their products throughout the entire supply chain, right from the manufacturer to the store, thus helping them minimize the chances of late deliveries or accepting damaged products.
Key Trends Set to Revolutionize Online Retail
If you wish to take your eCommerce business to the next level, integrating artificial intelligence (AI) into your operations is one of the best ways. AI can prove instrumental in helping you improve various aspects of your eCommerce, including better customer service, streamlined sales data management, and more.
Trends to Revolutionize Online Retail |
Key Points |
Personalized shopping experiences |
ML algorithms can analyze vast amounts of consumer data in real-time, uncovering essential patterns, trends, and behavior that retailers can use to their advantage. |
Effective inventory management |
AI algorithms can analyze data such as competitor pricing, social media sentiment analysis, and other macroeconomic indicators to assist with demand forecasting |
24/7 assistance by chatbots |
AI-powered chatbots are available all the time for customers to ask simple and more complex questions and get immediate answers without having to wait to talk with a customer service agent. |
Fraud prevention |
Advanced machine learning algorithms can analyze transaction data in real-time to identify anomalies and block fraudulent activity. |
Data privacy and ethical AI |
eCommerce companies must comply with local and federal regulations regarding data privacy, such as GDPR in Europe and the Privacy Act of 1974 in the United States. |
Voice commerce |
AI-powered voice assistants like Google and Siri allow shoppers to make voice-enabled purchases easily. |
Sustainable eCommerce |
AI can make the eCommerce space more sustainable by targeting inefficiencies in logistics and supply chains, which reduces environmental waste. |
Personalized Shopping Experiences
There is no denying the fact that higher personalization makes shoppers happier and more satisfied. Data also suggests that almost 70% of consumers in eCommerce space spend more with brands that offer more personalized customer experiences.
This is where AI comes in.
Although the concept of AI-driven personalization is not new, it's becoming more advanced.
The future is expected to see AI personalization reach newer heights, as machine learning algorithms can analyze massive amounts of customer data within no time. This includes customer purchase history, browsing patterns, social media activity, and more to create highly personalized shopping experiences.
This, in turn, leads to accurate product recommendations and an exceptional shopping experience that's completely tailored to each customer's preferences. The technology allows you to do this by helping you understand your customer's behavior so that you can recommend their preferred products.
Effective Inventory Management
Efficient management of inventory is one of the key challenges for eCommerce businesses. However, AI helps you navigate this challenge by predicting sales trends and managing the stock much more efficiently without having to worry about overstocking or running out of products.
AI algorithms are also equipped to incorporate additional data sources such as competitor pricing, social media sentiment analysis, and other macroeconomic indicators to enhance overall demand forecasting accuracy.
Taking into account these external factors, eCommerce businesses conveniently adjust their inventory levels and accordingly align their strategies to meet changing market conditions with more efficiency.
Another area where AI algorithms shine in inventory management is in classifying and segmenting products based on different attributes, such as sales, profitability, demand patterns, and seasonality.
This kind of categorization allows businesses to prioritize their inventory management efforts strategically and direct their focus toward other high-value or fast-moving products.
24/7 Assistance by Chatbots and Virtual Assistants
A recent piece of research estimated that chatbots saved businesses a whopping 2.5 billion hours and a great deal of money in the tune of £6.5 billion. It is further expected that AI-driven chatbots and virtual assistants will continue to enhance customer support in the future as well.
AI-powered chatbots can be instrumental in serving eCommerce clients 24/7. These chatbots are always there to answer client queries and solve problems, if any. This means happier customers for your business and the advantage of higher loyalty to your brand.
Likewise, virtual assistants help retail brands handle large volumes of routine inquiries, offer accurate product recommendations, and assist clients with the overall purchase process.
The rapid advances in natural language processing (NLP) have made these chatbots and virtual assistants even more conversational and capable of answering complex customer issues and improving overall customer satisfaction.
Prevention of Fraud
Fraud is one of the major concerns in eCommerce but AI technology can significantly help with bolstering fraud detection and prevention efforts of companies.
This is because of the advanced machine learning algorithms that can analyze transaction data in real-time to identify as well as block fraudulent activities efficiently. This saves retail businesses from severe financial losses and builds trust and credibility among customers for the brand.
A survey done recently also found that as many as 49% of financial institutions have already integrated AI into their systems to better deal with fraud detection, and over 90% of them also plan to invest in it within the next few years.
Data Privacy and Ethical AI
Ethical AI and data privacy are another interesting trend to watch out for in this space. As more and more online retailers are integrating AI in eCommerce, there's a higher awareness of data privacy and the ethical implications associated with its use.
Some of the ethical AI practices involved here include ensuring AI systems are designed and deployed in ethically correct ways that respect basic human rights and avoid bias and discrimination. eCommerce brands that prioritize these ideas will not only comply with regulations in the future but will also focus on building trust and credibility with their customer base.
Data also suggests that while the trust in AI is increasing, almost 50% of people don't trust businesses that use AI to protect their data, and almost 44% of people don't trust AI to not discriminate or show bias.
Voice Commerce
While the number of voice assistants (like Siri and Alexa) in use across the globe was 4.2 billion at the start of 2023, this number is expected to reach a phenomenal 8.4 billion in the coming year as an increasing number of consumers turn to aspects such as speed and convenience of voice search.
The numbers clearly reflect that more online retailers now need to invest in voice commerce capabilities to be able to capture the rapidly growing audience of voice-enabled shoppers, and AI can be instrumental in enabling this.
AI-powered voice assistants are equipped to facilitate voice-activated shopping, thus allowing users to do everything from making purchases to tracking orders and enquiring about product details using the voice search feature. This requires businesses to optimize their eCommerce or online retail platforms for voice search and integrate the best voice assistant platforms.
Sustainable eCommerce
One area that is gaining a lot of momentum for both customers and businesses is sustainability. Data also suggests that as high as 78% of consumers believe in the importance of sustainability.
AI can play a key role in making eCommerce space more sustainable by optimizing logistics/supply chains and reducing waste. AI-based machine learning algorithms can come up with the most efficient delivery routes, reduce packaging waste through better sizing, and help eCommerce businesses make more environmentally conscious decisions in their supply chains.
How Can eCommerce Businesses Adapt to the Latest AI Trends From the Industry?
To be able to find the most relevant AI trends for eCommerce, retail organizations need to take a detailed and systematic approach. Empower your eCommerce business by integrating cutting-edge AI trends into your retail software to stay ahead in the dynamic industry landscape.
Here are some of the ways to navigate the process:
1. Identify Your Respective Business Goal
The first and foremost step for eCommerce brands in finding the relevant AI trend is to identify the unique business goal. This could be anything from automation of processes, and enhancing marketing strategy to building brand awareness.
2. Recognize Customer Pain Points
This is the stage where you need to dig deeper into your eCommerce operations to discover customer pain points. These could vary from business to business, ranging from financial challenges to operational inadequacies.
The best way to find them is by scrutinizing massive amounts of data and pattern recognition. These will help you with the required insights and relevant information needed to take a targeted approach.
3. Perform Resource and Budget Allocation Wisely
Various AI-powered tools can help eCommerce businesses identify key sales trends and make the right forecasts about customers' behavior and product demands. In addition to this, these tools refine targeting efforts and allow eCommerce businesses to develop a proper framework for overall budget and resource allocation.
4. Start the Pilot Project
Another important thing to do to evaluate the impact of AI on your business is to start a pilot project. You can begin with small-scale AI projects that help you highlight your approach's controlled experimentation and allow you to correct your marketing methodological approach.
5. Competitive Analysis
With rapid advancements in AI solutions for eCommerce, businesses across the board stand a chance to gain a competitive edge. Competitive analysis in terms of audience segmentation, platform utilization, marketing methodology, budget specification, and best practices of businesses can allow your business to stand out from the competition.
Wrapping It Up
Technology is revolutionizing how eCommerce businesses operate and engage with their customers by enhancing sales processes, offering personalized experiences, predicting shopping patterns, improving decision-making, and much more.
Overall, the technologies, use cases, trends, and benefits of AI in eCommerce (as discussed above) demonstrate its significant role in shaping the future of online retail.
As AI and machine learning technologies continue to evolve further, eCommerce companies willing to embrace and integrate these innovations into their operations will surely thrive in an increasingly competitive eCommerce market.
The need for retail companies today is to consider and implement a powerful AI adoption strategy for the future as these technologies continue to develop and evolve.