Artificial intelligence is becoming a dominant force in ecommerce, and it’s not just changing the way we shop. It’s changing the way we sell.
The use of AI in ecommerce is still developing , but there are already some great examples of how artificial intelligence is having an impact on retail.
The ecommerce industry is constantly changing and evolving. The use of artificial intelligence and machine learning has become the norm in this sector. From helping to find products to improve customer service, AI and ML are being used in many ways.
The ecommerce industry is taking advantage of the latest technology to improve their business. Artificial Intelligence (AI) and Machine Learning (ML) have become more accessible as a result of advances in technology. There are several ways in which AI is being used to improve certain aspects of ecommerce businesses.
The only way you can survive in this competition is by implementing AI into your strategy.
Let’s take a look at some ways and applications of artificial intelligence the ecommerce industry:
Recommendation Engines for Products Recommendations
Recommendations are great, but they have to be relevant. And this is where AI comes into play. AI recommendation engines can help you provide your customers with content that is tailored to their needs and preferences, thus increasing sales and revenue.
Recommendation engines are used in ecommerce to suggest products to customers based on their browsing history, search history and purchase history. In addition to that, they can be used for personalization, targeting and advertising.
Product recommendations in the ecommerce industry are a great way to boost your profit margins and increase sales. They can also help you improve your customer experience by providing them with products they want.
Visual Product Search
Visual search is used in ecommerce to help shoppers find similar products to what they are considering buying. This could be done by taking a photo of it and searching for similar products . It allows you to find similar items without having to manually type in each product name, the customers can a smartphone camera, or uploading an image from their computers.
Visual search can also be used to identify objects in images and videos, such as clothing, furniture and other products.
The technology works by using machine learning to identify items in an image, then displaying relevant results based on those identified objects. This technology can often help customers find what they ’re looking for faster than traditional text-based browsing.
The technology is relatively new, but it’s growing fast. According to Google Trends data from January 2019, the term “visual search” has grown over 300% since 2016, with searches increasing by 54% in the past year alone.
Voice Search
Voice search is the use of natural language to find information. In simple terms, it is talking to a device like your smartphone or smart speaker and having it respond in a meaningful way.
For example, if you are looking for a restaurant nearby, simply saying “Where can I find a good steakhouse near me?” will get you some results. Or if you want to know what movies are playing tonight at the local theater, just ask and you will be given a list.
Voice search has become more important as more people use it to find products and services online. A study by Google found that 20% of all mobile searches were done by voice in 2015 and that number is expected to increase significantly over time. For example, Apple Pay was introduced in 2014 with support for Siri voice controls and has seen rapid adoption among iOS users (it now accounts for over 50% of online payments).
With this success comes even bigger expectations from users who want everything they need at their fingertips whenever they ask their device a question — including ecommerce sales!
Chatbots
Chatbots are a type of software that can help you interact with customers and take orders. They are often used in e-commerce sites to provide customer service, like answering questions about products or helping customers find what they need.
Chatbots can be used for many different tasks in e-commerce, including:
Supporting the customer service team by taking simple questions from customers (e.g., “What are your shipping rates?”) and resolving them quickly. This helps free up time for more complex inquiries and increases overall customer satisfaction levels.
It can also be used for various other tasks like booking tickets, ordering food, checking the status of an order, getting the latest deals and much more.
Streamlining order management so you don’t have to manually process orders, handle refunds and other tasks.
Saving time by automating processes like inventory updates or product recommendations based on what customers have previously purchased or browsed online.
Chatbots are also used by brands for marketing purposes. By using chatbots, brands can target their audience on social media platforms where they have presence and engage them in conversations about their products/services or upcoming events related to them.
Inventory Management
Inventory management is a critical part of any business, but it can be particularly challenging when you have millions or even billions of SKUs in your product catalog that change frequently due to seasonality or special promotions. Managing inventory requires a lot of manual effort from employees across multiple departments who must constantly check prices and availability on thousands of products and then place orders as needed. This process can take days or weeks.
Inventory management is a complex process that involves the integration of multiple processes across the supply chain. This includes order management, inventory planning and control, demand forecasting and replenishment planning.
Artificial intelligence can help with inventory management in several ways. For example:
- It can automate repetitive tasks that take up time and money, such as data entry or decision making.
- It can help predict demand better by analyzing historical data and current trends.
- It can optimize product location based on past sales data (e.g., which shelf gets more foot traffic).
- It can assist in forecasting future sales based on previous years’ sales data (e.g., what percentage increase or decrease in revenue was there from last year?).
- Selling products faster – By analyzing historical data about customer preferences, AI algorithms can make suggestions on what products should be promoted and sold quickly
- Trouble-shooting – If there is an issue with one of your products, AI algorithms can help find out what went wrong and fix it before more customers get affected by it
Supply Chain Management
Supply chain management is a complex process and involves many stakeholders, including suppliers, manufacturers, distributors and retailers. As the world becomes more connected and technology advances, it becomes easier for companies to track and monitor their supply chains using artificial intelligence (AI).
Here are some ways AI can be used to improve supply chain management:
Supply chain visibility. AI can help organizations gain visibility into their entire supply chain by providing real-time data analytics. This includes tracking the location of products throughout their journey from production to delivery at retailers. This information can be used to optimize routes, reduce costs and ensure customer satisfaction.
Advanced forecasting. AI has the ability to predict future demand based on historical data analysis and also allows companies to forecast customer demand based on customer sales history as well as weather patterns or economic indicators.
Optimization of inventory levels. AI can help businesses optimize their inventory levels by analyzing customer demand patterns and identifying gaps between demands and available inventory levels. This helps them avoid overstocking or understocking products in warehouses while ensuring customers get the products they need when they need them most — which increases customer satisfaction and loyalty.
Pricing
A recent study found that more than half of all online shoppers say they’re more likely to buy something if it’s offered at the right price. That means that getting pricing right is crucial for retailers trying to win over customers.
How can ecommerce companies use AI in this area? Here are three ways:
- AI-powered price optimization helps retailers find the best prices for their products. With the help of artificial intelligence, you can use historical data and real-time information about your competitors’ offers to determine how much you should charge for specific items. This approach provides more accurate results than simply looking at past sales data or inputting current prices into an algorithm.
- AI-powered dynamic pricing allows merchants to set different prices based on demand, which means they can sell more items at higher prices when there’s less demand for them (such as during off-peak seasons). Dynamic pricing makes sense for retailers who want to maximize their revenue by selling out-of-stock items at higher prices when possible or by offering discounts when appropriate.
Fraud Prevention
Fraud is one of the most important challenges facing ecommerce businesses today. Fraudsters are becoming more sophisticated every day and it’s up to you to keep up with them.
Artificial intelligence can help you stay ahead of fraudsters by identifying suspicious transactions before they occur. It also helps you detect fraudulent activity after it happens so that you can take appropriate action as soon as possible.
One fraudulent transaction example is:
Card-not-present fraud – This occurs when a person completes an online transaction using their card details but without physically presenting their card to anyone at the time of purchase. Card-not-present fraud accounts for around 80% of all online fraud according to research from Visa Europe Collab acceleration program report 2020 edition: Fraud prevention through tech innovation. This type of fraud can be reduced with the use of artificial intelligence technologies such as two-factor authentication or biometrics.
Artificial intelligence is a powerful tool that can be used to prevent fraud. Machine learning algorithms are trained on historical data to detect patterns of fraudulent behavior. When new transactions occur, the system compares them against the historical data and classifies them as fraudulent or not based on the probability of fraud.
AI is particularly suited for ecommerce because it can be applied at every stage of the transaction process:
Online shopping platforms use AI to analyze shopping cart data and prevent abandoned carts from turning into chargebacks. This can increase conversion rates by up to 30%.
Merchants use AI to assess buyer risk before approving orders so they don’t have to manually review each one.
Payment processors use AI to evaluate individual transactions for risk before sending them through their systems so they don’t get hit with chargebacks. This can also keep transactional costs down by reducing chargeback fees.
User Experience Personalization
Personalization is a key factor of the modern ecommerce industry. It helps retailers to create a unique experience for every customer and provides them with a personalized shopping journey. However, the traditional approach to personalization has its limitations: it’s time-consuming, difficult to scale and requires significant investments from retailers. That’s why more and more businesses are turning to artificial intelligence for user experience personalization.
Personalization has always been a key part of ecommerce, but with the growing use of AI and machine learning, it’s become easier than ever to tailor content and products to each visitor. This can be as simple as offering customized recommendations based on past purchases or browsing history. It can also include more complex methods like understanding what items are most relevant based on past behavior and current location.
The more personalized your website is, the better chance you have at converting visitors into buyers. This can be especially important if you’re selling products that aren’t easily comparable — for example, fashion accessories or electronics.
Customer Data Platform (CDP)
Customer data platforms (CDP) are a relatively new and emerging technology in the marketing world. They’re designed to help marketers better understand their customers and target them with more effective advertising.
Ecommerce businesses have a lot of data to manage: real-time inventory, order history, loyalty program information, etc. This makes CDPs especially useful for ecommerce sites looking to improve their customer experience and generate more sales.
CDPs are used in ecommerce to manage and analyze customer data from multiple sources. The goal is to collect information about customers in one place so it’s easier for marketers to make decisions based on what they learn.
Ecommerce companies have been early adopters of CDPs. With the rise of omniChanel retailing, brick-and-mortar stores need to be able to track and engage with customers who visit their physical locations as well as those who shop online or through mobile devices. CDPs can help them do that by connecting customer data across multiple channels.
Wrapping up
With the growing speed of ecommerce industry, competition is rising and considering most of these companies are well-funded, businesses will have to adopt more advanced technologies like Artificial intelligence / Machine Learning to win over the customers.
AI is one of the best things to happen in ecommerce. It provides us with endless opportunities to increase sales and conversions by offering unique and personalized experiences to our customers. AI will become one of the determining factors for ecommerce businesses in their ability to remain competitive.
