AI personalization

Application of Artificial Intelligence in eCommerce

Technology has revolutionized the Ecommerce sector like any other or even better over the past many years. E-commerce is one sector for which application has increased in recent times owing to the rise of COVID-19 cases all around the world.

Ecommerce has become more of a necessity than luxury these days with even the smallest of retailers opening ecommerce platforms to survive in tough market situations. On the positive side, the retailers have enjoyed increased sales with Ecommerce applications. Artificial intelligence has added more value to the platform by taking the service to the next level.In this article, we are going to discuss 10 applications of artificial intelligence in E-commerce.

Provide a personal touch with Chatbots

AI ecommerce Chatbot

Implementation of chatbots in E-commerce websites has improved customer support service to a very big extent. Chatbots not only allow 24 x 7 customer service to buyers but also collects the preference of buyers and guides them to products of interest. Most standard E-commerce websites are using chatbots these days and quite often whenever you enter a website you will be greeted by a chatbot and asked to make a choice of your requirement. Based on your requirements the showcased products are filtered. AI supported chatbots are also capable of giving a human touch to the conversation by being able to address the customer’s queries in an intelligent manner. 

Chatbots not only provide good customer support but also enhance the impact through additional capabilities as explained below.

  • Deeper insights about the customer requirements result in better ability to address the customer needs and thereby better customer satisfaction.
  • Chatbots are capable of providing personalized or targeted offers to customers.
  • Self Learning capabilities is an additional feature recently added to chatbots which helps them improve over time as more and more data is populated into the system.

Improve recommendations for customers

Artificial intelligence based E-commerce systems are capable of predicting customer behavior. Many buyers would have wondered how the E-commerce websites like Amazon are constantly showing the products similar to your interest. AI and machine learning algorithms are capable of analyzing the captured data and come out with a list of products which each customer is likely to be interested in. This helps to increase the amount of time a user is likely to spend in the website. Data is captured not only from the purchase history of a user but also the list of products he had browsed through without buying. Various other factors considered for recommendation include browsing location, climate of the year, buying potential etc to name a few.Based on the conclusions reached at, the products recommended are showcased to each customer. To cite an example for the recommendation system, consider a scenario wherein a customer came to shop for a bunch of roses to give to his dear ones and the commodity is out of stock. AI / ML algorithm suggests a suitable replacement to the product thereby negating the impact of a situation where a material of demand is out of stock.

Inventory management

AI ecommerce Inventory

Inventory management is one of the most important areas in an E-commerce business. A regular inventory management application takes care of the stock of materials and also facilitates order of new materials required.Managing this data is not an easy task and requires a well drafted software to manage the same. However there might be situations where there is a sudden spike of demand for certain goods or a sudden dip for some category of foods.But, with implementation of AI into the software, it analyses the data and predicts demand for the goods based on historical data. Moreover, the inventory management system will get better over time as more and more data are fed into the system.

AI systems build a correlation between the current demand and the future demand. Instead of following traditional methods and maintaining heavy stock of commodities in order to make sure that no items are out of stock, with the help of AI we can follow the JIT concept and still make sure that the sufficient quantity of items are in stock. 

Predictive Analytics

Predictive analytics solution gives access to the ecommerce platform owner to a wide range of data and analyze them. The browsing patterns, payment methods, purchase patterns etc are few details recorded by the system while a user is browsing through the website. Imagine a solution wherein the collected data is analyzed and the system comes up with predictions in terms of probable sales volume and quantity of stock to be maintained for the next quarter. There is a huge array of factors to be considered for making these predictions a reality.

AI ecommerce PA

An AI supported ecommerce platform is capable of collecting the user data, analyze them and come up with predictions. The results come handy in many areas of the company. I have mentioned a few of them, moreover both the applications and capabilities of the tool are increasing everyday.

In terms of Inventory management the tool helps to predict the probable sales volume for the near future, so the process owner needs to maintain only the required stock and manage without any dead stock investment. The most preferred inventory management model these days is the JIT (Just In Time) model wherein very less quantity of inventory stock is maintained at any point of time. In this case, a sudden spike of demand might turn risky wherein there might be a situation of stockout for few items.

With the help of the predictive analytics tool a similar situation can be avoided. Similarly the tool is capable of coming up with probable buying interests of a particular customer with details like the comfortable price range, preferred brand or probable items of interest. With this prediction the system can showcase those items in his window which can improve customer retention, customer satisfaction and probable sales too.

Image recognition

Many of us would have come across a product which we like, as a photo or for eg. someone wearing a dress . Since you have no idea from where the product can be bought, it’s practically impossible to buy the product without knowing it’s source. Luckily Artificial intelligence has brought a solution to this problem. Based on the taken photo Artificial intelligence can select the particular product on the list and also show related products. Customer preference is mapped and the program comes up with an optimum product list. The site also records customer data and showcases a similar product list based on customer preferences.

Natural Language Processing

NLP is an AI tool which helps computers to understand, interpret and manipulate human language. A normal search engine in an ecommerce platform would be equipped to accept regular search terms and direct the search queries to apt products. However in the new era of search engines where Google and other search engines are providing information at fingertips to any user, the shoppers expect to enter a random phrase or even an idea into a search box and instantly see personalized recommendations that are clearly relevant to what the user was looking to discover.

Below mentioned are a few reasons why NLP has become a very important tool for an ecommerce platform.

  • As explained above, the buyer expects the system to lead the user to the exact product even when an abstract idea is entered in the search column. If the search text is not decoded the business owner will lose the customer even though the required product might be available in the store.
  • Proper data mining will not be possible unless the search text entered by the customers is interpreted and decoded into a standard format which can be understood by the system. Data mining being the initial stage of data handling, NLP will help the system to have proper structured data for further analysis.
  • NLP can also be used to analyze customer voice calls and emails, thereby measuring things like customer satisfaction.

Dynamic Pricing

Dynamic pricing, also referred to as surge pricing, demand pricing, or time-based pricing is a pricing strategy in which businesses set flexible prices for products or services based on current market demands. This feature is implemented in the back end operations of many major ecommerce platforms like Amazon, Flipkart etc. When a seller is selling a commodity on an ecommerce platform he provides a price range within which his commodity can be sold.

Support & Maintenance

The AI based system analyzes demand of each item and adjusts the price of the item accordingly based on different situations. For eg, during a discount sale, the selling price of items will be at lower end. Selling price of an item of high demand being sold fast would be at a higher end. The tool has found applications not only in ecommerce websites but also in airline websites, hotel booking platforms etc. Many would have noticed that, as the number of hits in searching for a ticket or booking a room increases the price of service also increases.

Logistics Planning

AI Ecommerce Logistics

AI is capable of properly plan the delivery schedule and routes for the delivery person to make his daily schedule of delivery. In a regular day to day scenario wherein the business owner has a list of products to be delivered and the list of customer addresses, the tool can schedule the most optimal delivery plan with minimum number of workforce within the scheduled time span and covering minimum distance. Having said that, there are plenty of variables involved and the business owner can prioritize the variable as per the requirement. Based on the designed delivery schedule the customer is also informed of the approximate delivery time of their product.

E-commerce websites have made life easier for the buyers and the sales volume is increasing exponentially over the past many years. With the introduction of Artificial intelligence to the platform there is huge value addition which has resulted in higher customer satisfaction, engagement and retention with last human interaction and effort.

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