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How Is Artificial Intelligence Used In E-Commerce?

Artificial Intelligence, AI plays a vital role in our lives and its role in e-commerce has allowed online retailers to explore advanced technologies for enhancing the customer shopping experience. This proves that traders are adopting modern ways rather than sticking on to the earlier. The most popular AI applications that are used by e-commerce companies are chatbots to improve customer service, image and voice-recognition for faster search results and recommendation engines with advanced algorithms for accurate product recommendations.

Usage of AI in e-commerce can be in the following ways:

Creation of Customer Centric Search: with the help of AI, one can easily find product which have similarity in its size, brand, color, brand or even fabri. Image recognition software helps in selecting items form the photographs online, its an Pinterest’s recent update of its Chrome extension. AI improves search results for online customers through personalized recommendations. The customer-centric experience is improved where AI interacts with visual elements of search. Images and videos are tagged, organized and used to search similar content.

Retargeting Potential Customers: AI helps in identifying the user’s interest on particular product or any service and also it notices the amount of time the user spends on a specific product. Retargeting is achieved with the piece of code and this code collects the information about location of the visitor and time spent on a page. It also includes cookies which contains data related to visitor’s session.

Efficient Sales Process: AI, integrated with CRM will help in customizing the sales messages, thus helping in reaching right people at right time. AI serves for multitask benefits and CRM serves for providing responses to customer queries and recognizes more opportunities and sales. If your AI system supports natural language processing then customers can interact with your CRM by asking questions and recognizing more sales and opportunities.

Create New Levels of Personalization: Observations on likes and dislikes of the customer helps in improving the personalized shopping experience of the customer. Apart from presenting personalized products, AI can also provide predictions about the customer’s expectations and measure customer behavior. This predictions can be used for future predictions and design customized sales strategy based on customer behaviour trends.

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Chatbots: Modern chatbots are able to interface customer databases and extract the details of customer and responds in more appropriate and personalized way. Chatbot is an effective and low-cost way of providing customer service and can automate order processes. Once the chatbot has been linked with one of the shopping carts then it can work with all other stores depending on platforms.

Implement virtual assistants: Virtual assistants helps in creating more efficient sales processes. Managing customer’s preferences and interaction with customers via different language can be achieved by these assistance. Communication is improved by Natural Language Processing engines to interact through chat, email, audio or video conferencing.

Improve Recommendations: Recommendations will help the customer in finding the best solutions. These recommendations are made based on the past purchases and activities of the particular customer. E-commerce companies are doing best in providing the best recommendations of products based on customer search history and customer behaviour. AI enables online retailers to add personalized pages to their website and give personalized recommendations to the visitors.

AI has huge impact on the way company’s deals with their customers and improves in-store experience.

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Written by rachana

I am Rachana, working as a Business Development Executive at FuGenX Technologies. FuGenX is a CMMi Level 3 company and is a fastest growing mobile apps development company in Bangalore, Delhi, Hyderabad and Ahmedabad, India. It provides services based on Artificial Intelligence, Data Science, Big Data, Automation, Machine Learning, Deep Learning.

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