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AI-enabled computer programs can think, learn, and act in particular situations as humans do. When these intelligent programs are applied to machines, they can understand and improve without human intervention. E-commerce is one such everyday use case where merchants are increasing their sales by leaps and bounds using this technology. Salespeople and customer representatives are now more empowered with chatbots and other AI-enabled programs that quickly solve customer problems and answer their queries. In fact, some companies have almost replaced manual conversations with AI-enabled chatbots.
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To understand the role of AI in powering e-commerce sales, let’s first look at Amazon. It leverages artificial intelligence in many ways, and it’s not just about the Alexa voice assistant or the Echo smart speaker line. The e-commerce giant uses AI across all aspects of business operations – from customer service to product recommendations to supply chain management. Its suggestive selling features end up accounting for 35% of customer purchases. The second major AI strategy it uses is enhanced search. It doesn’t just sell products, but also tries to create interactive and effortless shopping experiences as much as possible through its site. That includes making sure people find relevant results quickly. To accomplish this goal, Amazon relies heavily on machine learning algorithms to analyze user behavior and determine which pages should be shown to users based on past searches. This approach helps to ensure that every page on Amazon is optimized for relevance.
Similarly, several developments have been made in artificial intelligence to advance the e-commerce industry by effortlessly increasing sales and making any product within reach of any user sitting in any corner of the world.
Suggesting Personalized Recommendations
AI-powered personalization tools were developed with the goal of better understanding customers in mind and creating meaningful customer journeys through automated marketing systems. These programs use machine learning algorithms to analyze large amounts of data collected from various sources, including social media platforms like Facebook or Google Analytics. E-commerce websites use recommendation engines that use algorithms to filter customers’ data to suggest popular products and products based on their purchases.
Amazon improved its personalized recommendation to suggest items based on users’ shopping experiences. Their algorithm analyzes customer information such as purchasing data, page visits, and the products they need to suggest to them, and demographic data of buyers that they already have or eventually get from the customers such as age, geographic locations, gender, etc.
AI-driven personalization helps retailers:
- Increase conversion rates across all channels
- Improve the overall user experience
- Maximize ROI
Providing Voice-Based Search Experiences
Voice commerce is about searching for items based on voice and creating intuitive shopping experiences that power e-commerce sales. It’s an intelligent shopping experience enabled by artificial intelligence and machine learning that makes websites and apps smart enough to capture customer behavior.
Alexa is perhaps the best example to describe the crucial role of voice-based search and shopping experiences. Voice assistants like Apple’s Siri can also remind you to purchase products you frequently purchase and missed in the current shopping list.
Google optimized its search engine algorithm for understanding the meaning of the entire search query, and the algorithm was then called Google Hummingbird. Before this, it was merely search based on the keywords and learning to determine the content relevancy.
This changed how search engines handle operations by driving voice recognition and intrusive devices to make shopping experiences easy and more interactive. In short, all big players, including Amazon, invested in intelligence-based voice technology to give voice commerce experience to their users. This functionality has undoubtedly given more reasons to customers to interact with online shopping websites easily and make their shopping even more effortless and at their fingertips.
Creating an Efficient Sales Process
E-commerce businesses are now integrating artificial intelligence into their CRM to reach out to their customers more effectively. These AI-enabled systems use natural language processing (NLP) and learning to answer customer queries and proactively hop on the opportunities to help customers solve their problems. Many AI-driven CRM systems multitask to handle these sales functions. Popular e-commerce retailers The North Face uses IBM’s AI solution, Watson, to proactively ask customers questions in order to provide them with a more comfortable and personalized experience. For example, if a customer is buying a jacket, their website would ask questions like, which occasions would you wear this? This can be done through voice input AI technology. This creates a smart and efficient sales process to put the right products at the right place and time, resulting in more sales.
The rise of artificial intelligence has given businesses more opportunities to automate processes across multiple departments. For instance, chatbots can handle routine tasks like order processing and shipping while human agents take over high-value interactions. In addition, predictive analytics can predict which orders require additional resources before they’re placed, allowing you to allocate staff accordingly.
One study found that nearly half of all U.S.-based retailers plan to implement some form of automation within three years. Automating operations also provides more value to the end-user since these operations keep merchants updated with the customer purchase history data and derive analytics based on the data. The key here lies in understanding how people think about buying products and services – in other words, knowing the audience better.
Using In-Store Intelligence
As online retailers are experimenting with chatbots to assist customers without appointing humans and to give instant information, in-store experiences are also transforming with the help of AI-based robots. Lowe’s, for one, is known for assisting and greeting customers with their shopping assistant robot. This has improved overall customer engagement and experience. Besides this, e-commerce giants study sales trends over the previous years, analyze product demands, and estimate future sales. Based on that, they deal with supply-related issues that could impact inventory levels.
Moreover, some e-commerce giants are predicted to use automated robots to manage stocks 24/7 and quickly dispatch ordered items in precise orders. These applications eventually add to more intelligible customer experiences that could potentially improve product sales.
With its product recommendations, voice recognition capabilities, virtual assistants, tracking customer behaviors, and many other ways to know customers better each day, AI is transforming the future of online shopping. Integrating AI-enabled programs into e-commerce apps has now become mainstream for modern businesses.