ETEAM Blog How Artificial Intelligence Can Be Utilized In E-commerce And Help Buyers Make The Decision

Artificial intelligence continues to modify the world of online shopping today, and AI is creating a new system for e-commerce stores to operate and provide better services to their customers.

Right from offering virtual buying assistants to creating personalized shopping experience, AI is changing the online shopping experience for both retailers and customers by providing new ways to analyze big data and help e-commerce stores engage with their customers on a new level and create superior customer experiences.

With AI, e-commerce shops can analyze consumer data to predict future purchasing patterns and make product recommendations, based on their browsing patterns. According to a recent report by “Business Insider”, it is estimated that by the year 2020, about 85% of customer interactions will be handled without a human. With the growing influence of phone calls, emails, and chats, all being controlled by automated systems, this looks very possible. There are already various small-scale testing implementations of this concept.

AI is expected to de-clutter the shopping experience and avail them a plethora of options all at the click of a button. Simply, AI is helping transform customers experience and help them make better decisions from remembering a customer’s tastes and preferences, monitoring their search patterns and providing every individual with their choice of products. AI is redefining the way customers shop online. It is helping them make better decisions by correctly understanding the features that are desired by the customers and gauging their preferences accurately.

Looking into the different ways in which AI can be utilized to help buyers make better decisions, it includes:

AI MONITORS CONSUMER PATTERNS

With artificial intelligence, e-commerce stores can monitor the browsing patterns of a consumer, store the pages the visit, and note the websites which they regularly view and as per the result of this, recommend products which a customer is likely to purchase.

According to American Research firm Gartner, 85% of customer interactions will be handled without human intervention by 2020.

CHATBOTS AS ONLINE SHOPPING ASSISTANTS

Just the way offline shops have salespersons, shopping assistants are emerging online in the form of chatbots. Chatbots are software programs designed to simulate a human-like conversation with users. AI-powered chatbots employed by e-commerce stores help fulfill the needs of a store person in the online space. We are already seeing regular customer questions being funneled down a question / answer algorism that is reducing live chat time utilized. This trend would only grow with the eventual live chat being automated as well until a resolution is not reached where a live person can join in. In an another work around, one person could monitor multiple chat bots at the same time thus increasing productivity ten folds.

These chatbots are smart and intuitive and designed to perform simple to complicated tasks. E-commerce websites introduced chatbots to improve the shopping experience for customers, to help them with immediate response to their queries and provide 24/7 support. The advancements in AI and machine learning have led to smart and intuitive chatbots which not only provide relevant recommendations to consumers but engage in casual conversations with the customer. This way, modern chatbots are driving more transactions, earning customer trust and enhancing the chances of repeat purchases.

MACHINE LEARNING IMPROVING PRODUCT SEARCH

One of the most promising tools in artificial intelligence is machine learning. It can standardize product categories and quickly apply knowledge from large data to recognize patterns, objects, speech, visuals, etc. making it easier for customers to find their favorite products most conveniently. Machine learning has even improved product search capabilities in e-commerce. It can provide customers with the right preferences based on their search criteria. Machine learning algorithms are so advanced that it can provide personalized recommendations and acknowledge the shopper’s intent based on their shopping patterns, personal information, and profile data and so on.

RETARGETING POTENTIAL CUSTOMERS

Data from Conversica reveals that at least one-third of marketing leads don’t get followed up by sales staff. This means that pre-qualified potential buyers interested in your product don’t get converted. This is despite many companies being overloaded with customer data which they can do little or nothing with. This provides a goldmine of intel which can be used to enhance the sales cycle.

With AI, you will begin seeing products on your screen based on the time you spent at a particular store. This gives e-commerce store operators a chance to remarket their products customers. This is changing the face of shopping as e-commerce shops can now respond to their customer’s leads and impulses.

HIGH-END SECURITY

Work is on to ensure that in the coming years, AI will help e-commerce shops gain customer loyalty by protecting them from online fraud activities. Apart from this, AI will also help fetch more precise behavioral predictions and fasten the checkout process. According to a report, 13% of buyers reported that security is the major reason why they leave their carts abandoned. With the help of artificial intelligence, entrepreneurs will be able to use high-end security to provide peace of mind to its users.

AI AND ROBOTICS IN E-COMMERCE

AI and robotics are driving efficiency and helping customers make better purchase decisions. Some shops apply robotics to read RFID tags, and since each customer order cart has an ID unique to it, the bots can determine when a filled cart is ready for dispatch, thereby saving several precious productivity minutes. This is one example of how AI is changing is reshaping the e-commerce experience for many customers fueled by new technologies like machine learning, virtual reality, robotics, etc.

Research is even going on to determine why deviations occur in customer shopping experience and by being able to determine this difference based on past behaviors, they will be able to predict when the next deviation will occur possibly.

CONCLUSION

In the future, one can predict that more and more AI will be used to create multi-layer data on every customer based on their past and current buying behavior, and almost accurately predict their future behavior. With this sort of intelligence used in site searches and targeted adverts to potential eCommerce customer, the future will very much be reliant on AI. This won’t unquestionably end there, we will most certainly see its presence in logistics and further streamed line automation. For that to work, smart connected systems will be a pre-requisite.

One fact is clear, the human brain is the most complex machine that exists, and creating any tech that can even ‘think’ of understanding it, will be a long process which seems almost inevitable in the current environment.

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