Industry experts suggest the leaders of the future would spend only 50 percent of their time in managing people. Remaining 50 percent would be spent on monitoring robots, algorithms, data, and other software. The prediction is sufficient to elaborate on the importance of AI (Artificial Intelligence) and ML (Machine Learning) in the future.
The processes that are found to be rigid, repetitive and extensive are managed with the help of AI and ML. These days, thanks to chatbots, even routine customer service tasks can be carried out with the help of software alone.
What’s the use of machine learning in ecommerce?
The AI in Ecommerce is mainly based on data, and is more of ML, as of now. The term machine learning (ML) has been around since 1956, and scientists recognized that it was efficient to teach computers to learn instead of programming them to perform the given task. This capability is known as machine learning. A subset of ML, called deep-learning uses a set of algorithms, enabled IA to tackle problems.
As mentioned earlier, ML focuses on learning from data rather than depending on programming. Gadgets collect data all the time. It is not just for knowing customers and offering better products. It is also to empower algorithms and machine learning ecommerce. Natural speech, spoken words, videos, written words, and pictures can be used for feeding the ML software. The e-commerce industry is getting benefitted from the same. Algorithms get better with every search, every purchase, and every abandoned cart on the e-commerce portal.
Believe it or not, e-commerce websites like Amazon can even track consumer’s behavioral biometrics, including keystrokes and mouse movements. All this data is used for creating a perfect customer profile which is further used for making decisions like whether to offer urgent delivery, cash on delivery, and rich discounts to retain the consumer or not.
Machine learning in ecommerce helping firms to predict cancellations
The effects of artificial intelligence are visible in the form of millions of dollars in savings as well. Technology is helping companies to use AI and machine learning to understand their customers’ behavior. A certain percentage of orders get rejected by customers. As the product returns from the consumer’s doorstep, it suffers damages. AI helps in predicting orders from customers that might get rejected. If the probability of rejection for the customer is greater, the system automatically removes discounts, cash-on-delivery option from the consumer’s account when he or she visits the portal to make purchases.
Companies use past data to find a pattern based on pin code, address, order date and time as well as the selling price, to surface the probability of order rejection from the customer.
Helps in choosing the best delivery options
At times, e-commerce firms place their inventory at multiple locations. If the customer residing in Mumbai has to be served a product kept at the company’s warehouse in Delhi, the firm can either deliver the product expediently in a day or take the usual three days.
The product can be delivered to the consumer in one day by sending it over the flight by spending a little bit extra in transportation, or it can be provided in three days using other (usual) modes.
Data can tell if the customer would be delighted to get the order in one day and come back for buying more items. Machine learning looks at past patterns of orders placed by the customer and points out the future order-stickiness. It also checks if the time taken to serve the request can be correlated with future orders. The system automatically selects the best delivery duration according to the rules set by the firm and the customer’s rating.
AI-driven personalization software
Almost every big ecommerce player has AI-driven inventory-based product recommendation software in place.
The way it processes data is straightforward. Take Wine Ring’s wine selection preference engine as an example. There are one hundred thousand wines made every year. Even the most accomplished wine expert won’t be able to taste all of them each year. Thus, machine learning can surely make things easier. The firm’s patented algorithm understands the user’s wine preferences like a human being over time. Users need to download the app and give feedback for various wines that they have tasted. Once the system receives and processes a handful of ratings to get a sense of preferences, it allows a consumer to take a screenshot of the wine label at the store and predicts if they would like the concerned wine or not.
Users need to program their taste preferences in the app, indicating the wines that they love. All these metrics are stored in the user’s profile and accessed whenever the consumer requests a prediction. Most of the recommendation engines deployed by online shopping sites work similarly.
What’s the future of machine intelligence? Who would win in the artificial intelligence vs. human intelligence race?
No doubt, routine tasks can be automated to offer effectiveness and greater efficiency.
AI and ML are crucial elements for monitoring online activities. However, machines cannot be sarcastic; they cannot understand the emotions in images like humans. Even today, AI/ML powered chatbots and virtual assistants like Siri, Amazon Alexa, Microsoft Cortana, etc. can help in placing orders, but cannot be used for solving complex customer service issues like billing disputes. Similarly, AI alone is not capable of closing big sales deal, but can surely help a human sales rep with negotiating techniques.
Thanks to AI, data can be used for predicting future business needs and planning resource allocations accordingly. It can be used for offering a great experience to the customers and empower the organization’s employees. But, the question that everyone often asks is whether technology can completely replace humans. Who can answer this better than someone from Amazon? According to Raghava Rao (Amazon India’s VP and CFO), it cannot offer a human or leadership type of judgment when it comes to doing the right things.
Several essential activities of the e-commerce portal can be automated to provide greater efficiency and effectiveness without emptying the bank account. Simple widgets can change the primary e-commerce search feature into an AI-powered search and recommendation engine. You can also turn your basic website into a portal that can get better ranking in voice search results. For more details about the use of artificial intelligence in retail, you should consider chatting with one of Smart Sight Innovations engineers today.
