eCommerce platforms have grown in popularity in the past decade; with it, common ecommerce marketing questions have come. With the pandemic, online shopping boomed, and more people shifted from traditional brick-and-mortar shops to virtual shops. Though eCommerce platforms are doing well in sales, there is a growing concern for user experience. Specifically, customers complain about the overwhelming volume of products, difficulty finding what they need, and the long shopping process. This is where machine learning comes to the rescue. This blog will explore how eCommerce platforms can leverage machine learning for a better user experience.
1. Personalized Recommendations
Ever visited an eCommerce website, and the products shown on the homepage or in the suggestion column seem eerily spot on to your preferences? You can thank machine learning for that. Machine learning algorithms, fed with a customer’s past purchases or search history, can create personalized recommendations tailored for that specific user.
This saves customers time and energy in finding products they want, and eCommerce platforms increase their chances of selling. For example, Amazon has been using personalized recommendations to great success with the help of its machine learning algorithms.
2. Chatbots For Customer Support
Human customer support representatives have limitations, such as limited availability or lack of knowledge on every topic. However, with machine learning chatbots, customer queries can be responded to 24/7, with reliable answers, despite the complex nature of the question. These chatbots can recognize and respond to natural language input, support the most commonly asked questions, and more accurately route customers to the correct information or support bureau.
This, in turn, increases customer satisfaction, and eCommerce platforms with an intelligent chatbot support system can edge out the competition. Additionally, machine learning can improve existing chatbot systems by continuously analyzing customer interactions and offering more accurate solutions.
3. Visual Search
More often than not, customers have a vague idea of what they want to purchase and aren’t sure how to describe it. With visual search capabilities, users can upload an image of the product they need or desire, and the machine learning algorithm can find similar or exact results. This option is much more user-friendly than typing in the search bar, and it saves the customer time that they would have spent looking through multiple products to find what they want.
4. Adaptive Pricing
Dynamic pricing or personalized pricing means using machine learning algorithms to adjust the prices of products based on factors like inventory, demand, and customer behavior. When the system analyzes a specific customer’s purchase history or behavior, it can determine the prices they’re willing to pay and adjust prices to make the customer more likely to purchase. Adaptive pricing models can also reduce surplus inventory and help eCommerce platforms optimize their sales strategy to correspond with the dynamic online market.
5. Fraud Detection
One significant problem in the eCommerce industry is the issue of fraud. Machine learning algorithms can detect fraudulent patterns in real-time accurately. When a customer attempts to pay, the system can detect fraud by analyzing multiple factors, like the device used, location, and past purchase history. This makes eCommerce platforms safe for users to shop and benefits the platform financially in the long run.
In conclusion, machine learning has a significant role in enhancing the user experience on eCommerce platforms. With the assistance of machine learning, online retailers can need eCommerce platform customers’ needs more effectively. Personalized recommendations, chatbots, visual search, adaptive pricing, and fraud detection are just a few ways machine learning can improve the user experience, making customers happier and more likely to re-visit their platform. With the growth of eCommerce predicted in the short term, leveraging machine learning to improve the user experience will positively impact the profitability and growth of eCommerce platforms. Harnessed correctly, it can create a win-win for online retailers and customers.