Machine Learning and its Impact on the Ecommerce Industry
Technological advancements are the biggest game-changer in the revolution of the e-commerce industry. Like AR & VR, artificial intelligence, specifically machine learning, have a profound impact on e-business. According to research by Gartner, more than 80% of e-commerce website’s customers are managed by the grace of ML.
It is interesting that one-day computers would be able to make decisions more than humans based on recognizing & learning data patterns. Machine learning has been playing a significant role in the immense evolution of the e-commerce industry such as in marketing, sales, or even in inventory management systems. By using various kinds of machine learning applications & tools, you are capable of analyzing the latest trends & making cost-effective decisions.
In simple terms, we can define machine learning as learning your machine about some specific data( where words, typos, phrases are common) by developing an algorithm. Here, learn the means to test your required algorithm with some given patterns. There is a thin line between machine learning & artificial intelligence. ML is a subset of artificial intelligence, where you need to use a process or algorithm to improve for better performance(predict future trends & outcomes) over a period of time through some experience. On the other hand, AI is a machine that can process automated tasks by mimicking human activities.
Incorporating machine learning into e-commerce a small webshop can generate millions of datasets on a daily basis, which is nearly impossible for an experienced team to gather for providing a customized experience. In this article, we are going to share some most used ways of machine learning that have an impact on e-commerce.
5 Machine Learning Ways Have Impact On E-Commerce Industry
Here are the five ways machine learning impacts the e-commerce industry:
Machine Learning & Price Optimization
Selecting product prices based on market demand & competitors has always been a crucial factor for e-business owners. 47% of the cart abandonment rate happens only for the high price of the product than the competitor's product. Even variation in shipping price is also a big factor behind this. Besides this, if your targeted audiences are global then you need to analyze the shipping cost & set the pricing depending on the location, For this, you need to gather the bulk amount of data & then process these to obtain fair & ideal pricing.
The machine learning algorithm perfectly works here by combining competitors’ prices, new pricing trends & demands for items. Product supply & product demands play a vital role & influence pricing. You can’t always set all the product prices manually. Via the machine learning process, you can assess supply & demand, promotions, etc to retain an ideal price & also this algorithm helps to dynamically change the prices whenever you need it.
Machine Learning & Image Processing
Image processing & recognition is the practical area of implementing machine learning, also it has a great impact on e-commerce websites as a product search feature. Image recognition is an essential part of online stores.
Basically, this process lets customers input data by uploading their own captured image & the ML algorithm helps to find out the similar product available on the store’s server & display the products along with the current price & shipping details on the display. In this way, the purchase rate gets higher as it is considered as the most used & convenient shopping method. Another way of using image processing is to display alternative products of the given image so that, the user can choose from the best options.
Machine Learning & Customer Experience
Providing customized solutions is the ultimate motto of all e-business owners. To enable a customized service you need to segment your customer base & then target those customers with their required service. In the traditional business model, salespeople used to do all the work like approaching customers, observing their behaviors, attending to their queries with the solution & creating demographic information about the customer. But with the help of AI & ML, this can be possible in no time.
When customers land on your website & try to search for an item using their natural language, a background algorithm can detect the previous search history or activities on the internet. Relying on this information, it shows personalized as well as relevant information that allures them to purchase. ML holds the ability to personalize each & every small interaction on the basis of customer data & behavior that ensures a better user experience. One of the ideal examples of personalization solutions is the product recommendation feature of e-commerce sites.
Machine Learning & Robust Search Result
To provide customers with a better experience, owners should leverage deep search options for onsite search. Implementing machine learning on e-commerce search results offers a payoff to the owners. Giant companies like eBay & Amazon are incorporating AI, and machine learning & enjoying a full advantage of data prediction, and robust & most accurate search results.
Machine learning algorithms enable you to enable your users to look for the synonym of the targeted keywords instead of depending on the traditional keyword search. ML helps to analyze the data like previous search history & recommend you the best similar products & cross-sell items that are usually bought by consumers. The advantage of leveraging this algorithm is- it increases the click rate for a particular keyword & helps to rank on the e-commerce in-house search result.
Machine Learning & Fraud Detection
E-commerce websites are the most vulnerable place for any fraud or cyber attack because of the bulk amount of user data. Sometimes, ReCaptcha is not enough to detect the unusual behavior of fraud users. Integrating ML algorithms can help you as a shield as it can analyze any type of data that ensures a safe & secure transaction.
Using machine learning algorithms you can train the process with normal as well as unusual data patterns that are harmful to your website. As a result, it helps to detect any repetitive patterns that are not similar to the normal human behavior such as the bulk amount of form submission, filling forms too quickly, entering multiple information within a second for checkout & many more.
Wrap Up
Besides these popular use cases, other e-commerce business benefits of using machine learning are: boosting conversion, running relevant marketing campaigns, improving in-house business operation, making better decisions & many other activities. If you have started your very first e-commerce business & still have not adapted any machine learning tools then it is high time to get knowledge about the above-mentioned process & start implementing those for the growth of your business.
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