Because of evolving technology and new advancements, eCommerce businesses can now use a wide range of data and machine learning tools that help them improve sales and make more profits. These technologies allow retailers to set a seamless customer experience by solving common problems of visitors, automatically.
As a result, online retail revenues are expected to rise to $5,4 trillion in 2022 and retailers are doing everything possible to capture maximum sales. Data science is one such technology that can transform the eCommerce industry in 2022 by making a huge impact on the way retailers sell their products.
From healthcare to education and retail to transportation, each industry uses data science in one way or the other to get maximum benefits. Therefore, there exist many ways in which data science can transform the online shopping industry.
With the help of collected data, businesses can improve customer experience, increase sales, prevent frauds, and do so much more. This article lists five ways in which data science is likely to change the eCommerce industry trends forever.
Better Price Optimization
Price is an important factor when it comes to making a decision while shopping online. Thus, eCommerce businesses need to set the price right to make maximum profits. Data science can help online retailers build a competitive pricing strategy by analyzing factors like market segmentation, customer behavior, and cost analysis.
Generally, eCommerce businesses use tactics like allowing early access to sales for loyal customers or implementing different pricing strategies based on the location of the store visitors. Up until now, most of the eCommerce retailers used to do it using traditional pricing strategies like cost-plus markup or manual price management. But in 2022, these old-school tactics will no longer work.
The eCommerce industry is dynamic and retailers will have to upgrade their operations accordingly to stay competitive in the market. With technologies like Data Science, they can now look at the big picture, analyze prices offered by their rivals in real-time, and make an informed decision related to setting the price of products.
According to reports, Amazon's 35% of revenue is generated with the help of recommendation engines. And data science is the technology behind the robust working of these product recommendation engines that help eCommerce businesses boost sales. Recommendation engine works on finding patterns depending on customer behavior data and help increase sales in three ways:
Convert Visitors into Consumers: Most of the visitors on an eCommerce website are window shoppers. But, it is the job of recommendation engines to convert them into potential customers by suggesting products that they may like.
Increase Average Order Value by Cross-Selling: When a buyer adds an item to the cart, an eCommerce website's recommendation engine is responsible for suggesting relevant products. For example, an online store might suggest buyers purchasing a pair of jeans when they already have a T-shirt in the cart.
Increase loyalty: Recommendation systems also help build brands a personal relationship with consumers by helping them with finding the products they were looking for, easily. This also helps improve a website's overall customer experience.
The ultimate goal of product recommendation engines is to help an eCommerce business grow sales and increase revenues. And retailers are already leveraging this trend widely to upsell their products.
Insights Into Shopping Patterns and Customer Behavior
In 2022, eCommerce is set to revolve around customers. Retailers that want to secure a competitive edge over their competitors need to serve their website visitors or potential customers in the best possible way.
To empower retailers, data science is helping them determine customer preferences, behavior, likes, and dislikes to find out what influences their buying decision the most. Accordingly, online retailers can set the customer buying journey and present products in a way that makes maximum impact on website visitors.
In 2022, data science will also change the way retailers manage their eCommerce business operations like product marketing, inventory management, supply chain management, and much more by analyzing customer shopping patterns.
Improved Business Processes
Taking care of increasing customers' needs is a major but not only part of an eCommerce business. You need to plan several other things to make sure every business process is executed smoothly. For example, you need to stock the right inventory, plan marketing campaigns, and forecast demand.
In the coming years, online retailers will largely rely on data science and machine learning algorithms for the same. In fact, several eCommerce giants are already using these technologies to manage their business operations.
An eCommerce business collects massive datasets. If used correctly, these datasets can help them predict traffic spikes, plan inventory, make pricing decisions, prepare according to trends, and do so much more to streamline several business operations.
Cybercrimes are not new in the eCommerce Industry.
That's the reason why setting up an exceptional experience and providing good quality products isn't enough to prosper in the online retail world. You need to ensure customer safety to build a loyal user base.
Online attacks can not just result in loss of money but can also affect the reputation of an online business. But data science can help eCommerce businesses avoid such scenarios by detecting any type of suspicious behavior online. In 2022, eCommerce businesses are expected to adopt data science massively to detect and prevent cyber-attacks and maintain platform security.
Technologies like data science and machine learning have been taking the eCommerce world by storm. These technologies help eCommerce businesses increase revenue while improving the overall experience of customers.
Data science helps retailers present the right product to the right people at the right time and this trend will surely affect the way online businesses work, in the near future. How are you using data science to improve your business operations? Tell us in the comments below.