Tue. Jul 16th, 2024

Top Applications of Data Science in eCommerce Businesses

Both Data Science and eCommerce businesses are giant trends that are emerging with enormous momentum. This may be the biggest advent in the trading history of mankind. Data Science is progressing at a tremendous rate and shows no signs of slowing down in its application in a wide range of spheres and eCommerce is one of them. With the expansion rate of 50%, most eCommerce businesses are resorting to technologies like Data Science. 

Even if you own a small eCommerce business as an individual you are up in the front to make big bucks online through various business models like dropshipping. There are eCommerce businesses that are resorting towards data science to leave the competition behind by acquiring more customers and retaining the old ones. If you are curious about what data science can do for your business read ahead.

One hint to enhance your business online is that you should display your Chipboard Packaging boxes in beautiful and high-resolution images and videos because the packaging is proven to compel customers into buying products weather the business online or offline. People like to buy shiny, shimmering and beautiful packaging more than the product inside.

Of course, as a good businessman, you will have quality checks for your products and you will not sell crap in awesome looking packaging. There are successful companies that spend more time, effort and money on making the packaging of the product look better than the product inside but that does not mean that they ignore what they are selling.Here some of the few most prevalent applications of data science in the eCommerce industry.

Online Recommendation Systems

Recommendation systems are the application of data science that is helping eCommerce companies to retain customers with a huge success margin. The websites that are giants on the Internet like YouTube, Facebook and Amazon all use recommendation systems to suggest information and products to their users. As an example, if you have watched videos on eCommerce lately on YouTube algorithms developed by data scientists automatically start to present videos similar to your search. On the same note, if you have searched for jackets on Amazon or other huge online retailers, the recommendation systems will suggest you other fashion products similar to jackets. These recommendation systems have added huge values to many eCommerce stores and online markets.     

Customer Life Time Value

Simply put, customer lifetime value is the estimated anticipation that realizes how much the customer will contribute to the interest of an (eCommerce) business. In more simple terms a simple algorithm can be constructed that is the multiplication between the average values of the order multiplied with the Number of recurring orders which is again multiplied Average customer life span (The time for which the customer remains loyal). The bigger this multiplication results in the form of a number the value the customer is to the business and vice versa. This is just an oversimplified form of what this data science application does, several other ways include statistics and mathematics to come up with conclusions about the customer value.

Warranty Analysis

If you are selling products online that come with a warranty such as electronic devices then data science has solutions for your business problems in this area. The data of the product identification, product life cycle, type of problem, number of returns are traced with methods devised by data scientists. This information is also useful in keeping a check on fraudulent activity that leverages warranty of products.

Price Optimization

The objective of businesses is not just to sell products in high-quality packaging like custom Kraft boxes but the businesses need prices that benefits all parties while they make a profit and gain customer satisfaction. Machine learning algorithms that deal with price flexibility, location of the purchase, buying attitudes, and competitor pricing and as an outcome it provides the data scientists with valuable information that help them to optimize the prices of the business. This is a very powerful tool that sprouts from the marriage of eCommerce and data science that helps businesses position their products correctly.

Fraud Detection

The eCommerce sites are geared towards making more and more customers. The security of their payment systems is a big challenge against hackers. A hack into an eCommerce site spells disaster and may disrupt or destroy the business altogether. Despite efforts form eCommerce sites the black money rakes in billions that come from fraudulent means. This practice continues to grow but now data science comes to the rescue to detect fraud before a major catastrophe to the business strikes.

More and more the eCommerce businesses are resorting to machine learning techniques that are used in data science to identify suspicious online activity. The machine learning algorithms that are devised to catch fraudulent behavior look for patterns in the user information who might be someone with malicious intentions.

Customer Retention

Businesses are not a onetime selling game. Businesses are formed with repeat and satisfied customers. This is the basics of business every online or offline business knows. Customer retention depends on a concept that is called a “churn model.”

Churn model helps the eCommerce business to look for customers who are may in the future go to other eCommerce websites. Once such customers are indicated through an algorithm, the eCommerce company is bound to take action to retain those customers for further by sweetening the pots with other deals. The Churn models help calculate the churn rate depending on the nature of the eCommerce business.  

All eCommerce sites that are growing in business need the helping hand of data science. In this write-up, only the very few benefits that data science offers to eCommerce businesses are mentioned. There is much more than data science can offer insights to managers and decision-makers to come up with solutions to problems the modern online businesses face.

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