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10 Data Science Projects E-Commerce Businesses Are Using

10 Data Science Projects E-Commerce Businesses Are Using - CS-Cart Blog


The e-commerce business is crowded with everyone struggling to get a piece out of the whole cake. Most enterprises are employing data science as a means of beating the competition. As a business owner in this niche, you should equally think of the same. Below is a comprehensive list of ten of the best data science projects that e-commerce businesses are using:

1. eCommerce recommendation system

The use of recommendation systems has made the e-commerce field more professional in dealing with clients. So, what even is a recommendation system? Well, for starters, this is an intelligent subclass of information filtering command. It predicts the preference of a client to a particular product. It achieves this by analyzing a client’s past internet experiences and searches. It helps customers to select specific products that interest them the most.

‘To set up a recommendation system for eCommerce, you will either need to use content-based filtering, hybrid recommendation filtering or collaborative filtering’—says Tom Mendes, the specialist from the HR system.

2. Customer retention

The churn model—e-commerce sites should embrace this project firmly. Customer retention appeals to retain customers after a specified period. It is a vital part of any business as it ensures that your company gains more from returning customer, as well as prospects. A happy customer is always a returning customer. However, one will only return when they get a reason to. Some clients tend to forget about the site soon after making their initial purchase. You need to make sure that you harness them before they decide to check out some other e-commerce sites.

3. E-commerce standalone software

An excellent example to use is the multi-vendor e-commerce software. It allows you to create an online marketplace for your commodities. Using this eCommerce recommendation system, independent vendors are privileged to sell their commodities through one storefront. Some of the advantages you stand to gain by using this software include: 

4. Customer lifetime value model

Do you know what it takes to make a customer valuable? On the other hand, do you even know what customer lifetime value model means? Well, this is a prediction of the net profit that is associated with the entire future relationship made with a returning client. In nonprofessional’s language, it is calculating how much profit a returning client brings to the table during his or her lifetime. Nonetheless, why is this important to calculate? 

It is imperative to know these figures because it helps the company learn which customers need more concentration in terms of marketing and advertising. It also helps in the customer retention model.

5. Fraud detection

With the emergence of new technological systems every day, the world is slowly becoming susceptible to fraudulent attacks and activities. There are millions of transactions carried out every day. With this massive number in play, the e-commerce field is no exception nor is it immune to fraud. Therefore, you need to ensure that all customer details and transactions, plus your details, are safe from fraudsters. Using data science project and techniques, you can easily detect fraud and deal with it accordingly. Some of the projects you can use include data mining, clustering, and classification to find anomalies and matching algorithms for risk estimation and evasion of false alarms.

6. Improved customer service

The traditional customer service that you know barely is enough to cater to clientele needs. You need to employ data science techniques such as Natural Language Processing. This data science technique helps to retrieve customer reviews. Afterward, it determines why a negative review is present and how to deal with it. The data scientists will then try to evaluate the sentimental meanings of the words. This subsequently helps the e-commerce site maximize user satisfaction.

7. Price optimization

Data science is making price optimization easier every day. Most of the e-commerce sites value their items using unique formulas. When it comes down to pricing, there are different factors to consider. Some of the most vital factors include market segmentation, cost analysis, and competitor analysis. Pricing is a crucial factor that you should never ignore, especially when you want to improve profits, market share, and overall revenues.

8. Seamless online payments

Most of the e-commerce sites available integrate mobile platforms. For this reason, the payment method needs to be smooth, safe, and secure for clients. There should not be any loopholes affecting the safety of clientele funds. Big data analytics helps to make sure that this is possible.

9. Quality assurance

Due to the presence of warranties in shopping, e-commerce sites can validate the authenticity of products. This is through the analysis of warranty claims that check the quality and reliability of the items in question. This will help manufacturers identify any quality problems early enough and deal with them to avoid any future altercations and damage to the business. 

Text mining encompassed with data mining helps to identify such flaws and deal with them as they occur. Accrued data provides insights and recommendations.

10. Inventory management

It is baseless to run an e-commerce site if you cannot manage inventory correctly. You will lose customers quickly when you fail to get them what they need and when they need it. They will comfortably move to the next provider if you fail to be accurate in your delivery. To design the right inventory tactics, you will need to use predictive analytics and learning algorithms.

Editor notice: By the way, CS-Cart recently got an update with an advanced inventory management system, check it out.


In summary, these are the ten best data science projects you can use to improve your e-commerce business. E-commerce is the future of shopping; you need to grow your business to outweigh the rising competition.

— by Kurt Walker

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