Decathlon, the world’s largest sporting goods retailer company, surprised the entire eCommerce industry with its large number of sales when businesses were facing the biggest challenge during the Covid-19 pandemic.
This eCommerce company invested in optimizing its website, mobile app, and online marketing to improve its performance which enabled them to get 4.5 million online orders in 12 months.
And do you know what was the key secret behind their huge sales?
Using data science in eCommerce
When asked to Dr. Florian Bischoff, director of eCommerce at Decathlon, he said “only data can prove whether you are making the right business decision or not. We used the algorithms of data science to understand the customer behavior and create an MVP to test and then accordingly improve our eCommerce strategy.”
Decathlon is not the only company which got succeeded with the power of data science,
L’Oreal, the famous cosmetic company used data scientists to figure out the impact of several cosmetic agents on different skin textures and compositions and then create better products based on the data.
Fruition Sciences, an online web application for wine producers, uses data science algorithms to decide the proper composition of their wine constituents.
Data science is the new gold for modern business people. And in eCommerce, it is doing marvels. Data science in eCommerce enables marketers and business owners to provide better products & services by understanding and capturing the customer’s behavior and integrating the information in marketing strategy and other business decisions.
If you have an eCommerce business and haven’t realized the importance of data science in eCommerce, you are probably missing the invisible gold mine in terms of data.
Today in this article, eSearch Logix will discuss why you should use data science in eCommerce. You will know if you dig a bit deeper, data science can give the secret keys to your eCommerce success.
So let’s know it
What is Data Science?
Data science is the field of study, preparing, analysis, cleansing, aggregating, manipulating, and extracting data to get deep data insights and execute high level data analysis. It is the scientific process of extracting knowledge and insights from unorganized or raw information.
Data science utilizes artificial intelligence (AI) and machine learning (ML) in its core operations. And the one master or operates this called data scientist.
Why Business People are Using Data Science in eCommerce?
Every time when a user clicks on the Internet to buy something, it generates data. And then this information is captured and stored by businesses to analyze users’ online behavior and they accordingly attract them to make a purchase.
Data science here makes it easier for businesses to understand the captured information and use the analysis in further strategy. For example, if a person looking to purchase a new smartphone, he or she will search on Google or other search engines.
In this way, Google knows what users are searching for. Then after purchase, users share their product reviews on social media channels like Facebook, Twitter, Instagram, and Pinterest.
Data science makes it possible to organize all this information at one place to help eCommerce businesses find out what customers want and what factors drive their buying decision.
Today, eCommerce businesses are using data science in different areas to understand consumer behavior and make better marketing strategy. The eCommerce giant, Amazon uses data for providing a better shopping experience to customers.
Data science allows eCommerce businesses to provide personalized product recommendations, make the best of predictive forecasting, analyze the customer online behavior, prevent fraud, and upgrade the web experience.
Now you know how data science is empowering eCommerce businesses, it’s time to dig out the gold mine.
How Using Data Science In Ecommerce Can Bring Success To Your Business?
1. Improve Customer Retention through Better Churn Rates
Retaining customers is extremely important in eCommerce businesses to grow in long term scale. A churn model is a part of customer retention strategy that gives helpful metrics and the ability to identify loyal customers.
Using data science algorithms eCommerce businesses can know the customers who might switch to their competitor’s sites. In this way, the company can take quick action and retain them.
The success of your eCommerce business lies when your churn rate is low. Churn model is the popular data science technique that recognizes the best loyal customers. It calculates the churn rate by using different metrics related to the nature of your business.
2. Give Product Recommendations
A recommendation system plays a significant role in eCommerce website development. It is used to filter choices for a specific user based on their previous online activities. Having a good recommend system allows eCommerce businesses to provide personalized product recommendations to users help them find their favorite products quickly.
There are mainly three types of recommendation techniques in data analytics that are used in the industry:
- Collaborative filtering
- Content-Based Filtering
- Hybrid Recommendation Filtering
Data science here provides the power of eCommerce analytics that helps in improving sales growth. Amazon, Netflix is making the best out of using data science. A report says that 35 percent of Amazon’s revenue is produced due to its recommendation engine.
3. Analyze Customer Sentiment
Behind any customer’s purchase, there is buying intent that motivates them. And gathering customer feedback is a way to analyze the customer sentiment what factors customers mostly look at in a particular product before making a purchase.
By employing data science techniques like Natural Language Processing (NLP), text analysis, and online reviews allow data scientists to understand the sentiments behind the customer’s purchase. eCommerce businesses can further dive deep into customer sentiment analysis to know the key reasons behind a bad review.
4. Analyze Customer Lifetime Value Accurately
Customer Lifetime Value is an estimated or predicated numerical figure that gives the idea of how much a customer can bring value to the company’s revenue during his or her lifetime. This term matters a lot in eCommerce development.
Data science creates a data statistical model of a customer’s buying pattern to make calculated predictions. Through this model, you can easily know the value of CLV of your eCommerce store. If its value lies between 0.2-0.33.
5. Prevent Fraud in Ecommerce
Online frauds are the biggest trouble for eCommerce businesses. Online frauds can take place in many forms like affiliate fraud, customer identity fraud, merchant identity fraud, chargeback fraud, and more. If you fail to detect these frauds it can not only cause loss of revenue but also hamper your online brand reputation.
Data science here helps eCommerce businesses to find out online scams and suspicious orders based on various indicators like different shipping and billing address, large number of orders, multiple modes of payments, international orders, etc. Data science empowers the eCommerce business with a strong Fraud detection system by the following techniques like:
- Data mining
- Time series analysis
- Data clustering and classification
- Matching algorithms
Providing good customers may sound luring but a single online fraud can spoil the brand authority of your eCommerce store. Best eCommerce Development Company in USA reports that online fraud is a billion-dollar business and it is growing every year. Here, data science empowers eCommerce store with a strong Fraud detection system.
6. Understand Customer Behavior and Shopping Patterns
The key to eCommerce success lies in when you know what ultimately drives customer’s buying decisions. If you know consumer behavior, you can create your eCommerce marketing strategy effectively and influence consumers’ buying decisions.
Here data science allows digital marketers to study consumer behavior accurately and assists them to present their products in the best possible way that generates maximum ROI.
To succeed in the eCommerce business, it is essential to analyze consumers’ online shopping patterns, and without data science, it is almost like shooting an aim in the darkness.
Data science techniques clear the path by giving you data-driven figures on consumer online behavior and shopping patterns. It helps you find out the gaps in your eCommerce marketing and recognize the products which are most in demand and outdated.
Conclusion
The secret of eCommerce success is to know what exactly your customers want and how the best way you can provide it to them. And using data science in eCommerce you can do it easily. Data science uses AI & ML based algorithms which make it easier to provide effective data-driven eCommerce solutions.
Because data science involves science so you will need professional guidance and leadership that can help you achieve the best results for your eCommerce business.
eSearch Logix here stands out as the leading eCommerce development agency in India which has certified data scientists, software engineers, web developers and programmers, and professional marketers who together work to give the best solution for your eCommerce store.
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