It is indeed true that in today’s world, utilizing data properly has become more important than ever. Companies, no matter how big or small they are, are now trusting data to get an insight on how well they are performing, as well as to arrive upon big business decisions.
When it comes to the retail and eCommerce industry, data scientists and analysts are even more so relevant. From predicting the profit, loss, and rate of purchases of the organization, to even manipulating potential consumers into purchasing the product through behavior tracking, having a proper data science strategy has become an integral part of every enterprise. Most of the giant retail brands make use of data analysis to design customer profiles through which they learn about their sore points and hence market the suitable products, which further pushes the consumer to finalize the purchase.
1. Examples of How Data Science Has Helped Ecommerce Companies Gain Business Growth –
When it comes to the arsenal of a retailer, their recommendation engine plays the most important part. Retailers rely on these engines to influence a customer to purchase the product. Giving recommendations often help retailers to give a boost to their sales as well as to dictate the ongoing trends. If this sounds familiar to you, it is because eCommerce giants such as Amazon and even Netflix works based upon this tool.
Did you know that a recent survey has shown that up to 75 percent of Netflix users watch movies or shows based upon the recommendations given to them by Netflix? It is more than probable that when Netflix suggests a particular movie or show to you, you are going to end up watching it.
On a similar note, up to 35 percent of the total yearly revenue that Amazon earns is generated from its recommendation engine that recommends products to the buyers. Amazon provides you product recommendations based upon your browsing and purchase history, and at times even provide exciting discounts to lure you. It works since most of the time the human brain cannot resist buying a specific product that they have been wanting to buy, especially if there is a big discount on it.
- Data Analysis And Data-based Marketing In Ecommerce –
Machine Learning Algorithms –
This entire process of recommending products to consumers works based upon a huge amount of data science talent consisting of filtering as well as analysis put on by machine learning algorithms. They usually keep track of the online behavior of the consumers and further analyze the pattern to come up with appropriate suggestions that the consumer most likely is to find useful or matching their interests.
Market Basket Analysis –
One of the most popular and traditional data analysis tools, it works based upon a concept. Basically, if a consumer has already purchased a certain group of items, they are most likely to purchase another set of similar products. For instance, if you went to a restaurant and only bought appetizers but skipped buying any drinks, you are most likely to buy from the main course. When it comes to the retail industry, consumers mainly make purchases from their impulse, and market basket analysis works by making predictions based on the customer’s purchasing behavior.
3. How Data Science Has Helped Consumers To Choose Better Product On Ecommerce Portals
Price Optimization –
Selling products at just the right prices is an important aspect not only for the customer but for the retailer as well. The price consists of the amount it was required to create the product and the retailer’s personal profits, but the retailer also has to keep in mind the competitor’s prices and whether the customer base will be able to pay the price or not.
All of these factors are analyzed and calculated by the machine learning algorithms which take into account many factors such as the competitor pricing, customer’s attitude when it comes to buying, location, and hence set the prices optimally in a way that it profits all.
Analyzing Customer Sentiment –
An integral part of the online retail business is gathering customer feedback. And with the help of data science techniques such as machine learning and social media analytics, it has become rather easy for eCommerce companies to perform an analysis on brand and customer sentiments and relations. Data collected from online surveys and reviews, natural language processing, and text analysis are some of the ways through which brands can appropriately analyze customer sentiment.
Detecting Fraud –
In today’s digital world, fraud detection has become essential while making online transactions. Retailers, as well as consumers, can detect all kinds of suspicious behavior with the help of data science techniques. Providing reviews that identify fraud businesses proves to be extremely helpful for the customer before they can finalize the deal. Similarly, for businesses, a few fraud-related red flags include data mining and address mining, where incorrect or false data can be detected related to the address provided.
4. Why Data Science Certifications Are Important To Develop More Skill Set Or Workforce For Ecommerce –
Data science has its own applications in all sectors of retail and industry. Not only does it help businesses to make better decisions that can be based on data, that is also known as data-driven decisions. While job positions for data scientists have already seen a steep rise in the retail industry, it is eminent that it will rise even further in the near future. Standing at this point, having data science certifications are extremely significant for the development in sales of all organizations.
There are millions of eCommerce websites on the internet, and making a business stand out to the base can be difficult. But data science jobs help enterprises to analyze customer behavior as well as come up with ways through which customer service can be enhanced. Data science helps gather information about their strengths as well as about the areas which can be further worked upon, and hence is extremely crucial. We hope that this article was helpful to you!