3 Ways Data Science is Being Used in Ecommerce

data science ecommerce

A data scientist is someone who processes and analyzes large data sets, either structured or unstructured sets. As much as you may not want to admit it (especially if you are a creative person) data is everywhere and people are needed to dissect that data, especially in the field of e-commerce. 

Ecommerce has to deal with numbers and without the e-commerce algorithms, you would have a lot of trouble handling the data.

Without data science, ecommerce revenue would grind to a halt, and here are some of the best ways that data science and ecommerce are working hand in hand together in the field. 

What Exactly Does a Data Scientist Do in Their Career?

Still, before we do that, we need to know what a data scientist does for the field. A data scientist is a professional that examines and interprets a large amount of data. A data scientist needs to be able to combine the expertise of several mathematical roles including mathematician, scientist, statistician and computer professional. That’s a lot of data, because they need to be able to make inferences and also analyze all the trends of the ecommerce market.

If you want to see what a data scientist will do in the ecommerce field, you don’t need to look very far because they have their hands in everything!

1. Price Optimization

The retailers in the ecommerce field at first used a few data points to optimize prices, such as the margin of profits, the cost of sold goods, and the retail price from the manufacturer. However, now the data can be used in various different ways to increase or decrease prices. These prices can include seasonality, demand, and the locations of customers. 

All of this data can become a variable that can be used by merchants whenever they are trying to optimize their prices to bring customers the best deal or to give themselves the most profit.

2. Promotions Of Items Or Sales To Customers

The data can also help bring customers into the fold by looking at their past actions to predict their future results. For example, if a customer only buys from a certain store on Black Friday and keeps doing so every single year, then a storefront can reach out to that customer on or just before Black Friday.

Similarly, if the data shows that a customer only buys whenever an item is on sale at 25% off or more, then the storefront can automatically send emails notifying a customer of a 25% off sale, and increase the likelihood that the customer will make a purchase.

3. Algorithm Recommendations

Every single website uses algorithms to keep customers on their storefront and consuming or buying their content. 

For example, if you watch an action show on Netflix, then Netflix’s algorithm will show you more action shows and films to keep you watching. Websites can look at your search history and purchase history, as well as what you have already consumed to keep recommending things you might like.

Data Science Is Everywhere and It Is Fun To Understand

Once you understand that everything is a numbers game and that data points are used to predict patterns and tell stories, it can make the entire world a lot easier to understand and interact with. 

Every single company and entity you interact with, even small interactions, either give or take data from you, and then uses that data to help get to know you better. 

So if you are looking for a career that is never going to go out of style, try data science!

Cover Photo by rupixen.com on Unsplash

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