The influx of Big Data in eCommerce is one of the most talked about things in the worlds of eCommerce and Big Data. Big Data in eCommerce simplifies and essentially erases the struggles faced by online retailers.
02 June, 2020
5 Big Data eCommerce Tricks To Maximize Your Sales
These big data eCommerce hacks will help your online sales soar. Here's what you need to know to get started.
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Ashish Kumar
Ashish is an author and a data science professional with several years of experience in the field of Advanced Analytics. He has a B.Tech from IIT Madras and is a Young India Fellow, an exclusive 1-year academic program on leadership & liberal arts offered to 215 young bright Indians, who show exceptional intellectual & leadership ability.
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1. Create Personalized Stores: The suggestions that are displayed based on buying behavior and purchase trends over a period of time are what enhance the buying experience. A person looking for a particular product may not necessarily buy it. However, the customer will definitely go through the suggestions and more often than not, the purchase is made from the recommendations or suggestions provided by the website. These suggestions are made available with the help of Big Data and lead to increased sales conversions.
2. Optimize Pricing: When an online retailer is going to price their product, it has to be done based on how competitors are pricing them. Looking at competitor pricing, the cost of goods and logistics, etc., the decision on price is made. Competitor pricing across various competitors, cost of goods, logistics, variable pricing, seasonal pricing, and others is a lot of data to assort before setting the final price. Assorting this data and arriving at a fixed price is what Big Data helps with.
3. Accurate Demand: The problem of dealing with excess inventory is a huge one. Having stock on your shelf which is unsold is a huge liability and takes up space that new products need to occupy. The solution to this is demand forecasting done with Big Data Analytics based on historical data. Demand forecasting is the most key element for an online retailer.
4. Predict Trends: Showing the products that are trending at that particular time is what the people want to see. Predicting trends based on social media mentions, hashtags etc., will tell you the products that are creating a buzz in the market. The solution to this is trend forecasting using Big Data algorithms.
5. Generate More Sales: Cart abandonment is the biggest fear an online retailer has. A customer going to the checkout page and closing the page, leaving the cart abandoned, is a genuine source of concern when it becomes more than the permissible limit. Big Data can help online retailers create a personalized experience for the customers and can reduce cart abandonment. This will in turn increase the sales.