Importance of Data Science in the Retail Industry
Today, the retail industry is on the boom in this consumerism era. Every year, the sales are increasing exponentially and with increased sales and customers, huge amounts of data are created. This is why retail businesses are taking advantage of data science for making their businesses more profitable and customer oriented.
Retail business can collect their data from varied sources like customer transaction information, log files, social media related data, product sensor data etc. All these collected data are then processed and analyzed in a way that it can help the management and staff to take quick and effective actions which can lead to the development of the business and create a valuable experience for the customers.
Data science helps in understanding various trends and also helps in making decisions regarding promotion and marketing so that the products can reach the customers and eventually increase the revenue of the company. Some of the common ways the retail industry is using data science are discussed below.
Understanding consumer behavior
Consumers are the central pillar of a retail business and thus the need to understand them is of the highest importance. Big data is helping the retail industry in collecting and analyzing data related to customers buying pattern, their preferences, which makes them buy more, what are their reactions towards certain product or offers etc. Accumulating all these data is not a problem anymore because of the advent of the internet; one can make use of social media, e-commerce apps, and even stores. All this data is then churned to find out some important answers which can ultimately lead to higher customer acquisition and retention.
Personalize the buying experience
Data science is now using the consumer data and their buying pattern to understand what they like and what their interests are so that their sales and merchandising can be personalized according to the customer. Today, many retail industries are tracking customer behavior in stores and e-commerce platforms, so that marketing teams can increase promotional effectiveness. And increase cross-selling.
Targeted promotions
Marketing teams always try to create target bunches regarding the certain category of products, this is done to reduce unnecessary costs and loss of resources. Using data, one can do the same by gathering customer data and categorizing them into groups according to location, demographics, social media interactions, their likes, dislikes and preferences. All these data are then analyzed to find a deeper explanation about the customers and their purchase choices. For example, one must have experienced seeing advertisements about certain things that they might have searched online or like on social media. This is exactly how the customer conversion is achieved using the power of data science.
Operational analysis
The retail industry is not just about customers, it is also about products which move in supply chains. Controlling and managing these supply chains are of huge importance as they are in control of product life cycles and also the overall cost of the operations. Data science helps in analyzing machine data and sensor-generated data to find information about trends and patterns about the operational cycle, which in turn can help one in making better decisions.
