The increasing number of internet users and services has forced many enterprises and businesses to shift online from the physical ground. Millions of people use online platforms for communication, entertainment, shopping, business, marketing, and research. Among these, the E-commerce business disrupted the traditional retail market through various applications and delivery services.
To withstand this strong competition against E-commerce giants, the retail owners have to analyze the data using various techniques to improve sales and profitability. Many stores are now using data science techniques and BI tools to get a step ahead of being resilient in this digital era.
The retail market is just one example of the vast applications of Data Science and Artificial Intelligence. Enterprises in many developing countries, especially India, are using these technologies to understand the complex market structure and increase their presence. You can also be a part of this global trend by learning essential skills with a Data Science Course in India and start your own business or career as a Data Scientist.
Now, let’s see the top 5 trends or Use cases of Business Intelligence and Data Science in the Retail businesses:
Advanced Video Analytics
Retail owners install security cameras to safeguard their stores and catch shoplifters. With Artificial Intelligence(AI), these cameras can be equipped with the capabilities to detect and differentiate between various objects. Also, it can track a person and imitate the owner if he/she is present at the cash counter for a longer time period. Video surveillance also helps retail markets to mitigate the risks and ensure the safety of the store.
With AI video analytics, you can understand a lot about the users watching your advertisements. You can analyze for how long the users are watching your ads, and what catches their attention. After that, you can create strategies and increase your sales. Moreover, AI algorithms allow you to calculate the average height of the visitors and use the data to improve their experience by adjusting the display. In addition,
Using Data Science to offer Personalized Suggestions and Styling
People spend a lot of time choosing the right product they’re looking for, but sometimes they buy stuff which they even want. This is because E-commerce websites like Amazon analyze customer behavior using Data Science models and use the result to suggest relevant products. However, it might confuse customers on what attire is the perfect one for them.
The same problem exists if a customer is going to buy clothes from a retail store. As a store owner, you should know what your customers like to buy and create the perfect styling for them. Using algorithms like apriori, you can analyze the buying patterns and create a combination to increase sales. For example, Stitch Fix uses data science to analyze customer stylings and provide a user-friendly experience.
Due to the changing demands, retailers have to shift their focus from fixed pricing to exciting offers and discounts. Amazon earns millions of dollars by smartly using the data of customer demands and dynamic pricing. Similarly, retailers can use Data Science concepts like predictive analytics to see the market trends, customer demands, and set the pricing in real-time.
Data Science plays an important role in finding out the purchase pattern and predicting the future trends in sales and demand of various products. With better techniques, retailers can identify the products with high prices and set new pricing to increase their sales.
Using Business Intelligence to do Location-based Analysis for Physical Stores
Business Intelligence(BI) allows you to connect the data from different sources and analysis is based on different scenarios. As a retail owner, you can use BI tools to understand the traffic, tourism, and population of the new locations before making any decision. Investors, on the other hand, can weigh the potential of new locations and check the feasibility of the business. Data wrapping also tells us about the customer needs and their buying patterns.
Data Wapping is mainly used to improve the customer experience and make them feel rewarded for their work. Simply put, Data Wrapping is a way of bundling the information and showing how someone’s credit has changed or performance between different time periods. For example, Bookseller can provide an app to the reader that keeps a track of how many pages he reads every day. The app will then show the average time he spent reading. This gives a sense of satisfaction and motivates the customer to buy and read more books.
These were the five trends in Data Science and Business Intelligence for the retail industry. It helps the retailers to keep the customers coming back to your store and thrive in this competitive market. These technologies require a huge amount of data, which retail stores are full of. By using AI and Data Science, retailers can find new opportunities, use insights to make data-driven decisions, and improve customer experience.
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