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Impact of Data Science in Retail Industry

We are all conscious of the value of data, retail industry generates on a daily basis. Though, this archive of critical data is worthless if it cannot be translated into valuable insights. While all of the data is being generated and collected, it is not being used effectively. This paves way for decision-makers to employ predictive analytics to gain the best value of all the data gathered and make sure better sales outcomes in the near future. Value Base Academy in Bangladesh provides the interactive experience that reinforces learning & it is a lot better than other online learning platforms for many reasons it’s unique like it takes less time, more efficient, instructed by industry-lead experts with more than 12 years of experience. With exclusive access to data lab and analytical platform you are enabled with hands-on experience with real life projects. So, let’s start to perceive the applications of data science in the retail industry & how it is transforming the customer experience.





Recommendation engine It is used to give the recommendations of products that customers might wish to purchase based on customer’s behavior, interests, browsing history and similarity with other likely customers.


Recommendation engines proved to be of great use for the retailers as the tools for customers’ behavior prediction. The retailers tend to use recommendation engines as one of the main leverages on the customers’ opinion. Providing recommendations enables retailers to increase sales and to dictate trends. In Value Base Academy, trainees will determine how to make valuable future-ready decisions that are backed by data using modern recommender systems.



Price optimization

Pricing is undoubtedly the major factor that affects the sales of a product in a store or online. With the widespread use of e-commerce websites and google searches, it is very easy for consumers to do a price comparison for the product they are purchasing, and consumers will almost always go for a lower price product if the same product is available at a lesser cost elsewhere.




Price optimization techniques can help retailers evaluate the potential impact of sales promotions or estimate the right price for each product if they want to sell it in a certain period of time. Current state-of-the-art techniques in price optimization allow retailers to consider factors like competition, weather, season, special events / holidays, macroeconomic variables, operating costs, warehouse information etc. In Value Base trainees will study the process of beginning with data scientists carefully evaluating their data sources, then ensuring that they're accurate and fed into the model correctly for price optimization.

Fraud detection

Fraud detection is a critical issue for retailers determined to prevent losses and preserve customer trust.


Data Science and Machine Learning techniques such as Deep Neural Networks (DNNs) are being used to detect frauds in business transactions. Due to the growth of online transactions, shopping, banking, filing insurance claims, etc fraud has become a major problem for these companies and they are investing a lot of resources to recognize and prevent frauds. Personalized Marketing

Personalized marketing is the implementation of a strategy by which companies deliver individualized content to recipients through data collection, analysis, and the use of automation technology. This is a system used by retailers to integrate personalized recommendations based on their users browsing history, past purchases, likes, and dislikes.

Participants of our 12 week Applied Data Science Program will grasp a powerful suite of marketing analysis tools that can offer invaluable insights into customers behavior.





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