Data Science And Its Importance In Industry And Retail

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Deblohit Deb
Mar 03, 2019   •  46 views

Data science is an interdisciplinary field, rather a sequenceof data analysis, which deals with the processes and systems used to extricate knowledge from big data. It uses a lot of theories, simulations and techniques that are connected with various fields like mathematics, statistics, computer science and information technology. The idea of probability, data mining, uncertainty modelling, computer programming, pattern recognition are just a few of its subordinating operations used in data science.


Now over the past few years, Data science has become an integral part of business models in industries, however complex and intricate. Knowing the requirement of customers at a fingertip provides a optimum help to the retailers. The presence of the internet and digital technology provides innovative ways to collect online surveys about the customer’s choice. This rash can be clear by the data, that in 2015 the data science adoption in companies is about 17% whereas it reaches 68% in 2018.


• Challenges where Data Science can help:


1. Market analysis:


The process of market analysis is usually conducted by mining algorithm. It is a traditional tool of data analysis in retail. This analysis depends on the substantial amount of data collected via customers transaction. It also helps to understand the future choices of the customers by gathering the information about likes,dislikes and reviews on a large scale.


2. Price optimization:


The price of any productnot only depends on the costs of the items of the products but also on the wallet of the customer and on the offers of competitors. The data science provides the method of data analysis provides a new tool to handle the right price both for the customer and the retailer.


3. Customers satisfaction analysis:


Customer is connected with the companies in real time so that the retailer can anticipate their needs. Hence, customer satisfaction analysishas become the new tool to the retailer. So they don’t haveto focus on some external group or to wait for customer poll.


4. Information about new stores:


To find out the location of a store is no more a hectic job now. Thanks to the introduction of data science. The retailer just had to add the data about the ZIP code and the local potential market to the online platform and it gets visible directly to the specified customers.


5. Fraud Detection:

To maintain the reputation of your company and be one step ahead of fraudsters ,big data platforms provide regular monitoring to ensure the detection of any whimsical activity.


The above list mentioned only a few, whereas data science also helps to promote the new brands or products, merchandising, maintaining reputation on social media these are all to change the shopping experience as well as the retailer profits in the various sphere.

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