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https://dspace.fsm.ac.in/jspui/handle/123456789/4782
Title: | Digital Optimization using Data Science in Activewear Industry for Skyria |
Authors: | Sinha, Achyut Jain, Shilpi |
Keywords: | Data Science;Digital Optimization;Digital Marketing;025004 |
Issue Date: | 2023 |
Publisher: | FORE School of Management |
Series/Report no.: | ;2023 |
Type: | Technical Report |
Abstract: | The most valuable asset of an internet-based firm is its digital marketing. Whether it's discovering the ideal people through ad campaigns and leveraging data-driven inputs, or making them devoted customers and selling our products in the right place with the correct approach. It is a low-cost approach of targeting the correct consumers with a single click. Organizations employ data science to help them gain more relevant information. Using data science, businesses can now quickly determine where their items are selling at what price range, who their target audience is, and when to sell. This enables businesses to provide the appropriate things to the right consumers at the right time. Understanding data in the sportswear industry allows them to determine which goods are performing well and which are not, which ultimately helps with inventory management. During my internship period, I learnt how to implement data driven methods and other tools to increase the brand visibility and sales. A total of three projects related to increase the brand visibility online, data analysis of the sales records and running social media campaigns were implemented. The main aim was to enhance total sales by analysing historical data while also enhancing the general awareness, brand familiarity, and exposure of the web business. |
Description: | The first author of this project report is student and rest is /are guide /supervisor. |
URI: | http://10.10.10.29:8080/jspui/handle/123456789/4782 |
Appears in Collections: | PGDM_BDA_2021-23 |
Files in This Item:
File | Description | Size | Format | |
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025004_Achyut Sinha - Achyut Sinha.pdf | 27.73 MB | Adobe PDF | ![]() View/Open |
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