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We took Vrinda Storeโs data on a journey of discovery!
Here's what we found:
๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ถ๐ป๐ด ๐๐ต๐ฒ ๐๐ฟ๐ผ๐๐ป๐ฑ๐๐ผ๐ฟ๐ธ:- ๐ ๐ถ๐๐๐ถ๐ป๐ด ๐ฃ๐ถ๐ฒ๐ฐ๐ฒ๐? ๐ก๐ผ ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ! We addressed any incomplete data points to ensure a complete picture.
๐๐ผ๐๐ฏ๐น๐ฒ ๐ง๐ฟ๐ผ๐๐ฏ๐น๐ฒ? ๐๐น๐ถ๐บ๐ถ๐ป๐ฎ๐๐ฒ๐ฑ! Duplicate data was identified and removed for accurate analysis.
๐๐ผ๐ป๐๐ถ๐๐๐ฒ๐ป๐ฐ๐ ๐ถ๐ ๐๐ฒ๐! We ensured all data followed a consistent format, catching any errors along the way.
๐จ๐ป๐๐ฒ๐ถ๐น๐ถ๐ป๐ด ๐๐ต๐ฒ ๐ฆ๐ฎ๐น๐ฒ๐ ๐ฆ๐๐ผ๐ฟ๐:- ๐ง๐ถ๐บ๐ฒ ๐ง๐ฟ๐ฎ๐๐ฒ๐น๐ฒ๐ฟ'๐ ๐ฉ๐ถ๐ฒ๐: We charted the overall sales journey over time, revealing trends and patterns.
๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐ฃ๐๐น๐๐ฒ: We assessed the current state of each product in the store's inventory.
๐ฅ๐ฒ๐ด๐ถ๐ผ๐ป๐ฎ๐น ๐ฉ๐ฎ๐ฟ๐ถ๐ฎ๐๐ถ๐ผ๐ป๐: We examined how sales differed across various geographical regions.
๐จ๐ป๐ฑ๐ฒ๐ฟ๐๐๐ฎ๐ป๐ฑ๐ถ๐ป๐ด ๐ข๐๐ฟ ๐๐๐๐๐ผ๐บ๐ฒ๐ฟ๐:- ๐๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐๐ต๐ฎ๐บ๐ฝ๐ถ๐ผ๐ป๐: We identified key customers and their impact on overall sales.
๐๐ป๐ผ๐๐ถ๐ป๐ด ๐ฌ๐ผ๐๐ฟ ๐๐๐ฑ๐ถ๐ฒ๐ป๐ฐ๐ฒ: Customers were grouped based on their purchasing behaviour for targeted strategies.
-๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐ฃ๐ผ๐๐ฒ๐ฟ๐ต๐ผ๐๐๐ฒ:- ๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ ๐๐ต๐ฒ๐ฐ๐ธ-๐จ๐ฝ: We evaluated the performance of each product using sales data and customer feedback.
๐๐ฑ๐ฒ๐ป๐๐ถ๐ณ๐๐ถ๐ป๐ด ๐๐ฎ๐ด๐ด๐ฎ๐ฟ๐ฑ๐: Slow-moving or underperforming products were pinpointed for further analysis and potential adjustments.
๐ฃ๐ฎ๐ถ๐ป๐๐ถ๐ป๐ด ๐ฎ ๐๐น๐ฒ๐ฎ๐ฟ ๐ฃ๐ถ๐ฐ๐๐๐ฟ๐ฒ:- ๐๐ป๐๐ถ๐ด๐ต๐๐ ๐๐ผ๐บ๐ฒ ๐๐น๐ถ๐๐ฒ: We crafted clear visualizations like bar charts, pie charts and line charts for impactful communication.
๐๐ผ๐ป๐ฐ๐น๐๐๐ถ๐ผ๐ป ๐๐ผ ๐ถ๐บ๐ฝ๐ฟ๐ผ๐๐ฒ ๐ฉ๐ฟ๐ถ๐ป๐ฑ๐ฎ ๐ฆ๐๐ผ๐ฟ๐ฒโ๐ ๐๐ฎ๐น๐ฒ๐:- Target women customer of age group 30-49 years in states MH, Karnataka and UP with ads/offers/coupons on Amazon, Flipkart and Myntra.
This data analysis empowered Vrinda Store with a roadmap for data-driven decision-making. By optimizing sales strategies, enhancing customer satisfaction and addressing product performance, Vrinda Store is poised for significant business growth.