Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/20658
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kumar, U Dinesh | |
dc.contributor.author | Kishore, Kaushal | |
dc.contributor.author | Mane, Srinivas | |
dc.date.accessioned | 2021-11-15T11:00:30Z | - |
dc.date.available | 2021-11-15T11:00:30Z | - |
dc.date.issued | 2016 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/20658 | - |
dc.description.abstract | Forecast sales using store, promotion, and competitor data. Rossmann operates a chain of about 3,000 drug stores in seven countries in the Europe. Rossmann is faced with the task of predicting their daily store sales for up to 6 weeks in advance. Thousands of Rossmann’ s managers predict their store sales depending on the unique circumstances they face. In such scenario, the accuracy of prediction can be highly variable. | |
dc.publisher | Indian Institute of Management Bangalore | |
dc.relation.ispartofseries | PGP_CCS_P16_093 | |
dc.subject | Sales management | |
dc.subject | Pharmaceutical Industry | |
dc.subject | Sales strategy | |
dc.subject | Marketing | |
dc.subject | Rossmann | |
dc.title | Rossmann store sales prediction | |
dc.type | CCS Project Report-PGP | |
dc.pages | 13p. | |
Appears in Collections: | 2016 |
Files in This Item:
File | Size | Format | |
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PGP_CCS_P16_093.pdf | 485.9 kB | Adobe PDF | View/Open Request a copy |
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