Difference between revisions of "G1-Group12 Proposal"
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<div style="background: #6495ED; padding: 20px; line-height: 0.3em; text-indent: 0px;letter-spacing:0.01em;font-size:26px"><font color=#000000 face="Arial"><b>Data Collection</b></font></div> | <div style="background: #6495ED; padding: 20px; line-height: 0.3em; text-indent: 0px;letter-spacing:0.01em;font-size:26px"><font color=#000000 face="Arial"><b>Data Collection</b></font></div> | ||
| + | |||
<div style="background: #6495ED; padding: 20px; line-height: 0.3em; text-indent: 0px;letter-spacing:0.01em;font-size:26px"><font color=#000000 face="Arial"><b>Scope Of Work</b></font></div> | <div style="background: #6495ED; padding: 20px; line-height: 0.3em; text-indent: 0px;letter-spacing:0.01em;font-size:26px"><font color=#000000 face="Arial"><b>Scope Of Work</b></font></div> | ||
| + | |||
| + | {| style="text-align: center;center;background: #093066; color: white; width: 30%;" | ||
| + | ! style="width: 35px;" | County | ||
| + | ! style="width: 10px;" | Store Code | ||
| + | |-style="text-align: left; text-indent: 15px;background: white; color: black" | ||
| + | | New Taipei|| | ||
| + | *1. CF | ||
| + | *2. FG | ||
| + | *3. HF | ||
| + | *4. HS | ||
| + | *5. MZ | ||
| + | *6. PC | ||
| + | *7. PJ | ||
| + | *8. PK | ||
| + | *9. PS | ||
| + | *10. PW | ||
| + | *11. SD | ||
| + | *12. TI | ||
| + | *13. YS | ||
| + | |} | ||
| + | |||
| + | |||
<div style="background: #6495ED; padding: 20px; line-height: 0.3em; text-indent: 0px;letter-spacing:0.01em;font-size:26px"><font color=#000000 face="Arial"><b>Project Schedule</b></font></div> | <div style="background: #6495ED; padding: 20px; line-height: 0.3em; text-indent: 0px;letter-spacing:0.01em;font-size:26px"><font color=#000000 face="Arial"><b>Project Schedule</b></font></div> | ||
[[File:Gantt.jpg|999px|center]] | [[File:Gantt.jpg|999px|center]] | ||
Revision as of 14:29, 17 October 2019
Project Motivation
Our aim is to derive insights from profiling trade areas of individual pizza stores, to better understand the characteristics of a trade area that contribute to better sales. We began by digitising and delineating the existing operational trade areas, before analysing the points of interests within these trade areas, and comparing the characteristics of stores with high sales volume to that of stores with low sales volume, to generate insights for our client.
Project Objectives
Add project Objectives here
Data Collection
Scope Of Work
| County | Store Code |
|---|---|
| New Taipei |
|
Project Schedule
