Difference between revisions of "Three horrible guys Poster"

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In the above figure, we do see buildings that are not in any trade area. Therefore, this uncovered area may have been omitted and should be fulfilled by one of the branches.
 
In the above figure, we do see buildings that are not in any trade area. Therefore, this uncovered area may have been omitted and should be fulfilled by one of the branches.
==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>1. Missing Area Analysis</font></div>==
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==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>2. Store Sales Analysis</font></div>==
 
<div style="font-family:Helvetica;font-size:16px">
 
<div style="font-family:Helvetica;font-size:16px">
 
The yearly store sales of Pizza Hut located in Taiwan range from USD$6,809,445 - $13,863,637, with the branch YT being the lowest, and the branch MA having the highest sales. The median sales is branch SS, with USD$9597893.5
 
The yearly store sales of Pizza Hut located in Taiwan range from USD$6,809,445 - $13,863,637, with the branch YT being the lowest, and the branch MA having the highest sales. The median sales is branch SS, with USD$9597893.5
[[File:q3.png|600px|center]]
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[[File:q6.png|800px|center]]
<center>''Overall Store sales''</center>
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<center>''Thematic map of overall Sales''</center>
 
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From the sales data that we have extracted and populated into the geopackage layer, we can then plot these data on the map for each store. It has been split into 5 classes of Quantile (Equal Count). Below is an illustration of the classes and histogram:
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Based on the following thematic map, we can see that the top performers are branches YW,MA,CA and the branches WT,CR,YT are the worst performers. Our recommendation in this case would be to look at the factors surrounding the top performers and apply said factors to the worst performers in order to boost their sales.
[[File:q4.png|600px|center]]
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[[File:q8.png|800px|center]]
<center>''Symbology settings for overall sales''</center>
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<center>''Thematic map showing areas above/below median sales''</center>
 
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The map above reveals an interesting pattern, where the northern stores perform better than southern stores. Our suggestion would be to look at location based factors, such as type of buildings (residential/office) and see whether they vary between areas. It is also possible to look at connectivity with regards to road types, and see if accessibility is a problem for some stores.

Revision as of 19:20, 22 November 2019

3hg.png

Back to Project Home

 

PROPOSAL

 

DATA TRANSFORMATION

 

POSTER

 

WEB MAPS

 

REPORT


Click on link for Higher Res poster: https://smu-my.sharepoint.com/:i:/g/personal/eugene_choy_2016_sis_smu_edu_sg/ESn9eyBbwCtCtTUcK5fCqEcBODCufdBIHlu4kIejcdV1zw?e=aynLKD
G1 G1 lowerRes Poster.jpg



1. Missing Area Analysis

As we observe the generated trade areas, it seems there are some areas which are not covered by any of the branches. Hence, we decided to analyse these areas.

Q1.png
Missing area 1


In the above figure, the uncovered area is 大安森林公园 which is a park. As it is not common to order a pizza to a park, being uncovered is to be expected.

Q2.png
Missing area 2


In the above figure, we do see buildings that are not in any trade area. Therefore, this uncovered area may have been omitted and should be fulfilled by one of the branches.

2. Store Sales Analysis

The yearly store sales of Pizza Hut located in Taiwan range from USD$6,809,445 - $13,863,637, with the branch YT being the lowest, and the branch MA having the highest sales. The median sales is branch SS, with USD$9597893.5

Q6.png
Thematic map of overall Sales


Based on the following thematic map, we can see that the top performers are branches YW,MA,CA and the branches WT,CR,YT are the worst performers. Our recommendation in this case would be to look at the factors surrounding the top performers and apply said factors to the worst performers in order to boost their sales.

Q8.png
Thematic map showing areas above/below median sales


The map above reveals an interesting pattern, where the northern stores perform better than southern stores. Our suggestion would be to look at location based factors, such as type of buildings (residential/office) and see whether they vary between areas. It is also possible to look at connectivity with regards to road types, and see if accessibility is a problem for some stores.