Difference between revisions of "Analysis - Final Analysis"
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<div style="background: #fee5d9; padding: 5px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #cb181d solid 32px; font-size: 16px"><font color="#cb181d">Are there observable trends, or changes over time for restaurants and user preferences?</font></div> | <div style="background: #fee5d9; padding: 5px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #cb181d solid 32px; font-size: 16px"><font color="#cb181d">Are there observable trends, or changes over time for restaurants and user preferences?</font></div> | ||
[[Image:smiley.png|600px|thumb|center|Time-Series Analysis]] | [[Image:smiley.png|600px|thumb|center|Time-Series Analysis]] | ||
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| + | The composition of the positive reviews for the Beach Pizza restaurant has decreased from 100% in 2010 to 60% in 2014 as indicated by the green smiley face. This implies that there has been an increase in the level of customer dissatisfaction with regards to the Beach Pizza restaurant in recent years. Hence, the restaurant owner has to examine and rectify these poor performing areas in order to attract more customers which would in turn lead to an increase in the revenue. Likewise, this time series analysis of the composition of the text reviews can be applied to all the other restaurants. In addition, the graph would allow the restaurant owner to compare the composition of the text reviews with its competitors. This would help to explain the difference in the revenue if any. | ||
| + | </div> | ||
Revision as of 00:32, 20 November 2015
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The composition of the positive reviews for the Beach Pizza restaurant has decreased from 100% in 2010 to 60% in 2014 as indicated by the green smiley face. This implies that there has been an increase in the level of customer dissatisfaction with regards to the Beach Pizza restaurant in recent years. Hence, the restaurant owner has to examine and rectify these poor performing areas in order to attract more customers which would in turn lead to an increase in the revenue. Likewise, this time series analysis of the composition of the text reviews can be applied to all the other restaurants. In addition, the graph would allow the restaurant owner to compare the composition of the text reviews with its competitors. This would help to explain the difference in the revenue if any.
