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My goal is to transform the data into a dynamic dashboard that franchise owners can use to identify patterns, trends and opportunities for the business. I will achieve this by:
The data for this project was sourced from Maven Analytics for educational purposes. The following columns make up the original dataset:
I conducted an exploratory data analysis and cleaned the date. After cleaning, data transformation was next. New columns created :
Pivot tables were created to summarize the data and expedite chart creation. I mostly use bar, column and line charts to visualize the data.
These were my findings:
Hell’s Kitchen is our best performing branch. Followed closely by Astoria. Lower Manhattan is consistently lagging behind in patronage.
Already made Coffee and Tea are our best sellers which aligns with a cafe.
Loose Tea, Branded and Packaged Chocolate are the worst performing products. People can acquire these items at retail chains while purchasing household items.
High volume days are Friday and Thursday, when the workweek is ending. While weekends are low volume days as more people sleep in and enjoy leisure time, not needing coffee to stay alert.
Mornings are naturally when we get the most patronage.
As we establish our presence in the various locations, we are building a steady client base as shown with the consistent increase in revenue over our first 6 months.
Finally, these were my recommendations: