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##     group_rows
##                      Product Quantity PriceEach            DateTime       Date
## 1       USB-C Charging Cable        2     11.95 2019-04-19 08:46:00 2019-04-19
## 2 Bose SoundSport Headphones        1     99.99 2019-04-07 22:30:00 2019-04-07
## 3               Google Phone        1       600 2019-04-12 14:38:00 2019-04-12
## 4           Wired Headphones        1     11.99 2019-04-12 14:38:00 2019-04-12
## 5           Wired Headphones        1     11.99 2019-04-30 09:27:00 2019-04-30
## 6       USB-C Charging Cable        1     11.95 2019-04-29 13:03:00 2019-04-29
##     ZIP State          City
## 1 75001    TX        Dallas
## 2 02215    MA        Boston
## 3 90001    CA   Los Angeles
## 4 90001    CA   Los Angeles
## 5 90001    CA   Los Angeles
## 6 94016    CA San Francisco
df
Name Class Values
Product character
Quantity character
PriceEach character
DateTime POSIXct Time: 2019-01-01 03:07:00 to 2020-01-01 05:13:00
Date Date Time: 2019-01-01 to 2020-01-01
ZIP character
State character
City character 
##  [1] "USB-C Charging Cable"       "Bose SoundSport Headphones"
##  [3] "Google Phone"               "Wired Headphones"          
##  [5] "Macbook Pro Laptop"         "Lightning Charging Cable"  
##  [7] "27in 4K Gaming Monitor"     "AA Batteries (4-pack)"     
##  [9] "Apple Airpods Headphones"   "AAA Batteries (4-pack)"    
## [11] "iPhone"                     "Flatscreen TV"             
## [13] "27in FHD Monitor"           "20in Monitor"              
## [15] "LG Dryer"                   "ThinkPad Laptop"           
## [17] "Vareebadd Phone"            "LG Washing Machine"        
## [19] "34in Ultrawide Monitor"

The audience for this report are the managers for the technology products division. I will be providing recommendations for how to increase revenues.

This first visualization shows the overall sales of products throughout the course of the year. With this data, we can choose when to push more budget into advertising of our tech products.

Now that we have a general idea of sales in different months, we can look at popularity of these products and which contribute the most to overall sales. We will look at only the top 8 preforming tech products to keep the graph clean. The sales are based off revenue rather than quantity sold.

With this graph, we can see the highest to lowest preforming zip codes.

Now, we will focus on the top three ZIP codes to see what times of the year they are not spending as much. By looking at the top spending ZIP codes, we know that they have higher disposable income to spend on electronics. With this information, we can look to approve more budget to marketing or other efforts to increase spending in the slower time periods such as the tail end of winter and summer months.

Lastly, we will get more specific into which products the marketing team should try to push/market more during these months in order to maximize revenue.

In this graph, we can see the top 8 preforming products in the top 3 zip codes. With this information, we can advise the marketing team to push the sales of these top preforming products to get them closer to the sales of the Macbook Pro Laptop which is leading the charts by a large margin.