Enterprise Health
Landon Miller
2022-10-03
#Observations KJ currently has 31 deals that have not been closed. Even though Matt has the most closed lost, he has the second most closed won deals. KJ has the most closed won deals. Jeff and Parker have the least closed loss deals. 0 of the 8 deals with an annual recurring revenue greater than or equal to 1 million dollars have not been won. Jeff’s ratio of deals won to deals lost is 6:1. Thomas currently has the biggest deal at 2.8 million dollars, but it is only in the proposal stage at the moment.
#install.packages("openintro")
#install.packages(tidyverse)
#install.packages("readxl")
library(ggplot2)
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.2.1 ✔ stringr 1.4.1
## ✔ readr 2.1.3 ✔ forcats 0.5.2
## ✔ purrr 0.3.4
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(openintro)## Loading required package: airports
## Loading required package: cherryblossom
## Loading required package: usdatalibrary(readxl)
Hubspot_Data_for_Class_1 <- read_excel("Hubspot_Data_for_Class_1.xlsx")Hubspot_Data_for_Class_1## # A tibble: 334 × 6
## Record_ID Deal_Name Deal_Stage Close_Date Deal_Owner Annua…¹
## <chr> <chr> <chr> <dttm> <chr> <dbl>
## 1 10279704247 MOS Qualify 2023-04-21 16:12:00 Jay 150000
## 2 9794103143 MED Proposal 2023-03-31 15:59:00 Jay 1000000
## 3 9434330372 CORE Gain Sponsorship 2022-12-16 09:22:00 Jay 342500
## 4 9218714222 MON Demo 2022-12-15 11:36:00 Jay 300000
## 5 8667386634 MMT Closed lost 2022-06-03 08:22:00 Jay 22500
## 6 8665924620 NR Closed won 2022-06-30 10:37:00 Jay 24200
## 7 8405622154 ATC Deferred 2023-04-30 10:16:00 Jay 150000
## 8 8376067927 MAG Closed lost 2022-04-21 09:43:00 Jay 30000
## 9 8052578899 CAR Qualify 2023-03-31 11:33:00 Jay NA
## 10 8051015557 IMP Closed lost 2022-05-05 11:27:00 Jay 300000
## # … with 324 more rows, and abbreviated variable name ¹Annual_Recurring_Revggplot(Hubspot_Data_for_Class_1, aes(x = Deal_Owner)) +
geom_bar()
ggplot(Hubspot_Data_for_Class_1, aes(x = Deal_Owner, y = Annual_Recurring_Rev, color = Deal_Stage)) +
geom_point()## Warning: Removed 58 rows containing missing values (geom_point).
##Closed lost and won
Enterprise_Closed <- filter(Hubspot_Data_for_Class_1, Deal_Stage == "Closed lost" | Deal_Stage == "Closed won")
print(Enterprise_Closed)## # A tibble: 235 × 6
## Record_ID Deal_Name Deal_Stage Close_Date Deal_Owner Annual_Recu…¹
## <chr> <chr> <chr> <dttm> <chr> <dbl>
## 1 8667386634 MMT Closed lost 2022-06-03 08:22:00 Jay 22500
## 2 8665924620 NR Closed won 2022-06-30 10:37:00 Jay 24200
## 3 8376067927 MAG Closed lost 2022-04-21 09:43:00 Jay 30000
## 4 8051015557 IMP Closed lost 2022-05-05 11:27:00 Jay 300000
## 5 5281132294 MCC Closed lost 2022-02-01 09:19:00 Jay 100000
## 6 80536468 ADC Closed lost 2021-12-06 16:25:00 Jay 50000
## 7 6290897793 GUSI Closed lost 2022-04-28 08:43:00 Jeff 30000
## 8 5293533834 USSS Closed won 2021-05-31 18:54:00 Jeff NA
## 9 398502314 OHSU Closed won 2020-12-09 16:23:00 Jeff 260300
## 10 301167866 USSS Closed won 2021-04-15 13:13:00 Jeff 185000
## # … with 225 more rows, and abbreviated variable name ¹Annual_Recurring_Revggplot(Enterprise_Closed, aes(x = Deal_Owner, fill = Deal_Stage)) +
geom_bar()
Enterprise_Matt <- filter(Hubspot_Data_for_Class_1, Deal_Owner == "Matt")
print(Enterprise_Matt)## # A tibble: 76 × 6
## Record_ID Deal_Name Deal_Stage Close_Date Deal_Owner Annual_Recu…¹
## <chr> <chr> <chr> <dttm> <chr> <dbl>
## 1 6021505179 AMP Closed lost 2022-04-12 14:15:00 Matt 112100
## 2 6021419871 INV Closed won 2022-08-23 17:41:00 Matt 319000
## 3 5802428222 EH Closed lost 2022-04-12 14:15:00 Matt 108000
## 4 5474458213 THC Closed lost 2022-02-08 16:53:00 Matt 184600
## 5 5440361098 PU Closed won 2022-07-14 12:17:00 Matt 118600
## 6 5073434773 UTG Closed lost 2021-08-25 08:57:00 Matt 40000
## 7 5051861619 PCH Closed lost 2022-02-07 11:37:00 Matt 41700
## 8 5051843664 CH Closed lost 2021-08-25 08:57:00 Matt 108000
## 9 5051833358 MH Closed lost 2021-08-25 09:03:00 Matt 220000
## 10 5051717456 AOH Closed lost 2021-08-24 13:22:00 Matt 274000
## # … with 66 more rows, and abbreviated variable name ¹Annual_Recurring_Revggplot(Enterprise_Matt, aes(x = Deal_Owner, fill = Deal_Stage)) +
geom_bar()
Enterprise_other <- filter(Hubspot_Data_for_Class_1, Deal_Stage == "Deferred" | Deal_Stage == "Contract" | Deal_Stage == "Demo" | Deal_Stage == "Gain Sponsorship" | Deal_Stage == "Proposal" | Deal_Stage == "Qualify", Deal_Owner == "KJ")
print(Enterprise_other)## # A tibble: 31 × 6
## Record_ID Deal_Name Deal_Stage Close_Date Deal_Owner Annua…¹
## <chr> <chr> <chr> <dttm> <chr> <dbl>
## 1 10263616090 POL Qualify 2023-06-30 09:23:00 KJ 100000
## 2 10184892819 AGC Qualify 2022-12-31 12:10:00 KJ 25000
## 3 10117760550 MC Qualify 2023-06-30 14:23:00 KJ 100000
## 4 9944126474 IN Qualify 2023-03-31 11:56:00 KJ NA
## 5 9872064110 MB Qualify 2023-03-31 14:04:00 KJ NA
## 6 9494292544 CEN Demo 2023-03-31 10:24:00 KJ 110000
## 7 9413663363 ALM Proposal 2023-03-31 16:09:00 KJ 110400
## 8 8938605686 ALJ Gain Sponsorship 2022-09-30 13:30:00 KJ 14400
## 9 8738242958 COG Gain Sponsorship 2022-12-31 15:00:00 KJ 100000
## 10 8579937362 SW Demo 2023-12-31 12:34:00 KJ 100000
## # … with 21 more rows, and abbreviated variable name ¹Annual_Recurring_RevEnterprise_KJwon <- filter(Hubspot_Data_for_Class_1, Deal_Stage == "Closed won", Deal_Owner == "KJ")
print(Enterprise_KJwon)## # A tibble: 20 × 6
## Record_ID Deal_Name Deal_Stage Close_Date Deal_Owner Annual_Recur…¹
## <chr> <chr> <chr> <dttm> <chr> <dbl>
## 1 7610485823 ALA Closed won 2022-07-13 08:47:00 KJ 21600
## 2 6911097101 ALC Closed won 2022-04-20 16:05:00 KJ 130500
## 3 5429811876 JPMG Closed won 2021-06-22 14:48:00 KJ 352000
## 4 5191267867 ALB Closed won 2021-11-16 12:51:00 KJ 138100
## 5 5141602361 COR1 Closed won 2021-11-16 17:06:00 KJ 239000
## 6 2888538524 VERT Closed won 2021-12-15 15:36:00 KJ 100900
## 7 2836973689 HOUS Closed won 2020-10-29 12:02:00 KJ 48600
## 8 2657857468 HCAF Closed won 2021-06-21 10:59:00 KJ 245538
## 9 1427742616 BC Closed won 2021-09-30 11:07:00 KJ 292050
## 10 912128362 NNL Closed won 2021-09-01 17:38:00 KJ 151500
## 11 747816218 CARG Closed won 2020-02-05 12:00:00 KJ 390200
## 12 727600043 MPC Closed won 2019-12-12 09:38:00 KJ 235000
## 13 436810784 UPC Closed won 2021-09-21 07:32:00 KJ 275000
## 14 307640671 JPMC Closed won 2019-06-26 09:28:00 KJ 790000
## 15 255389036 HM Closed won 2019-06-26 17:51:00 KJ 161500
## 16 253655997 OHS Closed won 2020-06-26 15:00:00 KJ 542500
## 17 193577165 CA Closed won 2018-10-16 10:47:00 KJ 250000
## 18 150336627 WFBH Closed won 2018-04-05 08:21:00 KJ 198460
## 19 105694162 P66 Closed won 2018-11-07 12:20:00 KJ 258180
## 20 70499375 CPC Closed won 2019-01-04 12:11:00 KJ 155711
## # … with abbreviated variable name ¹Annual_Recurring_RevEnterprise_Won <- filter(Hubspot_Data_for_Class_1, Deal_Stage == "Closed won")
print(Enterprise_Won)## # A tibble: 53 × 6
## Record_ID Deal_Name Deal_Stage Close_Date Deal_Owner Annual_Recur…¹
## <chr> <chr> <chr> <dttm> <chr> <dbl>
## 1 8665924620 NR Closed won 2022-06-30 10:37:00 Jay 24200
## 2 5293533834 USSS Closed won 2021-05-31 18:54:00 Jeff NA
## 3 398502314 OHSU Closed won 2020-12-09 16:23:00 Jeff 260300
## 4 301167866 USSS Closed won 2021-04-15 13:13:00 Jeff 185000
## 5 268205194 AMG Closed won 2021-04-08 07:43:00 Jeff 190000
## 6 61675160 BU Closed won 2021-03-30 16:19:00 Jeff 60000
## 7 61674890 HNDOE Closed won 2018-04-02 00:00:00 Jeff 401920
## 8 7610485823 ALA Closed won 2022-07-13 08:47:00 KJ 21600
## 9 6911097101 ALC Closed won 2022-04-20 16:05:00 KJ 130500
## 10 5429811876 JPMG Closed won 2021-06-22 14:48:00 KJ 352000
## # … with 43 more rows, and abbreviated variable name ¹Annual_Recurring_Revggplot(Enterprise_Won, aes(x = Deal_Owner)) +
geom_bar()