trinalysis

Tools for working with transactional data in R

Installation

install.packages("devtools")
devtools::install_github("ben519/trinalysis")

---

Demo

Simulate Random Transactions (with a realistic pattern of customer churn)

library(trinalysis)
set.seed(2357)
transactions<- sample_transactions(
nCusts=100, sdTransactions=10, sdAmount=10, minDate= as.Date("2010-1-1"), maxDate= as.Date("2015-12-31"), products= c("baseball", "basketball", "football", "soccerball")
)
transactions## TransactionID TransactionDate CustomerID Amount Product## 1: 1 2011-11-23 1 6.88 football## 2: 2 2013-11-28 2 1.58 football## 3: 3 2010-12-09 3 16.07 basketball## 4: 4 2011-01-01 3 8.39 soccerball## 5: 5 2013-07-21 3 25.92 soccerball## --- ## 397: 397 2012-10-27 99 11.53 baseball## 398: 398 2015-08-26 99 10.46 basketball## 399: 399 2015-03-15 99 4.25 basketball## 400: 400 2011-01-31 99 12.85 football## 401: 401 2015-01-02 100 16.52 baseball

Extract customers from transactions

custs<- get_customers(transactions, colsCategory="Product")
print(custs, 5)
## CustomerID Transactions TransactionDate.First TransactionDate.Last## 1: 1 1 2011-11-23 2011-11-23## 2: 2 1 2013-11-28 2013-11-28## 3: 3 3 2010-12-09 2013-07-21## 4: 4 4 2010-07-30 2015-10-18## 5: 5 1 2010-08-04 2010-08-04## --- ## 96: 96 1 2015-10-30 2015-10-30## 97: 97 1 2015-03-16 2015-03-16## 98: 98 9 2014-04-14 2015-11-23## 99: 99 7 2010-02-12 2015-08-26## 100: 100 1 2015-01-02 2015-01-02## Product.First## 1: football## 2: football## 3: basketball## 4: football## 5: baseball## --- ## 96: football## 97: football## 98: basketball## 99: soccerball## 100: baseball

Basic Cohort Analyses

make_triangles(
transactions, format="triangular", minLeftOrigin= as.Date("2010-01-01")
)
## $ActiveCustomers## Cohort 0 - 12 12 - 24 24 - 36 36 - 48 48 - 60 60 - 72## 1: 2010-01-01 - 2010-12-31 22 9 10 11 7 10## 2: 2011-01-01 - 2011-12-31 20 11 12 11 9 NA## 3: 2012-01-01 - 2012-12-31 12 7 5 5 NA NA## 4: 2013-01-01 - 2013-12-31 20 11 12 NA NA NA## 5: 2014-01-01 - 2014-12-31 12 8 NA NA NA NA## 6: 2015-01-01 - 2015-12-31 14 NA NA NA NA NA## ## $Transactions## Cohort 0 - 12 12 - 24 24 - 36 36 - 48 48 - 60 60 - 72## 1: 2010-01-01 - 2010-12-31 30 18 21 17 11 16## 2: 2011-01-01 - 2011-12-31 33 22 20 17 18 NA## 3: 2012-01-01 - 2012-12-31 17 17 8 8 NA NA## 4: 2013-01-01 - 2013-12-31 29 21 20 NA NA NA## 5: 2014-01-01 - 2014-12-31 22 16 NA NA NA NA## 6: 2015-01-01 - 2015-12-31 20 NA NA NA NA NA## ## $Transactions.cmltv## Cohort 12 24 36 48 60 72## 1: 2010-01-01 - 2010-12-31 30 48 69 86 97 113## 2: 2011-01-01 - 2011-12-31 33 55 75 92 110 NA## 3: 2012-01-01 - 2012-12-31 17 34 42 50 NA NA## 4: 2013-01-01 - 2013-12-31 29 50 70 NA NA NA## 5: 2014-01-01 - 2014-12-31 22 38 NA NA NA NA## 6: 2015-01-01 - 2015-12-31 20 NA NA NA NA NA## ## $Amount## Cohort 0 - 12 12 - 24 24 - 36 36 - 48 48 - 60 60 - 72## 1: 2010-01-01 - 2010-12-31 314.70 150.91 191.09 140.89 86.94 162.88## 2: 2011-01-01 - 2011-12-31 252.26 186.85 144.38 121.21 150.71 NA## 3: 2012-01-01 - 2012-12-31 132.32 100.71 62.29 78.02 NA NA## 4: 2013-01-01 - 2013-12-31 185.52 150.33 186.78 NA NA NA## 5: 2014-01-01 - 2014-12-31 181.49 139.06 NA NA NA NA## 6: 2015-01-01 - 2015-12-31 179.84 NA NA NA NA NA## ## $Amount.cmltv## Cohort 12 24 36 48 60 72## 1: 2010-01-01 - 2010-12-31 314.70 465.61 656.70 797.59 884.53 1047.41## 2: 2011-01-01 - 2011-12-31 252.26 439.11 583.49 704.70 855.41 NA## 3: 2012-01-01 - 2012-12-31 132.32 233.03 295.32 373.34 NA NA## 4: 2013-01-01 - 2013-12-31 185.52 335.85 522.63 NA NA NA## 5: 2014-01-01 - 2014-12-31 181.49 320.55 NA NA NA NA## 6: 2015-01-01 - 2015-12-31 179.84 NA NA NA NA NA

Contact

If you'd like to contact me regarding bugs, questions, or general consulting, feel free to drop me a line - bgorman519@gmail.com