如何通过找出与往年的重叠来计算获客率？

Question

我设置了一个日期 CustOrder关于 2008-2013 年客户购买的日期，其中包含以下信息（这只是部分数据）：

CustID  OrderYear  Amount
101102  2008       22429.00
101102  2009       11045.00
101435  2010       10740.77
101435  2011       73669.50
107236  2012       162123.50
101416  2010       8102.00
101416  2011       360.00
101416  2012       36576.00
101416  2013       1960.00
101467  2012       997.00
101604  2010       2971.53
101664  2009       91.94
101664  2011       130.93
.........

有些客户可能每年都连续购买（即101416），或者只是某些年份（即101664）。我想计算出获客率，即当年获得了多少新客户，从比率和数量上看（对于没有持续购买的客户，只考虑第一次购买）。例如，

Year Customer  TotalCustomerNumber NewCustomerRate
2008   5          5                     0%
2009   3          8                     37%
2010   4          12                    33%
2011   2          14                    14%
2012   3          17                    17%
2013   2          19                    10%

有人知道ideas/hints怎么做吗？

感谢任何帮助！

Answer 1

我花了一些时间想出了一个解决方案，这个方法应该可行。看看评论了解详情：

# Setting a seed for reproducibility.
set.seed(10)

# Setting what years we want allowed.
validYears <- 2008:2015

# Generating a "fake" dataset for testing purposes.
custDF <- data.frame(CustID = abs(as.integer(rnorm(250, 50, 50))), OrderYear = 0, Amount = abs(rnorm(250, 100, 1000)))
custDF$OrderYear <- sapply(custDF$OrderYear, function(x) x <- sample(validYears, 1)) # Adding random years for each purchase.

# Initializing a new data frame to store the output values.
newDF <- data.frame(Year = validYears, NewCustomers = 0, RunningNewCustomerTotal = 0, NewCustomerRate = "")
custTotal <- 0 # Initializing a variable to be used in the loop.
firstIt <- 1 # Denotes the first iteration.

for (year in validYears) { # For each uniqueYear in your data set (which I arbitarily defined before making the dataset)

  # Getting the unique IDs of the current year and the unique IDs of all past years.
  currentIDs <- unique(custDF[custDF$OrderYear == year, "CustID"])
  pastIDs <- unique(custDF[custDF$OrderYear < year, "CustID"])

  if (firstIt == 1) { pastIDs <- c(-1) } # Setting a condition for the first iteration.

  newIDs <- currentIDs[!(currentIDs %in% pastIDs)] # Getting all IDs that have not been previously used.
  numNewIDs <- length(newIDs) # Getting the number of new IDs.
  custTotal <- custTotal + numNewIDs # Getting the running total.

  # Adding the new data into the data frame.
  newDF[newDF$Year == year, "NewCustomers"] <- numNewIDs
  newDF[newDF$Year == year, "RunningNewCustomerTotal"] <- custTotal

  # Getting the rate.
  if (firstIt == 1) { 

    NewCustRate <- 0
    firstIt <- 2

  } else { NewCustRate <- (1 - (newDF[newDF$Year == (year - 1), "RunningNewCustomerTotal"] / custTotal)) * 100 }

  # Inputting the new data. Format and round are just getting the decimals down.
  newDF[newDF$Year == year, "NewCustomerRate"] <- paste0(format(round(NewCustRate, 2)), "%")

}

输出：

> newDF
  Year NewCustomers RunningNewCustomerTotal NewCustomerRate
1 2008           32                      32              0%
2 2009           22                      54             41%
3 2010           19                      73             26%
4 2011           14                      87             16%
5 2012            7                      94            7.4%
6 2013            3                      97            3.1%
7 2014            9                     106            8.5%
8 2015            5                     111            4.5%

希望对您有所帮助！

如何通过找出与往年的重叠来计算获客率？

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