README.md

In griverorz/nps-package: Utilities for Net Promote Score calculation

The nps package

The nps is a package designed to be used as an example for the "R Development" class at Westat. It presents a number of features that are common in statistical programming in R like S4 classes, C/C++ integration, or unit testing. It is not intended for production use.

Net Promoter Score

The Net Promoter Score (registered trademark of Fred Reichheld, Bain & Company, and Satmetrix) is a widely used measure of customer satisfaction.

The Net Promoter Score is calculated based on responses to a single question:

How likely is it that you would recommend our company/product/service to a friend or colleague?

Respondents can answer in a scale from 0 (Very unlikely) to 10 (Very likely). Respondents who answered with 9 or 10 are called "Promoters" and respondents who answered with a value below 6 are called "Detractors". Values 7 and 8 are labeled "Passives". The NPS is defined as the proportion of Promoters minus the proportion of Detractors.

Although it has gained considerable popularity, it has also attracted controversy.

Usage

The package provides a function nps() that takes a vector of integer values and two sequences that define the group of promoters and detractors. The constructor validates the object by checking simple conditions such a non overlap between the values that define promoters and detractors.

The summary() method produces a frequency table with counts for each category.

x <- nps(sample(0:10, 50, replace=TRUE))
print(x)
summary(x)

The user can change the definition of the promoters and detractors categories by using the top and bottom arguments in the constructor.

x <- nps(sample(1:10, 50, replace=TRUE), bottom=1:6)

The package provides a function to calculate the score and its standard error through two methods: an analytical and bootstrap. The bootstrap solution is implemented through Rcpp and RcppArmadillo.

score(x, boot=TRUE, R=999)

It is also possible to edit the nps object using the top<- and bottom<- setters.

x <- nps(sample(0:10, 50, replace=TRUE), bottom=0:6)
bottom(x) <- 0:5
score(x, boot=TRUE, R=999)

Installation

The package can be installed using the devtools package.

install.packages("devtools")
devtools::install_github("griverorz/nps")

griverorz/nps-package documentation built on May 17, 2019, 8:38 a.m.