nps_calc: Tidy Calculation of Net Promoter Score

In marketr: Tidy Calculation of Marketing Metrics Plus Quick Analysis

Description

Simplifies the calculation of Net Promoter Score (NPS) from raw survey data within the tidyverse framework.

Usage

nps_calc(survey_data, ...)

Arguments

survey_data	Raw survey data. Needs to be one row per survey with the nps question in a numeric column called nps_question
...	Optional columns by which to group the nps calculation. There is no limit to the number of grouping variables chosen. Too many will likely result in nps calculations that are too fragmented / based on very small survey counts.

Details

Net Promoter Score was originally developed by Fred Reichheld and now is owned by Bain Company and Satmetrix Systems. According to Wikipedia it "is a management tool that can be used to gauge the loyalty of a firm's customer relationships."

Value

Data frame with nps and survey count for each combination of the grouping variables

Examples

nps_question <- sample(10, 100, replace = TRUE)
nps_date <- rep(seq.Date(from = as.Date("2019-01-01"), to = as.Date("2019-01-10"), by = "day"), 10)
nps_group <- rep(c("a", "b", "c", "d"), 25)
df <- data.frame(nps_question, nps_date, nps_group)
nps_calc(df, nps_group)

Example output

# A tibble: 4 x 3
  nps_group   nps survey_count
  <chr>     <dbl>        <dbl>
1 a          -12            25
2 b          -40            25
3 c          -28.           25
4 d          -32            25

marketr documentation built on Dec. 18, 2020, 9:07 a.m.