Quickly extract the Net Promoter Score (NPS) from a frequencies object of formatted NPS survey questions

Usage

calculate_nps(
  frequencies,
  result = result,
  label = label,
  value = value,
  input_type = c("grouped", "numeric"),
  by_variable = TRUE,
  variable = variable,
  add_group = TRUE,
  get_brand = TRUE,
  prompt = prompt,
  brand_var_name = "brand",
  prompt_rm_pre = ".+\\,.+recommend ",
  prompt_rm_post = " to a .+\\? \\-.+",
  arrange_nps = TRUE,
  append_nps_to_brand = FALSE,
  brand_factor = TRUE
)

Arguments

frequencies: A frequencies table as produced by y2clerk::freqs()
result: DEFAULT = result; The column of NPS question results (proportions) used to calculate the final NPS
label: DEFAULT = label; The column of NPS question labels (responses) used to calculate the final NPS (if `input_type` is set to "grouped", this column MUST include the values "Detractor", "Passive", and "Promoter" and no other values)
value: DEFAULT = value; The column of NPS question values (levels) used to order the final output
input_type: DEFAULT = "grouped"; The input type of the NPS questions. Must be one of either "grouped" or "numeric" corresponding to either pre-formatted (3 groups of "Detractor", "Passive", and "Promoter") or unformatted (scale of 0-10) Qualtrics NPS questions, respectively
by_variable: DEFAULT = TRUE; Boolean, controls whether the function calculates the NPS for each unique specified `variable` (question columns) or for the frequencies as a whole
variable: DEFAULT = variable; The column of unique NPS questions and question names used to calculate the NPS for each (if `by_variable` is set to TRUE)
add_group: DEFAULT = TRUE; Boolean, controls whether the function adds the specified `variable` as a grouping variable to the frequencies object (if it is already grouped) or if the specified `variable` will overwrite any and all previously applied grouping variables
get_brand: DEFAULT = TRUE; Boolean, controls whether the function extracts the "brand" (NPS question subject) from the specified `prompt` column or does not
prompt: DEFAULT = prompt; The column of NPS question prompts (question texts) from which to extract the "brand" (if `get_brand` is set to TRUE)
brand_var_name: DEFAULT = "brand"; The name assigned to the output "brand" column (if `get_brand` is set to TRUE)
prompt_rm_pre: DEFAULT = ".+\,.+recommend "; String pattern in the specified `prompt` column before which everything in the column is scrubbed to obtain the "brand"
prompt_rm_post: DEFAULT = " to a .+\? \-.+"; String pattern in the specified `prompt` column after which everything in the column is scrubbed to obtain the "brand"
arrange_nps: DEFAULT = TRUE; Boolean, whether to arrange the final output by the NPS results, with previous frequencies arrangements/orderings still intact
append_nps_to_brand: DEFAULT = FALSE; Boolean, whether to append the NPS values to the "brand" column, having the format "["brand"] (NPS = [NPS])"
brand_factor: DEFAULT = TRUE; Boolean, whether to convert the "brand" variable (with appended NPS values) to a factor for ease of data visualization (argument specification only applied if `append_nps_to_brand` is set to TRUE)

Value

An updated frequencies object with the new NPS column (and other specified columns) attached, formatted as specified

Examples


set.seed(1)

df <- data.frame(
  brand1_NPS_GROUP = sample(
    c(1:3, NA),
    size = 200,
    replace = TRUE
  ),
  brand2_NPS_GROUP = sample(
    c(1:3, NA),
    size = 200,
    replace = TRUE
  ),
  brand3_NPS_GROUP = sample(
    c(1:3, NA),
    size = 200,
    replace = TRUE
  )
) |>
  labelled::set_value_labels(
    brand1_NPS_GROUP = c(
      'Promoter' = 3,
      'Passive' = 2,
      'Detractor' = 1
    ),
    brand2_NPS_GROUP = c(
      'Promoter' = 3,
      'Passive' = 2,
      'Detractor' = 1
    ),
    brand3_NPS_GROUP = c(
      'Promoter' = 3,
      'Passive' = 2,
      'Detractor' = 1
    )
  ) |>
  labelled::set_variable_labels(
    brand1_NPS_GROUP = "How likely are you to recommend Brand1 to a friend or colleague? - Group",
    brand2_NPS_GROUP = "How likely are you to recommend Brand2 to a friend or colleague? - Group",
    brand3_NPS_GROUP = "How likely are you to recommend Brand3 to a friend or colleague? - Group"
  ) |>
  tidyr::as_tibble()

# Frequencies
frequencies <- df |>
  freqs(
    brand1_NPS_GROUP,
    brand2_NPS_GROUP,
    brand3_NPS_GROUP,
    nas = FALSE,
    prompt = TRUE
  )

# Calculate NPS
calculate_nps(frequencies)
#> # A tibble: 9 × 9
#>   variable         prompt             value label     n stat  result   nps brand
#>   <chr>            <chr>              <chr> <chr> <int> <chr>  <dbl> <dbl> <chr>
#> 1 brand1_NPS_GROUP How likely are yo… 1     Detr…    51 perc…   0.33     0 How …
#> 2 brand1_NPS_GROUP How likely are yo… 2     Pass…    54 perc…   0.35     0 How …
#> 3 brand1_NPS_GROUP How likely are yo… 3     Prom…    51 perc…   0.33     0 How …
#> 4 brand3_NPS_GROUP How likely are yo… 1     Detr…    61 perc…   0.41   -10 How …
#> 5 brand3_NPS_GROUP How likely are yo… 2     Pass…    41 perc…   0.28   -10 How …
#> 6 brand3_NPS_GROUP How likely are yo… 3     Prom…    46 perc…   0.31   -10 How …
#> 7 brand2_NPS_GROUP How likely are yo… 1     Detr…    58 perc…   0.39   -11 How …
#> 8 brand2_NPS_GROUP How likely are yo… 2     Pass…    48 perc…   0.33   -11 How …
#> 9 brand2_NPS_GROUP How likely are yo… 3     Prom…    41 perc…   0.28   -11 How …