diff --git a/R/row_count.R b/R/row_count.R
index d63596472..93f1ebbca 100644
--- a/R/row_count.R
+++ b/R/row_count.R
@@ -5,18 +5,18 @@
 #' `rowSums(x == count, na.rm = TRUE)`, but offers some more options, including
 #' strict comparisons. Comparisons using `==` coerce values to atomic vectors,
 #' thus both `2 == 2` and `"2" == 2` are `TRUE`. In `row_count()`, it is also
-#' possible to make "type safe" comparisons using the `exact` argument, where
-#' `"2" == 2` is not true.
+#' possible to make "type safe" comparisons using the `allow_coercion` argument,
+#' where `"2" == 2` is not true.
 #'
 #' @param data A data frame with at least two columns, where number of specific
 #' values are counted row-wise.
 #' @param count The value for which the row sum should be computed. May be a
 #' numeric value, a character string (for factors or character vectors), `NA` or
 #' `Inf`.
-#' @param exact Logical. If `TRUE`, `count` matches only values of same type
-#' (i.e. when `count = 2`, the value `"2"` is not counted and vice versa).
-#' By default, when `exact = FALSE`, `count = 2` also matches `"2"`. See
-#' 'Examples'.
+#' @param allow_coercion Logical. If `TRUE`, `count` matches only values of same
+#' type (i.e. when `count = 2`, the value `"2"` is not counted and vice versa).
+#' By default, when `allow_coercion = FALSE`, `count = 2` also matches `"2"`.
+#' See 'Examples'.
 #'
 #' @inheritParams extract_column_names
 #' @inheritParams row_means
@@ -45,14 +45,14 @@
 #' # count all 2s and "2"s per row
 #' row_count(dat, count = 2)
 #' # only count 2s, but not "2"s
-#' row_count(dat, count = 2, exact = TRUE)
+#' row_count(dat, count = 2, allow_coercion = TRUE)
 #'
 #' @export
 row_count <- function(data,
                       select = NULL,
                       exclude = NULL,
                       count = NULL,
-                      exact = FALSE,
+                      allow_coercion = FALSE,
                       ignore_case = FALSE,
                       regex = FALSE,
                       verbose = TRUE) {
@@ -90,10 +90,10 @@ row_count <- function(data,
     rowSums(is.na(data))
   } else {
     # comparisons in R using == coerce values into a atomic vector, i.e.
-    # 2 == "2" is TRUE. If `exact = TRUE`, we only want 2 == 2 or "2" == "2".
-    # to achieve this, we simply compute the comparison on numeric or non-numeric
-    # columns only
-    if (isTRUE(exact)) {
+    # 2 == "2" is TRUE. If `allow_coercion = TRUE`, we only want 2 == 2 or
+    # "2" == "2". to achieve this, we simply compute the comparison on numeric
+    # or non-numeric columns only
+    if (isTRUE(allow_coercion)) {
       numeric_columns <- vapply(data, is.numeric, TRUE)
       if (is.numeric(count)) {
         data <- data[numeric_columns]
diff --git a/man/row_count.Rd b/man/row_count.Rd
index c6a2bbdbc..cfcb051f1 100644
--- a/man/row_count.Rd
+++ b/man/row_count.Rd
@@ -9,7 +9,7 @@ row_count(
   select = NULL,
   exclude = NULL,
   count = NULL,
-  exact = FALSE,
+  allow_coercion = FALSE,
   ignore_case = FALSE,
   regex = FALSE,
   verbose = TRUE
@@ -61,10 +61,10 @@ excludes no columns.}
 numeric value, a character string (for factors or character vectors), \code{NA} or
 \code{Inf}.}
 
-\item{exact}{Logical. If \code{TRUE}, \code{count} matches only values of same type
-(i.e. when \code{count = 2}, the value \code{"2"} is not counted and vice versa).
-By default, when \code{exact = FALSE}, \code{count = 2} also matches \code{"2"}. See
-'Examples'.}
+\item{allow_coercion}{Logical. If \code{TRUE}, \code{count} matches only values of same
+type (i.e. when \code{count = 2}, the value \code{"2"} is not counted and vice versa).
+By default, when \code{allow_coercion = FALSE}, \code{count = 2} also matches \code{"2"}.
+See 'Examples'.}
 
 \item{ignore_case}{Logical, if \code{TRUE} and when one of the select-helpers or
 a regular expression is used in \code{select}, ignores lower/upper case in the
@@ -90,8 +90,8 @@ specific value indicated by \code{count}. Hence, it is equivalent to
 \code{rowSums(x == count, na.rm = TRUE)}, but offers some more options, including
 strict comparisons. Comparisons using \code{==} coerce values to atomic vectors,
 thus both \code{2 == 2} and \code{"2" == 2} are \code{TRUE}. In \code{row_count()}, it is also
-possible to make "type safe" comparisons using the \code{exact} argument, where
-\code{"2" == 2} is not true.
+possible to make "type safe" comparisons using the \code{allow_coercion} argument,
+where \code{"2" == 2} is not true.
 }
 \examples{
 dat <- data.frame(
@@ -115,6 +115,6 @@ dat <- data.frame(
 # count all 2s and "2"s per row
 row_count(dat, count = 2)
 # only count 2s, but not "2"s
-row_count(dat, count = 2, exact = TRUE)
+row_count(dat, count = 2, allow_coercion = TRUE)
 
 }
diff --git a/tests/testthat/test-row_count.R b/tests/testthat/test-row_count.R
index 7eea5d6a6..57c7e76ed 100644
--- a/tests/testthat/test-row_count.R
+++ b/tests/testthat/test-row_count.R
@@ -26,7 +26,7 @@ test_that("row_count, errors or messages", {
   expect_error(row_count(iris[-seq_len(nrow(iris)), , drop = FALSE], count = 2), regex = "one row")
 })
 
-test_that("row_count, exact match", {
+test_that("row_count, allow_coercion match", {
   d_mn <- data.frame(
     c1 = c("1", "2", NA, "3"),
     c2 = c(NA, "2", NA, "3"),
@@ -34,7 +34,7 @@ test_that("row_count, exact match", {
     c4 = c(2, 3, 7, Inf),
     stringsAsFactors = FALSE
   )
-  expect_identical(row_count(d_mn, count = 2, exact = FALSE), c(1, 2, 0, 0))
-  expect_identical(row_count(d_mn, count = 2, exact = TRUE), c(1, 0, 0, 0))
-  expect_identical(row_count(d_mn, count = "2", exact = TRUE), c(0, 2, 0, 0))
+  expect_identical(row_count(d_mn, count = 2, allow_coercion = FALSE), c(1, 2, 0, 0))
+  expect_identical(row_count(d_mn, count = 2, allow_coercion = TRUE), c(1, 0, 0, 0))
+  expect_identical(row_count(d_mn, count = "2", allow_coercion = TRUE), c(0, 2, 0, 0))
 })