diff --git a/Makefile b/Makefile
index fe9b2557f..f9981c48c 100644
--- a/Makefile
+++ b/Makefile
@@ -22,6 +22,9 @@ debug:
 asan:
 	python3 setup.py build $(VVAL) --debug --sanitize
 
+profile:
+	python3 setup.py build $(VVAL) --profile
+
 logo/kitty.iconset/icon_256x256.png: logo/kitty.svg logo/make.py
 	logo/make.py
 
diff --git a/README.asciidoc b/README.asciidoc
index 35783cbe5..f7f2f7b82 100644
--- a/README.asciidoc
+++ b/README.asciidoc
@@ -350,8 +350,8 @@ and ``input_delay``. These control the artificial delays introduced into the
 render loop to reduce CPU usage. See the link:kitty/kitty.conf[config file] for details.
 
 You can generate detailed per-function performance data using
-link:https://github.com/gperftools/gperftools[gperftools]. Build kitty with the
-`--profile` flag which will create an executable called `kitty-profile`.  Run
+link:https://github.com/gperftools/gperftools[gperftools]. Build kitty with
+`make profile` which will create an executable called `kitty-profile`.  Run
 that and perform the task you want to analyse, for example, scrolling a large
 file with `less`. After you quit, function call statistics will be printed to
 `stdout` and you can use tools like *kcachegrind* for more detailed analysis.