diff --git a/docs/programming-guide.md b/docs/programming-guide.md
index 4267b8cae81108adafa03149027b6697f4bb6f62..353730c28f3c72ede91920054179f07eb49ce5f0 100644
--- a/docs/programming-guide.md
+++ b/docs/programming-guide.md
@@ -1345,14 +1345,15 @@ therefore be efficiently supported in parallel. They can be used to implement co
 MapReduce) or sums. Spark natively supports accumulators of numeric types, and programmers
 can add support for new types.
 
-If accumulators are created with a name, they will be
-displayed in Spark's UI. This can be useful for understanding the progress of
-running stages (NOTE: this is not yet supported in Python).
+As a user, you can create named or unnamed accumulators. As seen in the image below, a named accumulator (in this instance `counter`) will display in the web UI for the stage that modifies that accumulator. Spark displays the value for each accumulator modified by a task in the "Tasks" table.
 
 <p style="text-align: center;">
   <img src="img/spark-webui-accumulators.png" title="Accumulators in the Spark UI" alt="Accumulators in the Spark UI" />
 </p>
 
+Tracking accumulators in the UI can be useful for understanding the progress of 
+running stages (NOTE: this is not yet supported in Python).
+
 <div class="codetabs">
 
 <div data-lang="scala"  markdown="1">