diff --git a/README.md b/README.md
index 2ab0286..cad2095 100644
--- a/README.md
+++ b/README.md
@@ -656,12 +656,9 @@ Product.search("apple", track: {user_id: current_user.id})
 
 [See the docs](https://github.com/ankane/searchjoy) for how to install and use.
 
-Focus on:
+Focus on top searches with a low conversion rate.
 
-- top searches with a low conversion rate
-- top searches with no results
-
-Searchkick can then use the conversion data to learn what users are looking for. If a user searches for “ice cream” and adds Ben & Jerry’s Chunky Monkey to the cart (our conversion metric at Instacart), that item gets a little more weight for similar searches.
+Searchkick can then use the conversion data to learn what users are looking for. If a user searches for “ice cream” and adds Ben & Jerry’s Chunky Monkey to the cart (our conversion metric at Instacart), that item gets a little more weight for similar searches. This can make a huge difference on the quality of your search.
 
 Add conversion data with:
 
@@ -690,8 +687,6 @@ rake searchkick:reindex CLASS=Product
 
 **Note:** For zero downtime deployment, temporarily set `conversions: false` in your search calls until the data is reindexed.
 
-This can make a huge difference on the quality of your search.
-
 For a more performant way to reindex conversion data, check out [performant conversions](#performant-conversions).
 
 ## Personalized Results
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libgit2 0.21.0