* Update sales copy

docs/source/index.rst

@@ -9,13 +9,21 @@ spaCy NLP Tokenizer and Lexicon
 spaCy is a library for industrial strength NLP in Python and Cython.  Its core
 values are efficiency, accuracy and minimalism.  
 
-* Efficiency: spaCy is 
+* Efficiency: spaCy is TODOx faster than the Stanford tools, and TODOx faster
+  than NLTK.  You won't find faster NLP tools. Using spaCy will save you
+  thousands in server costs, and will force you to make fewer compromises.
+
+* Accuracy:  All spaCy tools are within 0.5% of the current published
+  state-of-the-art, on both news and web text. NLP moves fast, so always check
+  the numbers --- and don't settle for tools that aren't backed by
+  rigorous recent evaluation. An algorithm that was "close enough to state-of-the-art"
+  5 years ago is probably crap by today's standards.
+
+* Minimalism:  This isn't a library that covers 43 known algorithms to do X. You
+  get 1 --- the best one --- with a simple, low-level interface. This keeps the
+  code-base small and concrete.  Our Python APIs use lists and
+  dictionaries, and our C/Cython APIs use arrays and simple structs.
   
-It does not attempt to be comprehensive,
-or to provide lavish syntactic sugar.  This isn't a library that covers 43 known
-algorithms to do X. You get 1 --- the best one --- with a simple, low-level interface. 
-For commercial users, the code is free but the data isn't.  For researchers, both
-are free and always will be.
 
 Comparison
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