14. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the processor to: receive a plurality of documents from at least one user, wherein each document includes unplanned information relating to a customer support issue or sentiment; identify at least one customer support issue or sentiment contained within each document by parsing the plurality of documents; if a confidence level of the identification meets a confidence level threshold of the customer support issue or sentiment, classify the documents satisfying a confidence threshold using a classifier into one of a plurality of classes, each class associated with the identified at least one customer support issue or sentiment; cluster a remainder of the plurality of documents that do not meet the confidence level threshold into a plurality of clustered groups containing similar terms relating to the customer support issue or sentiment using a clustering engine, the clustering engine applying a word analysis; and output a frequency of each identified customer support issue or sentiment within at least one of the plurality of classes and plurality of clustered groups, the frequency based on said classification or said clustering.
14. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the processor to: receive a plurality of documents from at least one user, wherein each document includes unplanned information relating to a customer support issue or sentiment; identify at least one customer support issue or sentiment contained within each document by parsing the plurality of documents; if a confidence level of the identification meets a confidence level threshold of the customer support issue or sentiment, classify the documents satisfying a confidence threshold using a classifier into one of a plurality of classes, each class associated with the identified at least one customer support issue or sentiment; cluster a remainder of the plurality of documents that do not meet the confidence level threshold into a plurality of clustered groups containing similar terms relating to the customer support issue or sentiment using a clustering engine, the clustering engine applying a word analysis; and output a frequency of each identified customer support issue or sentiment within at least one of the plurality of classes and plurality of clustered groups, the frequency based on said classification or said clustering. 20. The computer-readable storage media of claim 14 , wherein the computer-executable instructions further cause the processor to receive by the clustering engine all documents that do not meet the confidence threshold.