We are all pretty familiar with the results of a search engine query. You enter keywords into bing, google or yahoo or some other search engine and get back results. In this example, I entered techstars and the following results displayed:

Page after page listing all of the potential matches; it’s like an inventory list and what may be important is tucked onto page 8.  A social media semantic search works differently and in CI:Insight represented differently.  CI:Insight gives you a tw0-tiered view of social media conversations:

• a high-level contextual view of topics – a landscape of conversation grouped by themes
• the ability to delve into specific posts – if you want to read that blog post from bosoxbomber you can

Conducting a social media semantic search reveals the context and themes of social media conversations over a specified length of time related to the key terms you have entered. CI:Insight’s semantic filter includes customer conversations on Facebook, twitter, message boards, blog and news sites.

For example, entering techstars into CI:Insight provides this contextual visual representation of your search.

A landscape of conversations is displayed as groupings called themes. As you scan this conversation mapping,  you are actually grocking the output of several hundred conversations, over a user-defined period of time, and from a variety of different authors within a single informational pane.

The size and placement of groupings indicate the volume of activity around a particular theme; top-left reveals outlier conversations. Highlighting a theme displays the number of included conversations and key words associated with those messages. Clicking the theme displays the messages, which comprise a specific grouping.

Semantic searching is a more efficient and enlightening method of identifying customer conversations and voice of customer than a traditional search query.