10. A method comprising: querying historical linguistic data sets of exchanges between customers and customer relations representatives over social media; extracting conversations from the historical linguistic data sets between said customers and said customer relations representatives; wherein extracting conversations uses a customer relations representative identifier and extracts all messages sent by said customer relations representative identifier or to said customer relations representative identifier; wherein said messages are grouped by a customer using a customer associated identifier; ordering chronologically a list of all said messages by said customer associated identifier; extracting from the list of all said messages groups of messages, wherein each group of messages is related to an individual subject; aggregating said groups of messages into pseudo synchronous conversations; separating each pseudo synchronous conversation of the pseudo synchronous conversations into one or more segments and associating one or more classes to each of the one or more segments; labeling each segment in said each pseudo synchronous conversation according to conversation analysis; and, computing engagement metrics from said labels of each said segment, wherein said engagement metrics are selected from the group consisting of: resolution rate, properly handled threads rate, customer hang-up, conversion rate, and happy customer rate.
16. The method of claim 10 , further comprising: producing metrics from the segments, wherein said metrics are selected from the group consisting of: message thread length, time thread length, first wait time, average wait time, and arrival rate.