1. A method implemented by one or more computing devices, the method comprising: receiving, by the one or more computing devices, customer metadata for an external social platform, wherein the customer metadata includes customer tags used with published content; receiving, by the one or more computing devices, employee metadata for an internal social platform, wherein the employee metadata includes post identifiers and employee tags associated with particular posts; generating, by the one or more computing devices, tag suggestions for a new post on the internal social platform, wherein the tag suggestions are selected from a group of data including the customer tags and the employee tags and wherein the group of data includes an indication of the origin of each of the customer tags and the employee tags as from the internal social platform or the external social platform; receiving, by the one or more computing devices, additional internal metadata for new posts for the internal social platform, wherein the additional internal metadata includes new post identifiers and one or more selected tags associated with the new posts, wherein the selected tags are selected from the tag suggestions; and performing, by the one or more computing devices, data correlation to determine a level of employee focus on customer issues, wherein the data correlation is based on the new post identifiers, the one or more selected tags, and an indication of the selected tags as being selected from a tag suggestion originating from the internal social platform or the external social platform, and wherein the level of employee focus on customer issues is determined by a level of adoption of the customer tags in the new posts for the internal social platform, based on how many customer tags are included in the additional internal metadata.
1. A method implemented by one or more computing devices, the method comprising: receiving, by the one or more computing devices, customer metadata for an external social platform, wherein the customer metadata includes customer tags used with published content; receiving, by the one or more computing devices, employee metadata for an internal social platform, wherein the employee metadata includes post identifiers and employee tags associated with particular posts; generating, by the one or more computing devices, tag suggestions for a new post on the internal social platform, wherein the tag suggestions are selected from a group of data including the customer tags and the employee tags and wherein the group of data includes an indication of the origin of each of the customer tags and the employee tags as from the internal social platform or the external social platform; receiving, by the one or more computing devices, additional internal metadata for new posts for the internal social platform, wherein the additional internal metadata includes new post identifiers and one or more selected tags associated with the new posts, wherein the selected tags are selected from the tag suggestions; and performing, by the one or more computing devices, data correlation to determine a level of employee focus on customer issues, wherein the data correlation is based on the new post identifiers, the one or more selected tags, and an indication of the selected tags as being selected from a tag suggestion originating from the internal social platform or the external social platform, and wherein the level of employee focus on customer issues is determined by a level of adoption of the customer tags in the new posts for the internal social platform, based on how many customer tags are included in the additional internal metadata. 9. The method of claim 1 , wherein performing the data correlation further comprises: determining a proportion of the new posts in the additional internal metadata that has at least one associated customer tag.