1. What is the best practice for naming clusters?
There is no perfect way to name a cluster. Affinio provides Cluster Summaries that display the three most nuanced traits to help you quickly differentiate between clusters. You can choose a label from one of these top resonating traits, create a hybrid of them all, or use these suggestions as a reference point for your research. Click the pencil icon beside the cluster in your left menu to find suggestions and name the cluster. See: How to Name a Cluster, FAQ: Auto Cluster Name Recommendations.
2. How are the audience segments (clusters) defined?
Our segmentation algorithm looks at every connection of every member of an audience, then it breaks them into clusters based on their interests and affinities. This method identifies naturally occurring clusters within your audience without bias, discovering clusters you may not have known existed.
3. How do you identify the quality or homogeneity of a cluster?
The best way to determine the quality of a cluster is to look at “Shared Interests” from the “Audience Summary” within the main Overview section. The higher the Relevance Score, the more alike the cluster members are. If you are looking to push content to a cluster, look at the “Interconnectivity,” which is also found in “Audience Summaries.” A higher density score indicates that cluster members are seeing the content shared by multiple people.
4. What does density (i.e. Interconnectivity) measure?
Density represents the number of people in that cluster who follow other members of that cluster. The higher the density percentage, the more likely people in this cluster are to know each other. Density does not scale with size; there tends to be higher density within smaller groups, as people can only be connected to so many users at one time on a network.