Social media channels with audiences in the millions are increasingly
common. Efforts at segmenting audiences for populations of these sizes
can result in hundreds of audience segments, as the compositions of the
overall audiences tend to be complex. Although understanding audience
segments is important for strategic planning, tactical decision making,
and content creation, it is unrealistic for human decision makers to
effectively utilize hundreds of audience segments in these tasks. In
this research, we present efforts at simplifying the segmentation of
audience populations to increase their practical utility. Using millions
of interactions with hundreds of thousands of viewers with an
organization’s online content collection, we first isolate the maximum
number of audience segments, based on behavioral profiling, and then
demonstrate a computational approach of using non-negative matrix
factorization to reduce this number to 42 segments that are both
impactful and representative segments of the overall population. Initial
results are promising, and we present avenues for future research
leveraging our approach.