MediaVest Achieves Poetry In Motion: Develops Method For Paid, Owned, Earned Media (Your Know, POEM)
Publicis’ MediaVest unit has unveiled what it claims is a new, proprietary methodology for measuring the compounding effects of paid, owned and earned media, and has come up with an eloquent way of branding it. Dubbed POEM (paid, owned and earned media), the new system utilizes the kind of powerful regression modeling techniques that are typically utilized in so-called media mix modeling systems, but applied specifically to social media variable.
The trick explains, Yaakov Kimelfeld the agency’s senior vice president-digital research and analytics, was determining how many regressions to apply to which variables in the process.
Kimelfeld says the method could well be called POEMS, because it actually accounts for a fourth variable that some refer to “shared” media – a hybrid that falls somewhere between an advertiser’s owned-content, and consumer’s user-generated content.
The power of POEM, he says, is that it enables MediaVest and its clients to quickly analyze the multiplying effects earned and shared media have on the paid and owned media MediaVest executes, and to factor and adjust campaigns on-the-fly based on the incremental media impressions generated by them.
In fact, he says POEM also enables MediaVest to calculate and recalculate the effective costs of media buys based on the incremental reach achieved from earned and shared media, and to analyze which mixes are most likely to project predictable outcomes.
For example, a brand utilizing POEM identified that a 12% increase in print impressions resulted in 1% increase in Facebook page views. But it also shows how the traditional medium triggered “ripple effects” in social media that ultimately impacted the brand’s owned media, noting that an 18% increase in Facebook page views yielded an 8% increase in visits to the brand’s own site.
Kimelfeld says the method can be used to project future mix outcomes, but also to determine the ROI, or return on investment, of media spending based on the impact of those ripple effects.