During my 13 years at Arbitron, I can’t tell you how many times I had Program Directors, General Managers and Owners ask me to recommend a fix for whatever ratings problem their station was experiencing. One of the things I love about joining Coleman Insights is that I now have the opportunity to help broadcasters answer their programming strategy questions.
This article from Arbitron discusses the “Hockey Stick” theory, which evaluates the impact different groups of listeners have on your station, and first appeared several years ago when I was a member of Arbitron’s PPM Implementation Team. As we combed through tables and tables of raw PPM data, we aimed to help customers understand what drove the ratings in a PPM world. This is similar to the many free PPM studies Coleman Insights has offered to the industry, which you can access here.
What I think is most important about the kind of analysis Jon Miller writes about is its demonstration of how different segments of a station’s audience can have varying impact on its ratings performance. It’s not all about P1s, nor is it all about maximizing Cume. It’s about finding the right balance to cater to a station’s heavy, medium and light listeners simultaneously. Furthermore, that balance is different for every station and it likely changes over time for an individual station.
Arbitron’s findings described in the article about the role P2s and P3s can have on a station’s ratings performance dovetail with the TSL MaxSM sampling technique Coleman Insights utilizes in many of its FACT Strategic Music TestsSM. For those not familiar with it, TSL Max utilizes an appropriate combination of a station’s heavy, medium and light listeners and then weights their music scores based on the quantity of listening they do to our client station. When these weighted scores are compared to unweighted scores, it provides insights into how to balance the tastes of a station’s core listeners with its broader Cume audience. This is one example of how the advanced research techniques we use provide insights into how to maximize a station’s ratings performance.
Ratings can tell you how your station is doing, but they don’t really tell you why. I look forward to answering some of those “why?” questions now, and utilizing our strategic research tools to provide deeper insight to our clients beyond the data.
