Programming Glossary

Average Quarter-Hour Persons (AQH Persons) – The average number of persons listening to a particular station or format for at least five minutes within a 15-minute period. Average Quarter-Hour Rating (AQH Rating or AQH PUR) The Average Quarter-Hour Persons estimate is expressed as a percentage of the population being measured. Cume Persons – The total number of different persons who tune in to a radio station during the course of a daypart for at least five minutes. Cume Rating or Cume PUR The Cume Persons audience expressed as a percentage of all persons estimated to be in the specified demographic group.

Cume Persons x 100 = AQH Rating (%)

Population

 

Format Share – The percentage of those listening to radio in the Metro Area who are listening to a station of a particular radio format.

AQH Persons to a specific format


X 100 = share
AQH Persons to all formats

 

Index – A numerical comparison of one percentage to another, with 100 being the norm. P1-First Preference Listening – Persons who listen to one radio station more than any other are P1 listeners for that station. Time Spent Listening (TSL)An estimate of the amount of time the average listener spent with a station, format (or total radio) during a survey week or for a particular daypart. This estimate, expressed in hours and minutes, is reported for the Metro only.

Quarter Hours in a time period x AQH Persons


= TSL
Cume Audience

 

OES (Optimum Effective Scheduling) is a formula originally developed to help commercial radio stations understand how many times a given commercial had to be played before the average listener (50% of your cume) actually hears it 3x (generally accepted as the number of times someone has to hear something for them to begin to take notice.) Over time, researchers began to understand that what held true for commercials could also be applied to songs, promos, personality names, etc… So, if you have access to your stations’ P6+ Cume Persons and P6+ AQH Persons numbers, you can figure out how many times you have to expose them to something in order for half of your cume to “hear” it. By the way, it doesn’t matter if you use P12+ or W25-54 (or any other demographic subset,) just so far as you’re consistent in choosing both Cume and AQH from the same estimate. You can accurately calculate OES for any demographic cell. Here’s the formula. Divide your Cume Persons estimate by the AQH Persons estimate. This will give you your “turnover ratio.” Then, multiply your turnover ratio by 3.29 to find the number of times you’ll have to play something in order for your average listener (not your Super P1’s or your P4’s) to be exposed to it three times. For example, WXYZ has a cume of 728,400 and an AQH or 22,200, so (728,400 divided by 22,200 = 32.81081. 32.81081 x 3.29 = 107.94756. That means if WXYZ wants someone to hear a given song three times, given their current listening patterns, and average weekly time exposed to our station, they have to play it 108 times before the average listener is exposed to it enough to actually “hear” it. Super P1’s will need fewer spins, but P3’s & P4’s are going to need to be exposed to it a whole lot more to hit three “listens.”