The Components of Radio Ratings: Understanding the Math

The Components of Radio Ratings: Understanding the Math

by Tracy Johnson

The radio Ratings Game is complex. The further one digs, the more complicated it seems. Many factors cause ratings to fluctuate, but understanding the components of radio ratings is fairly simple. It’s the math that causes some broadcasters to pull their hair out.

This article explains the components of radio ratings and how they work together to make up a report.

Components of Radio Ratings

All responses from ratings participants are entered into a complex formula computed from actual listening. Results are then projected across the entire population in a market.

The end product is reported as ratings estimates that become ratings. This is what radio stations and ad agencies use to sell and purchase advertising.

At the core of the process, the relevant statistics follow:

Cumulative Audience

This is commonly referred to as Cume. It’s the total reach of a radio station. Think of it as the total number of listeners who tune into a radio station at least one time in a period. PPM markets usually get both a Weekly Cume and a Daily Cume. In Diary markets, only Weekly Cume is reported.

Radio has always been a medium with a broad reach. Up to 93% of the United States population are reported to listen to the radio in a typical week. This reach (Cume) continues to be a strength.

But more important than Weekly Cume is repeat daily listening. In fact, a valid argument can be made that Daily Cume is the most important ingredient for improved ratings performance.

Quarter Hours (QH)

Quarter hours are reported as a raw number. It’s the total number of listening occasions a radio station receives in a ratings period. It’s the average number of persons listening to a particular station in a 15 minute period.

The more quarter hours a station earns, the higher the Average Quarter Hour (AQH) rating.

In order to be credited with a quarter-hour of listening, a listener must tune in for a minimum amount of time in the same 15 minute period. In The United States, a minimum of 5 minutes listening must take place. In Canada, it’s just two minutes.

However, QH fluctuation is often misleading. Increased quarter hours may or may not result in a higher share of audience.

Overall station share is a percentage, as explained below. Increasing quarter hours is good, of course. But it must be examined in the context of total listening to all stations in a market to be meaningful. In other words, AQH could be increasing, but AQH share may be declining. Or vice-versa.

Time Spent Listening (TSL)

TSL is the total number of quarter hours tuned in by an average listener. This is usually expressed as an average by dividing the total number of quarter hours earned by station Cume.

TSL is affected by many factors, primarily by competition and format. It’s explained in more detail here.

Average Quarter-Hour Share (AQH Share)

AQH Share is mathematically expressed as AQH Persons listening to station divided by the AQH Persons listening to all market radio stations, then multiplied by 100.

This is the percentage, or share, received by an individual station compared to total listening in the market.

AQH Share is the number most often referenced and tracked when evaluating and reporting ratings performance.

First Preference (P1) Listeners

Ratings services report the percentage of each station’s audience that spends the most time with each station. A respondent becomes First Preference or P1 listener to the one station they listen to most.

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To qualify as a P1, a listener must listen at least one-quarter hour more than they do to any other station.

Many times, P1 status is very close. And it can vary from week to week. Sometimes, a respondent is P1 to a station they don’t prefer. Occasionally, they don’t even like that station. The meter records listening to all radio signals it receives, so Incidental Listening can greatly impact P1.

P1s are important to a station’s ratings success. Up to 90% of a station’s total listening comes from as few as 10% of a station’s total listeners.

Ratings Breakouts

Each report includes detailed analysis for individual time periods, as well as demographic, ethnicity and geographic criteria.

The most common broad demographics are:

  • 6-plus
  • 18-34
  • 25-54
  • 35-64

Narrower demographics are also available, including:

  • Teens
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65-plus

Broader reports are also available. The most popular are:

  • 18-49
  • 25-44
  • 18-54
  • 35-plus

Each report can be further sliced by gender and ethnicity. Of course, the further a report is dissected, the smaller the resulting sample size. This can cause greater volatility in ratings results.

Relationship of Time Spent Listening and Cume

As you probably figured out, TSL and Cume are the primary factors in ratings success.

Stations with a large cume typically attract the most people because their programming reaches a broad audience with a mass appeal format.

Think of CHR (Contemporary Hit Radio, or Top 40) for example. These stations tend to be a sort of melting pot for listening, playing current hit songs to give listeners a quick fix of today’s most popular music. They play only songs most popular with the masses.

However, since they refuse to play polarizing songs, the result is a relatively short playlist that is more repetitive than most stations. This causes listeners to tune in often, but for short periods of time.

On the other hand, a format like AC (Adult Contemporary) or Classic Rock specializes in attracting a narrower audience for longer periods of time. Music selections tend to be broader in playing hit songs from a broader era (AC) or deeper into less familiar songs that appeal to a clearly defined listener (Classic Rock).

These stations rely on longer TSL but attract a smaller overall audience.

It’s also an example of two different, but valid, programming philosophies. Stations can program wide and narrow or broad and shallow, as explained here.

Cume Goes Up, TSL Goes Down

All broadcasters want a large audience that listens longer. That’s ideal, of course. But ratings rarely show growth in both Cume and TSL.

With a larger cume, chances are the average Time Spent Listening will be lower.

And vice-versa.

It’s common sense. Just as in growing a business, there are three ways to increase ratings. Find out how here.

When a radio station increases cume, growth will come from new listeners. Each individual in the new audience probably has a favorite station.

Converting a new listener to becoming a P1 is hard! It takes time. So it makes sense that an increase in new listeners will reduce the average TSL of the station’s overall Cume.

The opposite is also true. When Cume is reduced, a station usually doesn’t lose fans. It loses secondary listeners that contribute a fraction of the quarter hours a P1 does. So TSL goes up.

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Smart broadcasters understand this relationship and avoid knee-jerk ratings reactions. I call it the Ratings Freak Out and explain it here.

Daypart? What Is a Daypart?

Ratings are calculated to measure listening in narrow time slots called Dayparts. A Daypart is simply a time slot.

Ratings companies usually divide the day as:

  • Mornings: 6:00 am – 10:00 am
  • Middays: 10:00 am – 3:00 pm
  • Afternoons: 3:00 pm – 7:00 pm
  • Evenings: 7:00 pm – 12:00 midnight
  • Overnights: 12:00 midnight – 6:00 am

Times are quite broad and don’t really reflect how listeners use the radio. For example, morning radio listeners usually have quite different needs for radio listening compared to at-work listening. And most folks start work long before 10:00 am. Yet ratings services define the daypart breakdown for “mornings” as 6:00 am -10:00 am.

For ratings purposes, this is fine as long as programmers understand it’s not a guide for programming their station. Don’t accept the ratings company’s subjective time slots as standard. This will lead to poor programming decisions.

If Dayparts are not specific enough, further breakdowns can be accessed for each hour of the day.

The end result is a detailed report of listening estimates. A broadcaster could isolate a micro-target such as 25 to 34-year-old Asian women listening between 3 and 4 pm.

The rich data should be a tremendous benefit for radio, but sample sizes are not adequate or accurate. The problems are detailed in this article.


These components all work together. Here’s a formula that explains the relationship in practical terms:

Convert Weekly Cume to Daily Cume. Promote to increase Daily Occasions. That combination drives Time Spent Listening.

Now you understand the basic radio ratings components and how they work together. Use it to analyze station performance in each ratings period.

But to get even more value from the wealth of information available, track your ratings performance over a period of time using this ratings tracking tool. Doing so will provide a better perspective for making decisions based on long-term trends.

Download “Ratings Tracking Tool” Ratings-Tracking-Tool.xlsx – Downloaded 90 times – 105 KB


How Radio Ratings Work

The Components of Radio Ratings: Understanding The Math

Why Radio Ratings Sample Sizes Are So Low

Pros and Cons of PPM Ratings

Radio Ratings: Higher Shares Are Driven By Daily Cume.

Why Do Radio Contests Work? Because Ratings Respondents Play

Ratings Case Study: If You Made Decisions Based On This Information, You Would Be Fired…

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