Ratings: UP/DOWN. Do You Know WHY?

Because there are numerous factors that cause ratings to rise and fall, too many to list in this post, it's often difficult to put a finger on exactly what causes fluctuations in your ratings.

Without the aide of analytical tools discovering why your numbers fluctuated can be frustrating.

This is not meant to be a substitute for those efforts, but rather a quick check list of numbers that sometimes get ignored when looking at the "bigger" picture.

Look for these numbers to help uncover the question of "Why?".

Audience Composition/Sample Composition: For most markets ratings break down the demos into multiple demographics: Teens, 12+, and 18+, 18-24, 25-34, 35-44, 45-54, and 55-64 for both men and women.

Here, you'll find what percentage of your audience falls within each cell.

How Does This Help You?

You certainly have an idea of whom you where targeting during the book. These numbers show how accurate you where in reaching that demo. If your primary target was Women 25-34 and your audience is comprised of only 5% from that demo, you immediately know you have a problem. Now, look at the sample composition to see if the problem was your station's or was due to a poorly distributed sample either demographically or geographically (or both).

You can also see what station did a better job in that demo. Was it reach or TSL? Compare both the Audience Composition in Cume and AQH to help you draw a conclusion.

Daypart Trends: By looking at the Cume Rating/Persons and the AQH Share/Persons trends, you can quickly see where you were most affected.

Be sure to keep a record of what, if any, changes occurred in any daypart during a book that could have affected your outcome (i.e. If you had a new afternoon show this book and AQH went down).

Look at how well each daypart converted the available Cume to AQH. Your marketing may be bringing them in, but is your PM Drive show keeping them?

You may also narrow down the reason for a trend to a show element by looking at the Hour-By-Hour shares. Maybe your "All Request Lunch Hour" is (or isn't) the reason for your mid-day spike. Is your morning show losing or gaining audience from 6:00am - 8:00am? You'll find these answers here. PPM data really shines here, due to its granularity and also demonstrates convincingly that much of what people write down is not what they really do.

Metro Cume Duplication Percent: With which stations do you share the most/least of your audience? Is their audience reciprocating?

This is a great way to monitor your marketing tactics. What can you do to get the attention of your competitor's listeners?

Population Estimates and In-Tab Diaries by County: Make sure you've concentrated your efforts on the hot spots. This is especially important now, since samples will still be based on changes in population estimates that started by in 2000. It will be 18 months before actual 2010 changes start to impact the estimates.

If doing a diary review, be sure to look at your return rate from these counties and compare it to your competitor's.

Look at the zip codes and do the same comparison. Be sure you know where those active radio listeners live. Even better, study the zip codes which contribute more than average time spent listening to you.

Cume Recycling: find out what percentage of your total cume persons listen to any particular daypart. Simply divide the 12+ cume for each daypart by the total metro cume.

How well are you recycling your listeners through other dayparts? Do this for your competitors' stations as well and find the dayparts you can improve upon. You can also break this down by specific demo, as well as AQH persons.

Listening Locations: This is another indicator that is sometimes given little attention. It shows what percentage of your audience listens "At Home", "In car", and "Other". You'll get a feel for your listeners' morning, in-office, and drive time listening habits.

While looking at the big picture and searching for the generic answer in your latest book, don't take for granted these often overlooked calculations.

They can help point out some of the finer, more intricate reasons WHY your station performed the way it did.

Correct the problems you uncover, and next book you and you'll be asking, "why did we do so well this book?" Even better, you'll KNOW.