Podtrac's Measurement Methodology Compared

The following provides a comparison of Podtrac’s measurement methodology compared to other podcast measures:

• Data points including those from podcatcher software, RSS subscriber, and podcast directories
• Methods including panels and the Portable People Meter

Podtrac's Measurement Metrics Compared to Other Data Points

Podtrac defines a podcast as a recorded file or series of recorded files made available to Internet users through a distribution protocol known as Really Simple Syndication, or RSS. To be measured by Podtrac, a podcast must have an associated RSS feed.

Podcasts are sometimes referred to as podcast series. Individually recorded files, editions, or releases from a podcaster within a single podcast series are generally referred to as podcast episodes.

Podcatcher Software Subscriber Statistics

Podcatcher software records the computer addresses of people who click on the RSS or subscribe button. Some users take advantage of the "subscribe" feature to receive a podcast series, while others use it to sample a single episode. Podcatcher software as a class is still in its early stages, and the usability of these interfaces varies widely. In some cases finding and pressing the subscribe button may be easier than finding and selecting an option to download a single podcast episode. A subsequent decision by the user to cancel the subscription, or to interrupt the download, may not be successfully matched back to the original subscription. While subscriber numbers can provide counts of users who clicked a subscribe button within various podcatcher software, subscriber numbers derived from "subscribe" button-clicks are not as indicative of usage as other data on subscriptions from other media, such as magazines, or email newsletters, for example. Subscription counts tell little about listening behavior, intent, or podcast loyalty. Because podcast "subscriptions" and podcasting itself are both new concepts to consumers as a whole, this measure provides little additional visibility into consumption of podcasting content.

Podcast RSS Subscription Reports

RSS subscription reports provide data to podcasters regarding recurring subscriber access to RSS hosting feeds. This measures access to the feed itself, but does not provide any confirmation that subscribers actually downloaded episodes reported in the RSS feed. While this measurement is more useful than podcatcher software subscriber statistics, it does not address the advertisers' need to know what was actually downloaded.

Podcast Directory User Statistics

Podcast directories offer users the ability to sample a wide variety of podcasts within a single web site or software application. Some directories collect data and provide rankings based on the number of users clicking a subscribe button for a particular podcast series, within the directory. Other directories base their rankings on some measure of users' opinions of the podcast expressed as the number of users voting for a specific podcast. These types of rankings may be more reflective of users' willingness to vote, or the level of promotion a podcast may receive within a given directory, or usability attributes of a directory's particular user interface rather than measuring numbers of listeners to a particular podcast. Additionally, directory-specific rankings such as this represent a subset of podcast usage if the podcast is available on multiple directories. They undercount podcast downloads compared to methods that capture downloads from multiple sources, such as Podtrac.

The Podtrac Method Compared to Other Measurement Methods

There are various methods of measuring the usage of media content. While the details of the specific methods can vary greatly, they can be loosely categorized as content-centric, user-centric, and server-centric. Each has strengths and weaknesses, so determining which type is better depends on how the measurement data is used, and of course how well the measurement methods have been executed.

Podtrac is a content-centric encoding method that captures all downloads of the encoded podcast, even from multiple directories and web sites. Encoded podcasts are measured no matter how many times they are downloaded.

Panels and samples are examples of user-centric measurement methods. They focus on capturing all podcast usage by a user. Because they attempt to measure the average user, they may not capture usage from many light users, or heavy users.

If the user is part of an opt-in panel, several demographic characteristics may be known about the user. In server-centric measurement, all content on a server is measured. Little may be known about the user, and combining data across servers for the same content may be difficult.

Panel Measurement Systems

Panel systems project or estimate usage behaviors of a larger population by measuring a portion of the population, called a sample. The sample is selected based on its similarities to the population as a whole. These systems can provide insights into behavior and usage that can be categorized by specific user characteristics, such as age, gender, and location. Sample-based systems such as this, however, can't collect raw data that equals the scope of the entire population. For podcasts, this means that lightly downloaded podcasts may show no usage in the sample, even though they may have hundreds or thousands of downloads among the millions of Web users. Even for popular podcasts, the actual downloads from the entire population will vary from the projected downloads of the sample. For Advertisers looking for numbers of advertising messages delivered, actual Download Counts is a more meaningful measure than a download estimate projected on a population from a panel.

Portable People Meters

The Arbitron PPM is a small, electronic, portable device that is deployed among a carefully selected sample that is designed to closely reflect the population by age, gender, geography, race and ethnicity. Arbitron recently announced a one-time test of the capability of the Portable People Meter to successfully measure a podcast. While the conditions and details of the test were not released, the PPM provides an innovative service in measuring audible media. There are several limitations of the PPM however when it comes to its usefulness to podcast advertising measurement for the foreseeable future. First, PPMs are costly and there are not enough of them distributed nationally at this time to make this system a viable option to provide advertisers with insights into podcast advertising or listenership. Second, because it is based on a sample, it has the same limitations on collection of usage as described in the paragraph, above. In a climate of ever-increasing fragmentation of media - and thousands of podcasts - it is likely that a sample of PPM users will listen to only a few of the many podcasts, which carry advertising. Therefore, the PPM would not replace other podcast ad delivery measures, especially for podcasts with smaller audience share. And finally, it is unclear what level of effort would be required by podcasters and/or advertisers to encode their podcasts with the audible cues interpreted by the PPM.