Triton Digital's measurement data and your data strategy

Triton Digital's comprehensive range of audio and advertising products can generate an array of measurement data that you can access and use for a variety of purposes, from simple to complex use cases, and with differing levels of granularity. This article provides a summary of the measurement data types that Triton makes available, along with some example use cases, to show how Triton measurement data can form the backbone of your organization's data and reporting strategy.

Streaming Measurement Data

Triton’s streaming measurement products aggregate streaming data produced by all platforms and sources that host your radio station streams. Once aggregated, Triton provides you with a single source of "truth" for a range of performance metrics concerning both the consumption of streams (started sessions, active sessions, duration of sessions) and the people consuming the streams (count of unique people listening).

Triton provides a wide variety of dimensions and filters to enable you to exclude or include various aspects and granularities in views of your data, including:

• Geographical relating to the location of the listening individuals

• Geographical relating to the location of the stream's station and market

• Device and player (the specific device or device type on which the stream was listened)

• Distributor (the listener-facing app or site from which the stream originated)

• Format (of station)

• Time and date (normalized to local time of the originating station).

These metrics, dimensions, and filters enable a great degree of flexibility and granularity in the views of your streaming data.

Rolled-up streaming metrics for your entire organization can be included in our Streaming Metric Rankers, published monthly, should you choose to opt-in to the program. The Streaming Rankers show the scale of your business among national and international peers and competitors.

Podcast Measurement Data

While Triton recommends that our partners host their Podcasts at Omny Studio, it's important to note that this isn't necessary in order to use the podcast measurement products listed here.

Triton's podcast measurement products provide metrics for the consumption data generated by your podcasts (Downloads, Downloaded Hours, Data transferred) and the people that listen to those podcasts (count of listeners). These core metrics can then be filtered and sliced by several dimension types, such as podcast, episode, geography of listener (by DMA, MSA, country, and market), Apple category (genre), device type and family, and time and date.

The Podcast Metrics Demos+ tool, currently in Beta, provides granular data on the listeners of your podcasts, such as: age, sex, ethnicity, education, marital status, purchasing intent, and media consumption patterns.

Rolled-up Podcast metrics for your entire organization can be included in our Podcast Reports, published monthly. These ranker reports show the scale of your business among national and international peers and competitors.

Another measurement tool for podcasting is Line-Ups, which exposes your download and listener counts for individual podcasts, or groups of podcasts, directly to key advertising agencies. The goal of Line-Ups is to provide those agencies with transparent metrics that they can trust, with the supplied data sent directly and automatically from Triton via the Triton user interface, without involvement from the publisher of the podcasts.

Use Cases and Data Strategy

Measurement of your audio metrics is the foundation that enables you to manage your business effectively and to make informed decisions about what's working and what needs support or extra resources, promotion, or retirement; what's growing and what isn't; what's changing and how to respond. Without a measurement tool that provides trusted and reliable consumption data you are managing your business blind. Triton Digital is the industry leader in the field of audio listening metrics.

Using the data that we provide, you can build out reporting that shows trends in consumption and audience over time for your stations, podcasts, markets, formats, and your entire company. Once identified, items that are performing well can have their methods studied and emulated by those that are underperforming, thus lifting your audience numbers and revenues. Furthermore, trends can be discovered that would have otherwise been overlooked, and changes to your operations can be made in response.

Example

BlorkRadio Inc., is a large (fictional) radio conglomerate with stations spread across the US. They have instigated trend reporting by daypart for all of their stations using data provided by Triton. The data that they use is exported from Triton’s Streaming Metrics user interface, and hence is normalized to the local time zone of each station.

When the pandemic hit, BlorkRadio faced significant uncertainty, not least regarding the effect that home working would have on their audience's consumption habits. However, using Triton-based reporting, they quickly established that with the elimination of commuting time their listeners were now tuning in approximately an hour later in the morning, particularly to their News/Talk stations. This was seen across the country, shown easily in the data due to the normalization of time zones in the Triton data. 

Detecting this change in listener behavior helped BlorkRadio make the decision to shift their News/Talk programming back an hour. As a result, they saw an uptick in Session Starts, improvements in Time Spent Listening and greater audience retention compared to pre-pandemic norms.

The data that Triton provides can also be used as a sales tool. Where your measurement metrics show success, those metrics should be touted in pitch and renewal discussions with prospective and current clients.

Podcast Metrics Demos+ further expands on such sales opportunities: by analyzing the Triton provided demographics and spending-intent data of your podcast audience, you will likely find that you have audience segments that are desirable to advertisers and buyers that are under-represented in your existing advertiser base. This data can form the basis of pitch meetings for such potential customers.

Triton data can also be displayed back to customers as a form of standard advertising campaign reporting or attribution reporting: "Look at our excellent metrics for the stations, dayparts, and podcasts that carried your ads; your spending is reaching a huge and engaged audience!"

The Triton rankers, both for Streaming and Podcasting, are important tools for buyers in evaluating where to spend on audio. Including your company in the rankers helps you place your stations and podcasts within the overall audio advertising spend in a position that is commensurate with your size and scale.

More good news: complex data engineering is not required to apply these use cases to your stations and podcasts. All of the use cases discussed so far can be satisfied by exporting data from the Triton product user interfaces and manipulating that data into reports in Microsoft Excel or Google Sheets. That said, Triton does offer a metrics API and a granular record transfer option for clients who want to visualize and report on their data in a more automated way, or who want to use the opportunities presented by ingesting individual streaming session and podcast download records.

Below are some examples of use cases that are unlocked by opting to receive such granular data from Triton:

• Tracking how your listener base is migrating from live streaming to podcasting/time shifted radio/on-demand radio and tracking your organization’s rate of converting and keeping your audience as they make the transition. This can be done by comparing streaming session and podcast download origination data by IP address over time.

• Integrating with a Data Management Platform of your choice using IP addresses.

• If you are building out advertising products that aim to serve more than just audio ads to the same individual, harvesting the IP addresses of streaming sessions and podcast downloads and targeting those IP addresses with visual banner ads is a possibility.