Ways of accessing Triton measurement data

You can access, view, and manipulate your audio measurement data from Triton Digital in a variety of ways, from quickly accessible views in the Triton user interface to large and automated raw record file transfers that provide the foundation for data science. This article outlines four ways of accessing, viewing, and interacting with your Triton measurement data.

User Interface

All of the Triton Digital measurement products offer a user interface accessed via web browser, within individual profiles secured by passwords. There are two main ways to interact with and view your data within the Triton user interface without exporting the data.

Graph and Dashboard Views

Webcast Metrics "Realtime Listening" shows listener counts for your entire organization, with graphs showing the current and recent history by hour and by daily count of listeners. These views are useful for the detection of issues that might be affecting your listener numbers. Furthermore, our "Charts," "Trends," and "Dashboard" pages, across both our Streaming and Podcasting measurement user interfaces, give filterable and modifiable graphs of many of our measurement metrics across longer periods of time.

Queries

By running queries and viewing the results in our "Explore" and "Audience Details" pages, the top rows of your query results are shown on-screen. In some cases the data displayed on-screen may be sufficient to answer the relevant business question. If not, the data can be exported for further analysis.

Exports

When running queries in the "Explore" and "Audience Details" sections of the user interface, a substantial number of rows of data can be generated. In order to view, filter, sort, and further analyze this data, it can be exported to common spreadsheet formats (XLSX and CSV). The data can then be opened and accessed in spreadsheet programs such as Microsoft Excel or Google Sheets.

Creating reporting templates in Excel or Google Sheets is a way of issuing standardized and frequent reporting on your Triton measurement data for your business. Setting up such report templates to update graphs, tables, and dashboards when new Triton data is added to a template, on weekly or monthly basis, provides you with a simple reporting process that can be managed by the analysts on your team.

Metrics API

We offer a metrics API for clients who prefer to automate the data export process from Triton (for example to collect and store data from Triton in a data warehouse that you own), or for clients who want to automatically populate dashboarding and visualization software (such as Tableau, Looker, Power BI, and Google Data Studio) directly from our API.

The API has similar functionality to the export methodology:

• Within the "Explore" views of Triton's user interface you setup a query, as you would when exporting the data.

• You save the query and access a unique ID that relates specifically to the query that you have created.

• You use that ID to retrieve the query's output via the API, using a variable date range to pull data into your data warehouse or dashboarding and visualization software.

Raw Records

For clients who want the most granular form of measurement data, Triton offers raw record transfer. Note that this data will be of considerable size as each row represents one streaming session. Also note that the records will be raw; not yet filtered and processed by Triton to exclude non-IABv2 compliant sessions. We can provide this data in an automated way via common secure file transfer methods. You can then automate the ingestion of this data into your data warehouse for exploration and reporting.

Why would you opt for this complex and unrefined option? Because the records include useful metadata, such as IP address, that is not available through our user interface or Metrics API. Additionally, you can undertake analysis of sessions that Triton would normally filter out, such as short duration (less than 1 minute) sessions. The raw record option is aimed at organizations that have a robust data infrastructure in place and that want to undertake data science-style studies or develop their own business intelligence applications for the analysis of their measurement data.

Use Case Examples

BlorkRadio Inc., is a large (fictional) radio conglomerate with stations spread across the US. They have built a data warehouse and are now ingesting raw records.

• BlorkRadio can track how their listener base is migrating from live streaming to podcasting/time shifted radio/on-demand radio, and track their rate of converting and retaining their audience as listeners make the transition away from "live" broadcast audio. They do this by comparing streaming session and podcast download data over time by IP address.

• BlorkRadio has chosen to work with a Data Management Platform that Triton does not yet integrate with directly. They use the metadata from the streaming session records in the raw record transfer in order to do this.

• BlorkRadio is building out an advertising product that serves visual banner ads to individuals who hear the audio ad for the same advertiser. In order to do this, they harvest the IP addresses of streaming sessions and podcast downloads and then target those IP addresses with visual banner ads.