In Streaming Insights, you will find analytics, reporting and audience measurements for your stations distributed through SoundStack.
In this article we are going to cover:
The Streaming Insights dashboard has four tabs: Overview, Trends, Sessions and Tracks. You can easily switch between these tabs by clicking on one of the tabs near the top-left of the screen. We’ll cover the Overview tab first, followed by a walkthrough of the Trends, Sessions and Tracks tabs.
Insights - Overview
The Overview section allows you to breakdown and display visualizations of your station statistics using maps, graphs and charts.
Note: The time zone used for all reports can be changed by clicking on the user's profile at the top-right corner of any screen.
Today filter will be automatically selected along with all the stations, but you can also select a specific station.
Additionally, we provide you with one more filter named Dayparts. You can select it for more in-depth reports. As such, you could run a query for certain times of the day across multiple days. An example of this is wanting to analyze only your morning listener traffic across Monday through Friday but to exclude all data before 4 AM and after 11 AM. Using dayparts can generate fine-tuned reports.
As you set the filters, you’ll observe that the Overview page updates to reflect the filtered analytics, including the next section that presents a high-level summary of your statistics by the total number of active sessions for selected stations (1), number of session starts that accessed the selected stations (2), total listening hours (3), the sessions that didn't remain connected for at least 1 minute (4) and the average time spent listening to your stations (5).
Below the summary information, you will find a line graph with data about the number of listeners over time, based on the range selected. The time dimension is distributed on the horizontal axis, while the vertical axis reports the values of unique listeners. The graph below shows what a 7 day filter might look like.
If the filter range selected is lower than three days, the granularity of the horizontal axis changes to hours. This graph shows what a 2 day filter might look like, with the number of listeners per hour represented.
Another alternative besides choosing from a predefined date range can be Real-time statistics. Then, you can narrow your analytics results by starting typing the name of the station.
The next section presents a high-level summary of your statistics by the total number of active sessions for selected stations (1), number of session starts that accessed the selected stations (2), and the total number of your stations (3).
On this page, you will see a geographic map of the IP address locations of the users currently listening to your stream. We provide the ability to drill down to the city level. Of course, these are not the exact physical locations of individual listeners.
Because of the various ways that users on the internet can be assigned IP addresses, the accuracy of this data varies. Determining a listener's country of origin is 99% accurate, but nailing down a specific city from an IP address is between 50% and 80% accurate.
The last section of the Overview page presents more detailed statistics through four pie graphs which further breakdown statistics according to the filters you originally set at the top. These graphs show the total sessions by different dimensions: by station (1), by country (2), by platform (3), and by device (4).
There is a “See all” link at the top-right of each pie graph which will redirect you to the Sessions tab.
Insights - Trends
With this feature, you can compare streaming data over time to determine which stations are performing well and which ones need more attention.
Yesterday will automatically be selected as the default Period filter (1), along with all the stations, but you can also select a specific station using the Stations filter (3). Similar to the Overview tab, the Dayparts filter (2) is available, and if needed, you can change the time zone by clicking on the user's profile at the top-right corner of the screen. The Trending Downward filter (4) lets you hone in on the metrics that are trending downward from the last period, the same period last year, or both.
The statistics will be displayed across three distinct columns: This period (1), Last period (2) and Same period last year (3).
- (1) This period - displays the data for the period selected in the filter.
- (2) Last period - displays the data for the last period, i.e. period-over-period. For example, selecting the Last Month's period will show you month-over-month.
- (3) Same period last year - displays the data for the same period last year, i.e. year-over-year.
The metrics shown here include TLH, Active Sessions, Session Starts, Bounce Rate, ATSL, Unique Users, and Session Peak. For additional details on these metrics, scroll to the bottom of this article.
Insights - Sessions
In the Sessions tab, we provide you with one more filter to help you to explore the session details of your station(s) as well as the ability to export these details in a CSV file.
The default dimension used for filtering on the Sessions page is “By station”. This can easily be changed to “By country”, "By platform" and "By device" using the drop-down menu on the right.
If you select a different filter than Real-time, we provide you with one additional feature named Time grouping. As such, you could filter analytics "Hourly", "Daily", "Weekly", or "Monthly".
Once you’ve set a filter, the results can be ordered by ascending or descending using the default table view.
Clicking on a specific country name will result in a breakdown of that country’s regions.
If Device dimension is selected, you can drill down to platform by clicking on a device name.
You can easily switch to the bar graph view in order to see the same results in a different format.
If you would like to download your results, this option is available by clicking on the “Export to CSV'' button. This will download a CSV file with your data which can be imported into another tool of your choice.
Note: Filters will be automatically added by the system to the name of the CSV file.
Insights - Tracks
The Tracks section allows you to break down your Total Listening Hours (TLH) statistics by artist.
Today and By artist filters will be pre-selected for your convenience. While the By artist filter can not be changed, you have the flexibility to switch to another time frame if desired.
If you want to save your results, just click the "Export to CSV" button to download them.
Metrics and terms
TLH | Total Listening Hours - Is computed by summing the duration of all sessions that were active (at least 1 minute) during the selected date range |
SS | Session Starts - Number of sessions started within the specified timeframe. Only sessions above one second are counted as a Session Start. We filter out any sessions that are shorter than 1 second. |
AS | Active sessions - Number of sessions that reach 60 seconds or greater within the specified timeframe. Sessions shorter than 1 minute are only counted as Session Starts. |
% | Percentage out of total TLH - Percentage of TLH for each result shown from the total TLH of all the results in the report. |
| SP | Session Peak - The maximum number of active sessions reached at the same time for a given station. |
| ATSL | Average Time Spent Listening - Is computed by averaging the duration of all active sessions during the selected date range |
| Bounce rate | Percentage of sessions which have been connected for less than 1 minute. In other words, the number of listeners who left after initially tuning in. |
| UU | Unique users - shows the number of unique Active Sessions. This is defined by the number of different IP addresses and User Agents that connected to a station within the specified timeframe. |
Note: Total Listening Hours (TLH) and Aggregate Tuning Hours (ATH) are the same metric.
This concludes our introductory tutorial on using Streaming Insights.
If you have any further questions or concerns please do not hesitate to contact our Support Team through the ticket submission form or by emailing us at [email protected].