The digital landscape is constantly changing, and with it, there is a need for advanced telemetry tools that can help businesses in making data-driven decisions. Agama, the leading provider in the video observability domain, has introduced the Customer TopN Explorer application, which is a significant upgrade from the traditional TopN devices app.
Agama’s Customer TopN Explorer application is a powerful tool that aims to improve your video delivery service. With its ability to locate devices based on any QoS metric, group membership, and service type, you can quickly and easily identify the areas where your video service needs improvement.
One of the key strengths of the TopN Explorer application is its ability to offer an interactive exploration of devices, premised on the selection of a Quality of Experience (QoE) or QoS parameter. A powerful set of features, such as time range selection, service type, device group, ascending order filtering, max result configuration, and overlay options, ensures a high level of customization.
Best practices for using the Customer TopN Explorer application
- Choose the TopN metric. The TopN metric, also known as the primary Key Performance Indicator (KPI), is the backbone of your data exploration. By design, the TopN metric can be custom-tailored to specific use cases. For example, you can select the TopN metric to identify the devices with the highest numbers of stalls or those devices with the lowest QoE (Quality of Experience) score.
- Add additional KPIs for comparison, sorting, and filtering. This multi-layered analysis is essential to draw the most meaningful insights from your data. For example, you can add up to three ‘extra metrics’ for comparison, sorting, and further filtering. This will help you to identify trends and patterns in your data that would not be visible if you only look at the TopN metric alone.
- Interact with the interactive table to manipulate and visualize data. The interactive table allows easy manipulation of data. By clicking on a column, you can sort data alphabetically and use histograms to get a visual representation of the relative frequency of values within the dataset. Furthermore, the application provides powerful filtering options for expert-level analysis. For example, you can define ‘Metrics filter expressions’ or display timelines for extra metrics to narrow down devices based on unique QoS constraints.
- Mastering KPI-centric exploration. A strategic approach to your main KPI or TopN KPI, as well as your additional KPIs, is essential for getting the most out of your TopN Explorer. This allows you to narrow down your search and identify specific problem areas with good accuracy. For example, you can use multiple KPIs to identify the most problems in customer devices. Or you can use individual filters to narrow down your search to specific devices or groups of devices.
Problem: You’ve received reports of quality degradation on Android devices.
Solution: Use the TopN Explorer to either filter by the operating system (Android) or player (in this case, ExoPlayer).
The next step is adding “Exits while stalled %” as a second KPI with Metrics Criteria set to reflect exits while stalled 1% or higher. This metric is useful because it measures how many viewers leave the stream while the player is stalled and rebuffering.
The third additional KPI could be “Exits before initial play”. Set the metric criteria for any ‘Exits’ before play above 1 to filter results where the viewer left the player before the video started. This tactical use of multiple KPIs and individual filters enables you to narrow your search and pinpoint problem areas with impressive accuracy.
Problem: Suppose our Customer Service Team alerts us to a common issue from the previous evening: frequent stalls occurring on smart TVs. The complaint is specific: “stalling image” on ‘smart TVs’. Examining customer reports and analyzing the data shows that the issue isn’t confined to a particular smart TV brand or model. However, all complaints seem to originate from the A area, thus narrowing our focus to a specific geographical location.
- Configure Agama TopN Explorer
- Filter by service type ‘Adaptive streaming live’.
- Filter by device groups: ‘Devices: tv’ and ‘Geolocation:B/A’.
- Set the time frame from 18:00 to 22:00 (yesterday evening).
- Choose ‘stalls’ as our TopN KPI with the Metrics criteria set to “viewStatesStalled:>1”.
- When filtering on multiple KPIs, set this value to at least 1 to ensure you’re filtering devices that have experienced a minimum of one stall in the selected time frame. Our example only uses one KPI, so we can leave it at 0.
Analyze the results
- Identify the device with the highest occurrences of stalls.
- Don’t overlook the meaning of your devices while focusing on an outlier. The underlying root causes could be significantly different.
- Utilize the device details menu to delve deeper into each instance and gain a comprehensive understanding of the device’s performance dynamics.
Export the data for further analysis
- If the results of the TopN Explorer require an even deeper dive into the data, export your data for a more comprehensive analysis using external tools.
- Increase the maximum results setting to load more data and use the ‘Download report data’ button to secure a .csv file for extensive processing.
Agama’s Customer TopN Explorer is a powerful tool that enables you to take full control of your video performance telemetry data. With a detailed understanding of its functionalities, you can harness the full power of this application to deliver optimal results. Persistent exploration, strategic use of multiple KPIs, and intelligent data filtering are the keys to mastery. With these tactics, you’ll be well-equipped to navigate any challenges and uncover meaningful insights.
Reach out if you have any questions or if you’re ready to bring your telemetry analysis to the next level with more confidence and accuracy.
About Timmy Langeveld
Timmy is a video streaming expert with a product management background and a decade of experience in the telecommunications industry. He is Agama’s Business Development Manager, ensuring that our operators get the most out of Agama’s solutions on a daily basis.