The marketing dashboard can be broken down into four distinct tab groups: summary tab, details tabs (Trends, Audience Insights, Programmatic Insights, and Engagement Insights), specialized tabs (Playlist Analytics, TikTok Analytics, Top Movers, Track Benchmark, Decision Tree, and Q&A) and technical tabs (Asset Catalogue, Monitoring, and Unmatched Assets)
The general purpose of the summary tab is to present the user with a single-page, high-level overview of all subsets of data presented in the dashboard. The summary page is designed to surface the key metrics to allow you to quickly assess the performance of an artist, release or track across different sets of data (streaming performance, programmatic support, engagement, etc.) and provide an easy way to navigate to a specific tab to explore the data in more detail. Each section of the summary page corresponds to a particular tab of the dashboard, with the "explore details >>" button allowing you to navigate to a more detailed representation of the data quickly.
Performance Overview: top-level streaming stats: breakdown of streams by DSP, delivery type & source type
Geo Analytics: best-performing markets for the period (map + table surfacing the top 10 countries)
Explore details >> navigate to the Trends page.
Engagement Overview: top-level engagement stats (skip, sub30, completion rates), completion profile (percentage of streams played to a threshold: 25, 50, 75, 100% of the track played).
Completion profile data is generated using data from selected DSPs that report stream duration (Spotify & VK), so it does not cover all streams.
Explore details >> navigate to Engagement analytics.
Audience Overview: top-level listeners stats: age & gender profile + listener's snapshots stretching back four months.
Audience overview by listeners is only available at the asset granularity (by track, release, or artists)
When applying other filters (like DSP, source type, or country), switch to audience overview by streams by clicking the button at the top of the section. Audience overview by streams is skewed towards the more engaged parts of the audience (users who generate multiple streams), but it allows for full granularity.
Explore details >> navigate to Audience Insights
Programmatic performance overview: a high-level overview of the programmatic performance, split into three categories:
User & Editorial playlists: stream graph + top placements table
Algorithmic playlists: stream graph + placement selector, top algorithmic placements table
Algorithmic radio and autoplay: top assets on algorithmic autoplay (tracks, artists), autoplay streams by DSP + streams graph. Interacting with the pie charts allows you to quickly filter the radio & autoplay streams graph below.
Explore details >> navigate to Programmatic streams.
The trends tab is designed to help you analyze the streaming performance of any given asset/catalogue in more detail, allowing you to assess streaming performance across different DSPs, source types, and markets. Trends view is a powerful tool providing access to the wealth of first-party streaming data to empower you to assess the impact of past and ongoing marketing campaigns, definitively attribute streaming spikes and anomalies, isolate the most significant growth drivers and assess consumption seasonality.
Overview: A more detailed and upscaled representation of top-level streaming metrics: analyze performance in terms of streams, saves, and listeners by DSP, delivery types, and source types.
Geo-Analytics: Geo Analytics lets you quickly understand the breakdown of streaming consumption by country. To enable a more detailed analysis, three different views are accessible by interacting with buttons at the top of the Geo Analytics section:
By Total Streams: a filled map allowing you to assess the best-performing markets (in terms of # streams for the period) for your selection
By Streaming Growth: a filled map allowing you to find the fastest-growing markets for your selection (in terms of absolute change in streams compared to the previous period, depending on current timeframe selection)
View as a Table: a table-based representation of the local consumption data, allowing you to quickly sort markets by the desired metric.
Week-to-week Performance Breakdown: W2W Performance Breakdown allows you to definitively attribute streaming spikes and anomalies and isolate the most significant growth drivers for your releases. This section ignores the time frame selection and presents the conditionally formatted data on w-2-w change in streams across four key dimensions: by DSP, by asset, by country & by Source type. You can switch between dimensions by interacting with buttons on top of the section.
The rows of the w2w table can be continuously cnrtl / cmd + clicked to reveal the selection on the stream graph below and verify spike attribution.
Daily/Monthly details: this section is designed to help you assess your releases' daily/monthly consumption seasonality.
The programmatic streams tab is designed to analyze the performance on programmatic sources: algorithmic playlists, radio & autoplay, and user-generated and third-party/editorial playlists. The Programmatic Insights tab allows you to break down the contribution of each of the sources of the programmatic streams and assess streaming engagement by playlist or algorithmic placement.
Editorial and User playlists performance: a complete record of streaming performance on user & editorial playlists:
Ribbon chart of top 10 user/editorial placements (by #streams for the period)
A complete table of all user/editorial playlists that generated streams for the period
Complete tables can take a while to load when the selection is not filtered by release or track
Sparklines on the placement table allow to quickly assess the trend for a specific playlist/placement
Algorithmic playlists performance: a complete record of streaming performance on algorithmic playlists & placements:
Ribbon chart of top 10 algorithmic placements (by #streams for the period)
A complete table of all algorithmic playlists that generated streams for the period
Radio and autoplay performance: an overview of performance on radio & autoplay features by DSP, artist & track
The graph of radio & autoplay streams at the bottom of the section can be filtered by interacting with the elements above.
The Audience Insights tab is designed to surface the data describing the audience exposed to the particular asset: an artist, release, or track. Unfortunately, due to the issues regarding the listener data we've described at the beginning of this guide, listener-based audience insights are only available when at the asset granularity, which means that listeners data won't be available when filtering by DSP, source type, or country.
To account for this, audience insights are also available on a stream basis by clicking the corresponding button at the top of the audience page. Audience insights by streams allow you to get to a deeper level of granularity and review the audience profiles for specific DSPs, countries, or source types (e.g., generate the audience profile for algorithmic traffic on Spotify in the UK). Yet, the stream-based audience insights are also less precise, as they skew to more engaged parts of your audience (a single listener can, theoretically, generate a 100 streams and thus be counted 100 times when generating an audience profile)
Audience insights by listeners: assess the audience profile in terms of age and gender for a specific artist, release, or track. The audience profile is generated based on listeners in the last four weeks.
Audience insights by streams: assess the audience profiles in terms of age and gender at a deeper granularity level: filter by country, DSP, source type & more. Based on all streams generated during the selected timeframe.
Benchmark engagements rates for different audience subsets and countries/DSP
On-hover tooltips on the map view will allow you to quickly extract the audience profile in a specific market.
The Engagement Analytics tab is designed to provide a wealth of detail on how listeners on streaming platforms interact with your assets. The engagement tab allows you to review the key engagement metrics (skip, completion, and sub30 rates) and completion profiles across different source types, DSPs, assets, and countries.
Find local markets with the best engagement rates to educate your local marketing campaigns, benchmark the artist's tracks against each other to find the stickiest releases with high potential ROI, and more.
The Playlist Analytics tab is the first specialised tab designed to provide an interface for an in-depth analysis of editorial, third-party, or algorithmic playlists. The views allow you to study movements and performance within the top user or editorial placement and generate audience profiles (in terms of age, gender, location, etc.) for specific playlists. Get in-depth insights on particular editorial placements, find your most engaging playlists and understand how movements on playlists affect the bottom line.
Quite self-explanatory, the TikTok analytics tab deals with all data points from TikTok to enable you to analyze your catalog's performance on the platform. Find artists and tracks picking up steam on TikTok, review the life cycles of TikTok trends & challenges, assess your TikTok audience distribution by market, and report on the performance of TikTok-specific marketing campaigns.
The Top Movers section allows you to quickly assess the movements across your catalog and zero in on the primary growth and decay drivers by artist, asset, DSP & Market.
Compare Tracks (Track Benchmark)
The Track Benchmark tab allows you to overlay two or more tracks from the release date to put the performance data in context and assess the success of new releases. To enable track benchmark, the tracks compared must be released within your retention period (usually 120 days). To benchmark the tracks against each other:
Select tracks to compare through the track slicer at the top right of the page. Optionally, filter by DSP, country, or source type to benchmark subsets of data.
Review the "Your Current Selection:" table, and select the rows you want to compare when tracks have multiple versions (e.g., single version vs. an EP version)
Adjust the comparison range: set the first value to 0.
By following these steps, you should overlay two or more tracks against each other from the release date, allowing you to benchmark the performance of your past and current releases, providing context for the tracks' performance and engagement rates.