Data Model Structure
Because Ad Revenue Insights is a product delivered through Workspaces, your key reporting needs should be satisfied through the boards detailed above. However, as you get more familiar with the tool, you have the option to leverage the data model underlying this reporting.
Most commonly, you will want to inject particular properties or metrics into existing tiles while in full-screen mode in order to provide additional granularity and insights. The documentation below details the Ad Revenue Insights data model so you are able to perform such operations.
Ad Revenue Insights data, like all Piano Analytics data, is classified in three categories:
Events: Events are the primary data points ingested into Piano Analytics. A pageview or an ad impression firing or a conversion are examples of events (an event, by nature, is a data point associated with a timestamp).
Properties: An event can have hundreds of pieces of metadata attached to it (for example, think of all the rich device, referrer, and geography data a pageview contains). Each piece of event metadata is a property.
Metrics: Piano uses the combination of events, properties, other metrics, and computational formulas (division, addition, multiplication, etc) to calculate out-of-the-box metrics. Examples of metrics include conversion rate and CPM.
Ad Revenue Insights is always activated with Activation Insights. Details on the Activation Insights Data Model can be found here.
Events
The following events are critical to Ad Revenue Insights:
Event | Description |
Page.display | Event indicating a page has been displayed on-site or on a mobile/App screen. This event is essential to measure traffic correctly and is the origin of the "Page views" metric and associated properties. |
Ad.impression | Event capturing all ad impressions on a given page, which is the key ad event in order to properly calculate advertising revenue and compute all associated metrics. |
Widget.impression | Event used for Native Advertising Platforms. A widget is an interactive content unit that is integrated into a website or mobile app. This module can contain various ads in articles or videos formats personalized for each user based on interests and behavior. |
Properties
The following properties are implemented as part of the Ad Revenue Insights dataset. Properties should be seen as metadata that provide contextual information on your events.
Property Name | Property Key | Format | Description |
Ad revenue | ad_revenue | DECIMAL | The revenue attributed to a specific event for a given campaign. |
Ad slot code | ad_slot_code | STRING | User-defined ad container identifier. |
Ad slot ID | ad_slot_id | STRING | Unique ad container identifier automatically attributed by the SSP. |
Advertiser name | ad_advertiser_name | STRING | The advertiser shown on the ad. |
Line item ID | ad_line_item_id | STRING | Line item identifier automatically attributed by the SSP (Supply-side platform). Line Items are specific sets of parameters that dictate how an ad campaign will run on a publisher's website. |
Line item name | ad_line_item_name | STRING | User-defined line item label in the SSP (Supply-side platform). |
Line item type | ad_line_item_type | STRING | Line item information defining how inventory will be sold and prioritized for the given campaign. |
Creative ID | ad_creative_id | STRING | Creative identifier automatically attributed by the SSP to the creative. |
Creative name | ad_creative_name | STRING | User-defined creative name. |
Creative size | ad_creative_size | STRING | Dimensions of the creative displayed. |
Creative type | ad_creative_type | STRING | Technical category of the displayed creative (Third-Party, Image, Custom Template...). |
Header bidding | header_bidding | BOOLEAN | Information (yes/no) to know whether an ad impression was sold using header bidding. |
Order name | ad_order_name | STRING | User-defined order label containing high level information about an ad campaign. |
Pricing model | pricing_model | STRING | The unit of measurement of the transaction used for a specific campaign between an advertiser and publisher. |
Target segments | ad_target_segments | ARRAY STRING | Custom Key-value targeting criteria that enabled the ad to be shown to a specific audience. These segments can be created based on various criteria, such as demographic information, user behavior, interests, or contextual targeting. Target segments help advertisers to precisely define and target their desired audience for their advertising campaigns. |
ID Vendors | id_vendors | ARRAY STRING | ID Solutions present during the bid request when an ad was sold programmatically. |
Ad Platform | ad_platform | STRING | Advertising platform used to place ads. |
Ad inventory category | ad_inventory_category | STRING | The ad inventory category (Direct, Programmatic/Indirect, House) based on the type of line item. |
Page title | page_title_html | STRING | HTML title tag of the measured page. |
User ID | user_id | STRING | Identifier of the visitor who has logged on to your site (user). This ID can be numeric or alphanumeric. Information within "visit" scope (only 1 value per visit) |
Pageview ID | pageview_id | STRING | Identifier of page view. Information within the “event” scope (several possible values per visit). |
Content author | content_authors | ARRAY STRING | Person who wrote the article. |
Content publication date | content_publication_date | DATE | Article publication date. |
Content section | content_section | STRING | Section is a collection of pages defined on the publisher structure under the content of the article. |
Tags | tags_array | ARRAY STRING | Freely definable tags for the page, as provided by the publisher. |
Page content type | page_content_type | STRING | Information on the measured page’s content. The main values are “article”, “website”, “video” taken from the HTML “og:type” tag within the page. |
Metrics
Here is a list of metrics included in the current Ad Revenue Insights analyses.
Source | Name | Key | Description | Calculation | Formula |
Ad Revenue Insights | Ad revenue | m_ad_revenue | Revenue generated by on-site ads. | Sum of ad revenue. | m_ad_revenue_cpm + m_ad_revenue_cpd + m_ad_revenue_cpc |
Ad Revenue Insights | Ad impressions | m_ad_impressions | Number of ad impressions. | Count of the number of ad.impression and widget.impression events. | COUNT ad.impression + COUNT widget.impression |
Ad Revenue Insights | Ad impressions / pageview Ids | m_ad_impressions_per_pageviewid | Number of ad impressions per pageview IDs. | Ad impressions / distinct pageview IDs | m_ad_impressions / m_pageview_ids |
Ad Revenue Insights | CPM | m_cpm | Revenue per 1000 ad impressions. Ad revenue / ad impressions * 1000. | Ad revenue / ad impressions * 1000 | m_ad_revenue / (m_ad_impressions + m_widget_impressions) *1000 |
Ad Revenue Insights | RPM | m_rpm | Revenue per 1000 pageview IDs. Ad revenue / distinct pageview IDs * 1000. | Ad revenue / distinct pageview IDs * 1000 | m_ad_revenue / m_pageview_ids *1000 |
Ad Revenue Insights | RPS | m_rps | Revenue per 1000 visits. Ad revenue / visits * 1000. | Ad revenue / visits * 1000 | m_ad_revenue / m_visits *1000 |
Ad Revenue Insights | Ad and new subscription revenue | m_ad_new_subscription_revenue | Revenue from ads and new subscriptions. Ad revenue + Experience turnover. | Ad revenue + new VX turnover | m_ad_revenue + m_experience_turnover |
Ad Revenue Insights | Subscription RPM | m_subscription_rpm | New subscriptions per 1000 pageview IDs. Experience Turnover / distinct pageview IDs * 1000. | New VX turnover / distinct pageview IDs * 1000 | m_experience_turnover / m_pageview_ids *1000 |
Ad Revenue Insights | Articles | m_articles | Number of pages where page content type is “article”. Distinct pages where page_content_type = “article”. | Distinct pages where page_content_type = “article”. | COUNT DISTINCT page WHERE page_content_type = “article”. |
Ad Revenue Insights | Page views / article | m_pageviews_per_article | Number of pageview IDs per article. Distinct pageview IDs / articles. | Distinct pageview IDs / articles | m_pageview_ids / m_articles |
Ad Revenue Insights | Ad revenue / article | m_ad_revenue_per_article | Revenue from ads per article. Ad revenue / articles. | Ad revenue / articles | m_ad_revenue / m_articles |
Ad Revenue Insights | New subscription revenue / article | m_new_subscription_revenue_per_article | Revenue from new subscriptions per article. Experience turnover / articles. | New VX turnover / articles | m_experience_turnover / m_articles |
Ad Revenue Insights | VX payments / article | m_vx_payment_per_article | Visits with VX paid conversion(s) per article. | VX payments / articles | m_vx_payments / m_articles |
Ad Revenue Insights | Widget impressions | m_widget_impressions | Number of Widget impressions. A widget is an interactive content unit that is integrated into a website or mobile app. This module can contain various ads in articles or videos formats personalized for each user based on interests and behavior | Count of the number of widget.impression events. | COUNT widget.impression |
Ad Revenue Insights | Direct sell-through rate | m_direct_sell_through_rate | The direct sell through rate represents of available ad inventory that has been sold to advertisers. | Ad impression for direct ads / Line item impressions | SUM of ad.impression WHERE line_item_type = STANDARD OR SPONSORSHIP OR PREFERED_DEAL DIVIDED BY Line item impression |
Ad Revenue Insights | ARPU | m_rpv | Average Revenue Per Users : standard metric that divides advertising revenue and subscription revenue by the number of visitors multipled by one thousand. | (Ad revenue + New subscription turnover) / Visitors * 1000 | (m_ad_new_subscription_revenue/m_unique_visitors) * 1000 |
Ad Revenue Insights | Ad ARPU | m_ad_rpv | Average Advertising Revenue Per Users : standard metric that divides advertising revenue by the number of visitors multipled by one thousand. | (Ad revenue) / Visitors * 1000 | (m_ad_revenue/m_unique_visitors)*1000 |
Ad Revenue Insights | Subscription ARPU | m_subscription_rpv | Average New Subscription Revenue Per Users : standard metric that divides new subscription revenue by the number of visitors multipled by one thousand. Calculation: | (New subscription revenue) / Visitors * 1000 | (m_experience_turnover/m_unique_visitors)*1000 |
VX | VX payments | m_vx_payments | Visits with VX paid conversion(s). | Count of visits where goal type = “Payment Term Converted”. | count distinct visit_ID WHERE Goal Type = “Payment Term Converted” |
VX | VX payment rate | m_vx_payment_rate | Proportion of visits with VX paid conversion(s). | VX payments / visits | (m_vx_payments / m_visits ) |