> ## Documentation Index > Fetch the complete documentation index at: https://data-foundation.rockerbox.com/llms.txt > Use this file to discover all available pages before exploring further. # Log MTA ## Description * Captures every marketing touchpoint on each individual user path to conversion. * Synthesizes several types of data: * User context on the conversion event as well as conversion timestamp. * User, device, and referrer context for each marketing event. * UTM parameter tracking and custom URL parameters for each marketing event * Marketing ad object context for each marketing event. * Attribution credit assigned to each marketing event per four attribution methodologies: (1) first touch (2) last touch (3) even weight (4) Rockerbox custom multi-touch attribution model. * Excludes deterministic viewthrough touchpoints from Pinterest and Meta partnership integrations due to data sharing agreement restrictions. *** ## Schema Structure * Log Level MTA data is split into two tables with a 1:1 relationship: * **`log_mta_partner_permissioned_viewthrough`**: Core marketing touchpoint and attribution data * **`log_mta_user_identifiers`**: User identifier and device information (PII-adjacent data) * Both tables report data for ALL conversion events tracked in Rockerbox (e.g., Purchase, Add to Cart). *** ## Usage Notes * **Attribution Analysis**: All attribution metrics (first touch, last touch, even, normalized) are available in `log_mta_partner_permissioned_viewthrough`. * **Privacy & Compliance**: User identifiers are isolated in `log_mta_user_identifiers` to enable stricter access controls. * **Query Performance**: When user event identifiers are not needed, query only `log_mta_partner_permissioned_viewthrough` to reduce data scanned. * **Filtering by Conversion Type**: Join with `log_conversions_*` tables enrich attribution data with additional conversion and user context. *** ## Table Creation These tables are automatically created upon connecting Rockerbox with your supported warehouse provider. *** ## Table Relationship The two tables have a **1:1 relationship** based on the `log_mta_id` field: * Each record in `log_mta_partner_permissioned_viewthrough` has exactly one corresponding record in `log_mta_user_identifiers` * Join the tables using: `log_mta_id` This separation allows for flexible data governance and access control of user identifiers **Example Join:** ```sql theme={null} SELECT m.*, u.uid_event, u.hash_ip_event, u.user_agent_event, u.base_id FROM log_mta_partner_permissioned_viewthrough m LEFT JOIN log_mta_user_identifiers u ON m.log_mta_id = u.log_mta_id AND m.conversion_event_id = u.conversion_event_id --Include partition keys for optimal query performance AND m.date = u.date --Include partition keys for optimal query performance WHERE m.date >= '2026-01-01' AND m.conversion_event_id = '12345' ``` *** ## Partition Keys These are external tables. Always leverage partition keys when querying to improve query performance: **Log MTA**: * `log_mta_partner_permissioned_viewthrough.conversion_event_id` * `log_mta_partner_permissioned_viewthrough.date` **Log MTA User Identifiers**: * `log_mta_user_identifiers.conversion_event_id` * `log_mta_user_identifiers.date` **Note**: The `conversion_event_id` in these tables references `conversion_event_metadata.conversion_event_id`. Use `conversion_event_metadata` to find valid IDs before filtering. *** ## Logical Primary Key ### `log_mta_partner_permissioned_viewthrough` * `log_mta_id` — Unique identifier for each marketing touchpoint / event record ### `log_mta_user_identifiers` * `log_mta_id` — Unique identifier matching the corresponding record in `log_mta` *** ## Related Tables * **`log_conversions_*`**: Reference table containing metadata for the instance of the given conversion event * TBD * TBD * **`conversion_event_metadata`**: Reference table containing metadata for all conversion events tracked in Rockerbox. Use this table to: * Discover available conversion event IDs and their human-readable names to enabling filtering on specific conversions * Identify which conversion events are currently active \[!IMPORTANT] Always filter `log_mta_partner_permissioned_viewthrough` and `log_mta_user_identifiers` on `conversion_event_id` to leverage partition keys. *** ## Field Reference ### Table: `log_mta` Core marketing touchpoint and attribution data. | Name | Description | Type | | -------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | conversion\_event\_id | Partition Key - unique identifier of the conversion event tracked in Rockerbox | str | | date | Partition Key - date that the conversion occured | str | | log\_mta\_id | Unique identifier for the marketing touchpoint record attributed to the conversion | str | | log\_conversion\_id | Unique identifier for each instance of the conversion - used to join against log\_conversions schemas | str | | conversion\_id | Secondary unique identifier for each instance of the conversion - should not be used as a join key | str | | action | Name of the conversion action tracked in Rockerbox. This is often overloaded with additional dimensions for segmentation (e.g., `purchase..`) | str | | event\_type | Marketing event type (e.g., `onsite`, `tiktok_view`, `facebook_click`) that indicates whether the interaction was a click or impression. | str | | touchpoint\_id | Unique identifier for the marketing touchpoint | str | | sequence\_number | Order of the touchpoint in the user journey (1 = earliest) | int | | new\_to\_file | `1` if new customer (first-time conversion seen), else `0` | int | | pseudonymized\_user\_id | Pseudonymized user identifier for privacy | str | | request\_referrer | Referrer of the page where the user came from | str | | original\_url | URL of the marketing touchpoint | str | | utm\_campaign | UTM campaign parameter from the URL | str | | utm\_content | UTM content parameter from the URL | str | | utm\_medium | UTM medium parameter from the URL | str | | utm\_source | UTM source parameter from the URL | str | | utm\_term | UTM term parameter from the URL | str | | utm\_id | UTM ID parameter from the URL | str | | utm\_source\_platform | UTM source platform parameter from the URL | str | | utm\_creative\_format | UTM creative format parameter from the URL | str | | utm\_marketing\_tactic | UTM marketing tactic parameter from the URL | str | | mapping\_rule\_name | Name of the categorization rule applied to this touchpoint | str | | platform\_join\_key | Platform-specific identifier for joining with spend data | str | | platform | Marketing platform name (e.g., `tiktok_v3`, `facebook_v2`) | str | | tier\_1 | Marketing channel categorization level 1 (most broad), as defined in your mapping rules / reporting taxonomy. | str | | tier\_2 | Marketing channel categorization level 2 | str | | tier\_3 | Marketing channel categorization level 3 | str | | tier\_4 | Marketing channel categorization level 4 | str | | tier\_5 | Marketing channel categorization level 5 | str | | tier\_one | Raw ad object identifiers captured on event used to build reporting taxonomy | str | | tier\_two | Raw ad object identifiers captured on event used to build reporting taxonomy | str | | tier\_three | Raw ad object identifiers captured on event used to build reporting taxonomy | str | | tier\_four | Raw ad object identifiers captured on event used to build reporting taxonomy | str | | tier\_five | Raw ad object identifiers captured on event used to build reporting taxonomy | str | | timestamp\_conv | Timestamp of when the conversion occurred (ISO 8601 UTC) | timestamp | | timestamp\_events | Timestamp of the marketing event (ISO 8601 UTC) | timestamp | | updated\_at | Timestamp when the record was last updated. All records for same `date` + `conversion_event_id` partition share the same `updated_at` | timestamp | | onsite\_count | Total number of times the user appeared on your site | int | | total\_events | Number of marketing touchpoints before conversion | int | | even | Equal fractional credit across touchpoints | float | | first\_touch | `1` if first touchpoint, else `0` | int | | last\_touch | `1` if last touchpoint, else `0` | int | | normalized | Fractional attribution assigned by multi-touch model | float | | total\_revenue\_usd | Total revenue in USD associated with the conversion | float | | revenue\_even\_usd | Revenue attributed under even weight distribution (USD) | float | | revenue\_first\_touch\_usd | Full revenue if it's the first touch, else `0` (USD) | float | | revenue\_last\_touch\_usd | Full revenue if it's the last touch, else `0` (USD) | float | | revenue\_normalized\_usd | Revenue assigned by multi-touch attribution model (USD) | float | *** ### Table: `log_mta_user_identifiers` User identifier and device information (PII-adjacent data). | Name | Description | Type | | --------------------- | ------------------------------------------------------------------------------ | ---- | | conversion\_event\_id | Partition Key - unique identifier of the conversion event tracked in Rockerbox | str | | date | Partition Key - date that the conversion occured | str | | log\_mta\_id | Unique identifier matching the corresponding record in `log_mta` | str | | uid\_event | Rockerbox user ID cookie from the event | str | | hash\_ip\_event | Hashed IP address of the user for that event | str | | user\_agent\_event | User agent ID or identifier from the marketing event | int | | base\_id | Primary user identifier (e.g., customer ID) | str | *** ## Event Type Reference The `event_type` column in `log_mta` indicates the nature of each tracked touchpoint: | Event Type | Definition | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | | onsite | A click drove a user to site where a marketing touchpoint was tracked | | creative | A display impression (view-based touchpoint) | | address\_clean\_hash | A Direct Mail touchpoint from mailer address matchback | | postlog | A linear TV touchpoint from postlog spike analysis | | mail | A direct mail touchpoint via address matchback | | facebook\_click | In-app Facebook click that leads to conversion across devices | | tiktok\_click | In-app TikTok click that leads to conversion across devices | | adwords\_click | In-app YouTube click that leads to conversion across devices | | facebook\_view | Facebook view-based touchpoint (synthetically modeled) | | ott\_device\_via\_batch | View-based touchpoint that leverages an IP address matchback (includes Reddit viewthrough facilitated via Reddit data sharing partnership) | | ott\_mobile\_app\_via\_batch | View-based touchpoint that leverages an IP address matchback (includes Reddit viewthrough facilitated via Reddit data sharing partnership) | | ott\_web\_pixels | View-based touchpoint that leverages an IP address matchback (includes Reddit viewthrough facilitated via Reddit data sharing partnership) | | ott\_web\_via\_batch | View-based touchpoint that leverages an IP address matchback (includes Reddit viewthrough facilitated via Reddit data sharing partnership) | | external\_id | Touchpoint via custom matching of external file to Rockerbox data | | viewthrough\_events\_reddit | Reddit view-based touchpoint via deterministic matchback facilitated via a user-level data sharing partnership | | viewthrough\_events\_snapchat | Snapchat view-based touchpoint via deterministic matchback facilitated via a user-level data sharing partnership | | viewthrough\_events\_tiktok | TikTok view-based touchpoint via deterministic matchback facilitated via a user-level data sharing partnership | | tiktok\_view | TikTok view-based touchpoint (extrapolation of deterministic matchback to account for low user tracking opt-in rate) | | adwords\_view | View-based touchpoint for YouTube/Demand Gen campaigns (synthetically modeled) | | conv\_only | A direct (unattributed) touchpoint | | survey | A touchpoint inserted into user path to conversion based on a post-purchase survey |