> ## 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.<geo>.<web_or_app>`) | 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 |


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.