> ## 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 Level MTA

## Description

* Log Level MTA captures every marketing touchpoint on each individual user path to conversion.
* Log Level MTA is the synthesis of 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.

***

## Table Creation

* One log level MTA table is created for a single conversion event tracked in Rockerbox.
* The table is manually created in the [Rockerbox UI](https://app.rockerbox.com/v3/data/exports/data_warehouse).

***

## Partition Keys

* `date`

💡 **Note:** Leverage partition keys when querying the table to improve query efficiency.

***

## Logical Primary Key

These fields uniquely identify a record. While data warehouses do not enforce primary key constraints, this combination functions as the logical primary key for the table.

* `conversion_key`
* `sequence_number`

***

## Field Reference

| Name | Description | Type |
| - | - | - |
| report | The name of the report (only visible in Snowflake integrations) | str |
| advertiser | Rockerbox Account ID (only visible in Snowflake integrations) | str |
| identifier | Conversion segment ID (only visible in Snowflake integrations) | int |
| date | Date when the conversion event occurred | date |
| timestamp\_conv | Timestamp of when the conversion occurred (ISO 8601 UTC) | timestamp |
| conversion\_hash\_id | A hash identifier for a unique conversion (based on `conversion_key`) | str |
| conversion\_key | Unique delivered conversion ID (e.g., your Order ID) | str |
| action | Name of the conversion event | str |
| new\_to\_file | `1` if new customer (first-time conversion seen), else `0` | int |
| onsite\_count | Total number of times the user appeared on your site | int |
| total\_events | Number of marketing touchpoints before conversion | int |
| event\_id | Unique identifier for each marketing touchpoint | str |
| timestamp\_events | Timestamp of the marketing event (ISO 8601 UTC) | timestamp |
| sequence\_number | Order of the touchpoint in the user journey (1 = earliest) | int |
| hash\_ip\_events | Hashed IP of the user for that event | str |
| type | Report type (e.g., `platform_data`, `attribution`) | str |
| uid | Rockerbox user ID cookie | str |
| user\_agent\_events | User agent string from the marketing event | str |
| base\_id | Primary user identifier | str |
| currency\_code | Reporting currency for revenue and spend | str |
| fx\_rate\_to\_usd | Exchange rate to USD (1 if already USD) | float |
| platform | Name of platform (always `Rockerbox` for this dataset) | str |
| spend\_key | Platform spend identifier (usually Ad ID or composite key) | str |
| matches | List of categorization rules matched (last one is used) | dict |
| tier\_1 | Five-level categorization tiers aligned to UI taxonomy (most broad) | str each |
| tier\_2 | Five-level categorization tiers aligned to UI taxonomy | str each |
| tier\_3 | Five-level categorization tiers aligned to UI taxonomy | str each |
| tier\_4 | Five-level categorization tiers aligned to UI taxonomy | str each |
| tier\_5 | Five-level categorization tiers aligned to UI taxonomy (most granular) | str each |
| original\_url | URL of the marketing touchpoint | str |
| request\_referrer | Referrer of the page where the user came from | str |
| utm\_parameters | Dictionary of all UTM query parameters passed in the URL | dict |
| url\_parameters | Other non-UTM URL parameters | dict |
| tier\_one | Source data fields for taxonomy\_lookup categorization | str each |
| tier\_two | Source data fields for taxonomy\_lookup categorization | str each |
| tier\_three | Source data fields for taxonomy\_lookup categorization | str each |
| tier\_four | Source data fields for taxonomy\_lookup categorization | str each |
| tier\_five | Source data fields for taxonomy\_lookup categorization | str each |
| normalized | Fractional attribution assigned by multi‑touch model | float |
| revenue\_normalized | Conversion revenue assigned by model | float |
| first\_touch | `1` if first touchpoint, else `0` | int |
| revenue\_first\_touch | Full revenue if it's the first touch, else `0` | float |
| last\_touch | `1` if last touchpoint, else `0` | int |
| revenue\_last\_touch | Full revenue if it's the last touch, else `0` | float |
| even | Equal fractional credit across touchpoints | float |
| revenue\_even | Revenue attributed under even weight distribution | float |
| rb\_sync\_id | Rockerbox internal sync identifier | int |
| updated\_at | Timestamp when the record was last updated | timestamp |
| marketing\_type | Touchpoint category (e.g., `onsite`, `creative`, `mail`, etc.) | str |

***

## Marketing Event Type Reference

The `marketing_type` column indicates the nature of each tracked touchpoint:

| Marketing 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 leveages an IP address matchback (includes Reddit viewthrough faciliated via Reddit data sharing partnership) |
| ott\_mobile\_app\_via\_batch | View-based touchpoint that leveages an IP address matchback (includes Reddit viewthrough faciliated via Reddit data sharing partnership) |
| ott\_web\_pixels | View-based touchpoint that leveages an IP address matchback (includes Reddit viewthrough faciliated via Reddit data sharing partnership) |
| ott\_web\_via\_batch | View-based touchpoint that leveages an IP address matchback (includes Reddit viewthrough faciliated 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 facilaited via a user-level data sharing partnership |
| viewthrough\_events\_snapchat | Snapchat view-based touchpoint via deterministic matchback facilaited via a user-level data sharing partnership |
| viewthrough\_events\_tiktok | TikTok view-based touchpoint via deterministic matchback facilaited via a user-level data sharing partnership |
| tiktok\_view | TikTok view-based touchpoint (extrapolation of determinsitic 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 |


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