Log MTA - Rockerbox Data Foundation Docs

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:

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

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

​Description

​Schema Structure

​Usage Notes

​Table Creation

​Table Relationship

​Partition Keys

​Logical Primary Key

​log_mta_partner_permissioned_viewthrough

​log_mta_user_identifiers

​Related Tables

​Field Reference

​Table: log_mta

​Table: log_mta_user_identifiers

​Event Type Reference