Multi-Touch Attribution Engine Architectural Specification

Role: Principal Event-Driven Solutions Architect specializing in Marketing Technology infrastructure.

Context

• Target Brand Ecosystem: {{brand_ecosystem}}
• Primary CRM Platform: {{crm_platform}}
• Ingested Ad Networks and Channels: {{ad_networks}}
• Estimated Peak Event Ingestion: {{event_throughput}}
• Identity Graph Persistence Store: {{identity_graph_storage}}
• Ingestion to Reporting Latency SLA: {{latency_sla}}

Task

Produce an end-to-end multi-touch attribution (MTA) architecture specification that reconciles anonymous visitor interactions with authenticated customer lifecycles across {{brand_ecosystem}} while maintaining {{latency_sla}} SLAs.

Method

1. Define ingestion topology for disparate clickstream and conversion hooks from {{ad_networks}} to absorb {{event_throughput}}.
2. Specify the streaming buffer, event schema validation, and dead-letter queue mechanics.
3. Architect the identity resolution engine utilizing {{identity_graph_storage}} for deterministic and probabilistic user stitching.
4. Formalize the attribution modeling service supporting first-touch, linear, time-decay, and algorithmic shapley values.
5. Design state synchronization and bi-directional webhooks back into {{crm_platform}}.
6. Detail caching, aggregation layer partitioning, and analytical query access patterns.
7. Establish failure domain isolation, data replay protocols, and disaster recovery strategies.

Constraints

• Architecture MUST support idempotency keys on every ingestion endpoint to prevent duplicate conversion records.
• MUST NOT introduce single points of failure in the stream ingestion path.
• Identity graph merges must be fully auditable with rollback capabilities.
• Storage partitioning must be aligned with query access patterns across campaign dimensions.

Output format

Provide the architectural specification organized into these sections:

1. System Topology & Data Flow Diagram (ASCII/PlantUML format)
2. Ingestion & Validation Subsystem Specification
3. Identity Graph Storage Schema & Stitching Logic
4. Attribution Calculation Pipeline & Storage Layout
5. {{crm_platform}} Integration & Reverse-ETL Interface
6. Operational Resilience & Capacity Planning Target length: 1100-1400 words.

Self-review

• Confirm {{brand_ecosystem}}, {{crm_platform}}, {{ad_networks}}, {{event_throughput}}, {{identity_graph_storage}}, and {{latency_sla}} are explicitly addressed.
• Verify that both deterministic and probabilistic resolution failure cases are covered.
• Validate that replay strategies handle out-of-order conversion events.