Context Pattern Graph
Extract marketing decision context by detecting domain-specific patterns in documents teams already use. Turns unstructured execution artifacts into a structured decision graph.
Page Metadata
- Meta Title
- Context Pattern Graph - Marketing Decision Intelligence | DataInc.ai
- Meta Description
- Extract marketing decision context from documents and workflows. Turn unstructured execution artifacts into a structured decision graph.
- Primary Keywords
- context pattern graphmarketing decision intelligence
- Secondary Keywords
- decision contextmarketing knowledge graphAI marketing
What is a Context Pattern Graph?
Beyond traditional data
Capturing the "why"
A living decision record
Traditional systems of record store what happened: budgets changed, campaigns launched, conversions recorded. But they never capture why decisions were made. A Context Pattern Graph is a new layer of enterprise data architecture that captures decision traces: the inputs, exceptions, approvals, and reasoning behind each marketing action. Over time, this accumulated structure becomes a searchable precedent and an auditable source of truth explaining not just what happened, but why it was allowed to happen.
The Marketing Decision Problem
Lost context
Siloed reasoning
Invisible patterns
Today, critical marketing context is lost. When a team doubles ad spend on a channel, the platform records the new budget but not the rationale. Why a specific audience segment was targeted, or why a creative was approved despite low test scores, lives only in emails, Slack threads, and meeting notes. This lost context makes it impossible for AI systems to learn from past decisions or for new team members to understand precedent.
How Context Pattern Graph Works
Document intelligence
Pattern detection
Graph construction
DataInc.ai's Context Pattern Graph automatically extracts decision context from the documents teams already create: campaign briefs, performance reviews, approval emails, strategy decks, and media plans. Using domain-specific pattern detection trained on marketing workflows, we identify decision points, the inputs considered (performance metrics, customer feedback, external trends), rules applied (marketing guidelines, budget limits), exceptions made (overriding a policy for a key customer), and approvals granted. These elements are connected into a queryable graph structure.
Key Capabilities
Decision trace capture
Precedent search
AI context layer
The Context Pattern Graph enables three powerful capabilities: (1) Automatic decision trace capture, where every budget change, targeting shift, or creative approval is logged with its full context. (2) Precedent search, allowing you to query "How did we handle a similar campaign when a competitor ran a flash sale?" and surface prior decisions with their outcomes. (3) AI context layer, providing AI agents with the memory of past decisions and situational context that human marketers use intuitively, enabling truly intelligent automation.
From Fragmented Data to Connected Context
Unified view
Relationship mapping
Timeline awareness
A normal database might tell you a customer purchased a product. A Context Pattern Graph shows that the same customer clicked a Facebook ad, later opened three support tickets, and only converted after a retention email, along with the decision logic that triggered each touchpoint. This 360-degree view with explicit relationships and timelines goes beyond traditional CDPs by not only unifying data but encoding the sequence and reasoning behind interactions and outcomes.
The System of Record for Marketing Decisions
Auditable history
Institutional memory
Accelerated onboarding
Just as Salesforce became the system of record for sales transactions, the Context Pattern Graph becomes the system of record for marketing decisions. New team members can instantly understand why past campaigns were structured certain ways. Auditors can trace any spend decision back to its approval chain. AI systems can make recommendations grounded in actual organizational precedent rather than generic best practices.
Enabling the Next Generation of Marketing AI
Contextual agents
Informed automation
Continuous learning
In the age of AI agents, owning the context layer (the "why" behind decisions) is critical. The Context Pattern Graph provides the structured, queryable context that AI systems need to act with awareness of who the customer is, what's happening, what's been done before, and what constraints apply. This enables "right person, right message, right time" marketing by giving AI the institutional memory that human marketers build over years.
Integration with DataInc.ai Platform
Unified data layer
Quality-aware context
Revenue impact linkage
The Context Pattern Graph integrates seamlessly with DataInc.ai's other capabilities. Auto-Discovery maps your data landscape. Golden Taxonomy ensures consistent semantics. Rule Packs validate data quality. And the Context Pattern Graph adds the decision intelligence layer, connecting quality issues to the decisions that caused them and enabling AI-powered root cause analysis that understands not just what broke, but why the original decision was made.