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For questions about metrics, tables, and how SourceMedium works, the AI Analyst uses Knowledge Retrieval — providing instant answers from documentation and metadata without querying your warehouse.

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When Knowledge Retrieval Is Used

Knowledge Retrieval handles questions about definitions, concepts, and schema — anything that can be answered from SourceMedium documentation rather than your warehouse data.

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Examples

What is LTV?
How is ROAS calculated?
What does conversion rate mean?
Which table has order data?
What columns are in the customers table?
How does attribution work?
What's the difference between first-click and last-click?
How do I set up UTM tracking?
These questions share key characteristics:
  • “What is” / “How does” phrasing
  • Metric definitions (LTV, ROAS, AOV)
  • Schema questions (tables, columns)
  • How SourceMedium works

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How It Works

1

Classify Question

The AI recognizes that your question is about concepts or schema, not about querying data.
2

Search Knowledge Base

The question is matched against SourceMedium documentation and metadata.
3

Generate Answer

The AI synthesizes a clear answer from the relevant sources, formatted for Slack.

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What You’ll See

Knowledge Retrieval responses include:
ComponentDescription
AnswerClear explanation of the concept or term
SourceLinks to relevant documentation pages
ContextRelated concepts you might want to explore
No SQL is generated for Knowledge Retrieval questions. The answer comes directly from documentation and metadata.

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Question Categories

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Metric Definitions

What is LTV?
How is ROAS calculated?
What does AOV mean?
How is conversion rate defined?
The AI explains what the metric measures, how it’s calculated, and where you can find it in your data.

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Schema & Tables

Which table has order data?
What columns are in obt_orders?
Where do I find customer information?
What's the difference between dim_orders and obt_orders?
The AI describes table purposes, key columns, and when to use each table.

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SourceMedium Concepts

How does attribution work?
What's the difference between first-click and last-click?
How do I set up UTM tracking?
What is the attribution source hierarchy?
The AI explains SourceMedium-specific methodology and configuration.

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Data Structures

What are the possible values for order_type?
How is sales_channel determined?
What does sm_default_channel mean?
The AI explains dimension values, enums, and how data is categorized.

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Tips for Knowledge Questions

“What is LTV?” triggers Knowledge Retrieval. “What was our LTV last month?” triggers Standard Analysis.
Schema questions are answered from documentation, not by querying metadata.
After getting a definition, you can ask follow-up questions: “How do I calculate that in SQL?” or “Show me an example.”

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From Knowledge to Analysis

After understanding a concept, you can immediately apply it: Knowledge: “What is ROAS?”
ROAS (Return on Ad Spend) is calculated as attributed revenue divided by ad spend…
Follow-up: “What was our ROAS by channel last month?”
The AI now runs a Standard Analysis query to get your actual ROAS data.
The AI retains conversation context. If you ask about a concept and then want to see your data, it connects the two.

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Knowledge Sources

Knowledge Retrieval draws from:
  • Data Dictionary — Metrics and dimensions
  • Table Schemas — Column definitions and relationships
  • Core Concepts — Attribution, data transformations
  • Integration Guides — Platform-specific information
  • FAQs — Common questions and troubleshooting

Standard Analysis

How specific data queries are handled.

Deep Analysis

How open-ended questions trigger multi-perspective analysis.

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Explore the Knowledge Base

These are the sources the AI draws from for Knowledge Retrieval:

Glossary

Definitions of common terms and acronyms.

Attribution Concepts

How SourceMedium attributes orders to channels.