How to Build a Marketing Knowledge Base to Power AI-Enabled Marketing
- Chris McLellan
- Oct 21
- 5 min read
Updated: Nov 3
Marketers face growing pressure to harness a wave of AI tools without losing creativity, control, or results. Real progress comes from a system-level approach. Within an AI-Enabled Marketing System, the Marketing Knowledge Base is the foundation that connects strategy, content, and data in one reliable source of truth.
This is the anchor post for an open research initiative focused on developing a practical framework for building an AI-Enabled marketing function. Marketers, vendors, and other stakeholders are invited to contribute. To participate as an attributed collaborator, email: chris@friendselectric.ca
Quick Summary
Marketing teams are under pressure to adopt AI technology to scale activities without losing creativity, compliance, or brand integrity. The foundation for doing this effectively is a Marketing Knowledge Base, a structured, AI-readable system that organizes brand, product, and marketing information into reusable insights.
This post explains how to design a Marketing Knowledge Base that supports composable, more personalized marketing activities.
What this post covers:
Why a Knowledge Base is essential for AI-enabled marketing systems
Information domains included in a marketing Knowledge Base
How to transform data into into AI-readable formats
Deciding where to start with the Knowledge Base
How to avoid vendor lock-in
A strong Knowledge Base powers the next generation of marketing operations, enabling speed, consistency, and insight-driven storytelling.
Inputs/Outputs For Marketing Knowledge Base
Key Inputs
Product Marketing Knowledge Core (product information)
Insights from customers, partners, and colleagues
Performance data from marketing programs, tools, and systems
Key Outputs
Structured tables for 15+ informational domains
Insights (rows summarized by AI)
AI-readable docs that sync insights to AI Research Assistants
Pro Tips In Marketing Knowledge Base Design
Identify Informational Sub-Domains
A Knowledge Base is a structured source of truth that supplies information to a modern Content Engine. It captures the essential data that an organization can use (and reused) to tell consistent, factual stories about its products, people, and mission.
The information is typically hosted in spreadsheets or databases and organized in tables that reflect the key domains within the marketing function. This data provides the raw material for AI systems to compose more accurate, consistent, and personalized content.
The key marketing informational domains include:
Market: Geographic, industry, category
Product: Positioning, personas, value props, win/loss etc. (Product Marketing Core Knowledge)
Brand: Identity, tone, mission, values, visual + narrative rules.
Proof & Credibility: Testimonials, case studies, awards, press, analyst mentions
Pricing & Packaging: Tiers, bundles, licensing, promotions
Programs & Promotions: Loyalty schemes, offers, sustainability/buy-back, incentives
Legal & Compliance: Disclaimers, brand usage rights, data governance, accessibility
People: Profiles of Founders, internal experts, advocates, partners, influencers
Insights: Trends, patterns, anomalies powered by interviews + AI Notetakers
Messaging & Storytelling: CTAs, narratives, tone/voice examples
Operations & Performance: Channels, KPIs, campaigns, experiments, dashboards
Partnerships & Ecosystem: Integrations, co-marketing alliances, tech stack relationships
Collaborate Where Possible
Ownership of Knowledge Base tables should be shared wherever it make sense. For example, as subject matter experts, Product Marketing folks should own the Product Playbook (which is actually multiple tables). Similarly, if resources are limited, Finance might be able to manage the Pricing table.
Ultimately, data should be owned and managed by the people who understand how to improve and govern it best.
Transform Information Into Insights
In an AI-Enabled Marketing system, insights are concise, factual summaries drawn from structured marketing information.
Most spreadsheets (e.g. Google Sheets with Gemini, Excel with Copilot) and databases (e.g. Airtable) integrate AI capabilities that can be leveraged to summarize single or multiple records. This is a fast and efficient way to create composable “insights,” concise factual summaries that can be assembled and reassembled to generate accurate, compelling, and personalized content at scale. They are the genes that make up your content DNA.
Note: Insights are conceptually similar to the reusable “blocks” used in CRM or CMS systems, but they differ in purpose and flexibility. Insights are designed to brief AI content tools as part of a prompt, helping generate accurate and context-aware drafts. Blocks, by contrast, are static components limited to specific formats such as emails or web pages.
Sync Insights To Docs
Tables are excellent for organizing structured data, but most Generative AI tools still perform best when reading natural language. Turning structured rows into readable text helps bridge that gap.
A simple way to do this is to sync your Knowledge Base insights to documents that can be connected or uploaded to AI Research Assistants such as NotebookLM. A lightweight Google Apps Script or workflow platform like N8N can automate the process.
Note: Enterprise teams with access to Vector Database technology may be able to streamline this even further.
The alternative is to build a “doc-centric” Knowledge Base from the start, but large files and folders tend to introduce more errors, duplication, and drift over time. Keeping your data structured and automatically exported as text gives you the best of both worlds.
Stay Structured, Move Fast
It’s tempting to publish content ad hoc, but without a structured Knowledge Base as your foundation, scale and consistency will quickly break down.
Without it, achieving the benefits of an AI-enabled Marketing System, including speed, accuracy, and creative consistency, is nearly impossible.
Whether or not your business intends to invest in a large content marketing team, this is the path forward.
Avoid Vendor Lock-In
Your Marketing Knowledge Base is a strategic asset. Treat it like one.
Many CRM, email, and CMS platforms offer dynamic content capabilities, but with so many AI tools in today's martech landscape, marketers should be cautious about hosting their Knowledge Base in a dedicated app rather than a more flexible data management environment like a spreadsheet or database.
Some issues to consider:
Restrictions on table design, which will limit blocks
Difficulty in exporting data e.g. Custom content bots
Only support one or two content formats e.g. email and blog only
Challenges with access e.g. access ties to subscribers only
Issues with governance
Maximizing the ownership and control of critical marketing data is generally advised for marketers.
Explore Other Posts In The Series
Module 3: Planning (this post)
Module 4: Production (coming soon)
Module 5: Orchestration (coming soon)
Module 6: Optimization (coming soon)
Join This Research Project
For many marketers, AI is simultaneously everywhere and nowhere.
Teams are testing its capabilities, but few are adopting operational systems to actually guide its implementation, mainly because so few frameworks actually exist.
This research project is all about learning in public and building smarter and more productive marketing functions through controlled human-AI collaboration.
If you have expertise in marketing, creative strategy, knowledge management, system design, or AI agents and would like to become an attributed co-author of the design and Build Notes doc, please get in touch.
Email: chris@friendselectric.ca
About Friends Electric
Friends Electric is a private AI marketing consultancy founded by Chris McLellan, a Certified Chartered Marketer and contributing member of the AI Marketing Committee at the Canadian Marketing Association.
He's also founder and producer of the Ask AI podcast, and serves as Technical Committee Lead and co-author at the Digital Governance Council for the Data Collaboration Framework, a Canadian and international standard governing human-ai innovation.
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