How to Build a Marketing Knowledge Base for AI-Enabled Content Engines

Marketers are under pressure to produce more personalized content at greater scale without losing creativity or control. A Marketing Knowledge Base provides a resource to help make this possible, giving teams a single, reliable source of truth to power AI-assisted Content Engines.

This post is the first module in the “Guide to AI-Enabled Content Engines”, a new series by Chris McLellan, Principal AI Marketer at Friends Electric:

The Marketing Knowledge Base is at the heart of AI-Enabled Content Engines. Click to enlarge

Please Note! While this post focuses on the role of a Marketing Knowledge Base within the context of a Content Engine system, they are an incredibly valuable resource that supports a range of use cases, including planning, reporting, and campaign optimization.

Quick Summary

Marketing teams are under pressure to scale content 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 components.

This post explains how to design and maintain a Knowledge Base that supports composable content creation.

What this post covers:

• Why a Knowledge Base is essential for AI-forward marketing

• The 13 informational domains that Knowledge Base include

• How a Marketing Knowledge Base relates to content pillars

• How to transform data into into AI-readable formats

• How to decide where to start

• How to avoid vendor lock-in

A strong Knowledge Base powers the next generation of content operations, enabling speed, consistency, and insight-driven storytelling. These critical assets are best maintained as a series of tables and documents in spreadsheets or more robust data platforms like Airtable.

Structuring Marketing Knowledge Base

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:

• Brand: Identity, tone, mission, values, visual + narrative rules.

• Product: Features, benefits, value props, differentiators (aka Product Playbook)

• 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: Stories, observations, examples powered by interviews + AI Notetakers

• Market: Personas, segments, competitors, trends

• Messaging & Storytelling: Copy blocks, CTAs, narratives, tone/voice examples

• Operations & Performance: Channels, KPIs, campaigns, experiments, dashboards

• Partnerships & Ecosystem: Integrations, co-marketing alliances, tech stack relationships

• Competitive Intelligence: Competitor tracking, win/loss data, category benchmarks
  

Knowledge Base Relationship To Content Pillars

The tables in the Knowledge Base are abstracted into a smaller number of Content Pillars, which are the recurring themes that run throughout content strategies:

• Purpose & Vision: Why we exist, what drives us (via Brand + Programs)

• Innovation & Product: What we’re building and improving (via Product + Insights)

• Proof & Impact: Customer success, metrics, stories (via Proof + People)

• Community & Collaboration: Partnerships, voices, shared learning (via People + Insights)

• How-To & Education: Guidance, thought leadership, operational learnings (via Market + Ops)

Best Practices For Build Marketing Knowledge Base

Let Pillars Prioritize Tables

Populating 13+ tables can be daunting, so marketers should start with the tables that serve the most urgent or viable content pillars.

For example:

• If your company has early customer success stories, start with Proof & Impact.

• If your product has early traction, start with Innovation & Product.

• If your business is very early stage, begin with Purpose & Vision.

The point is that a marketing Knowledge Base is a dynamic, living resource that is constantly evolving.

Collaborate Where Possible

Ownership of Knowledge Base tables should be shared wherever it make sense. For example, as a 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.

Leverage AI Columns To Generate Blocks

Most spreadsheets and databases offer AI-powered columns that can be prompted to summarize a row (aka record) of data. This is is a fast and efficient way to create modular "blocks" of information that can be used by Generative AI tools to create accurate, compelling, and personalized content at scale.

Transform Blocks Into 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 blocks into documents that can be connected or uploaded to AI tools such as NotebookLM or Custom GPTs. 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 Content Engine, 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 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

1. Overview

2. Marketing Knowledge Base

3. Content Collaboration

4. Content Planning (this post)

5. Content Production

6. Content Publishing

7. Content Tracking

Let's Talk

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