ai-data-foundation-plan

Audit data assets, design a minimum viable customer schema, and produce a 90-day action plan.

1|Updated Mar 19, 2026

Search Tags:#planning #marketing #ai #data-quality #dpa #uganda #data-foundation

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npx skills add https://github.com/peterbamuhigire/social-media-skills --skill ai-data-foundation-plan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-data-foundation-plan
Source: https://github.com/peterbamuhigire/social-media-skills/tree/main/ai-data-foundation-plan
Command: npx skills add https://github.com/peterbamuhigire/social-media-skills --skill ai-data-foundation-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

A structured, compliant data foundation enables AI marketing by ensuring clean data assets, a minimal viable schema, and a practical 90-day action plan.

Core Features & Use Cases

Data asset inventory and quality assessment to map all sources (including WhatsApp, spreadsheets, and CRM)
Design of a minimum viable customer schema tailored to EA marketing needs
A concrete 90-day plan with milestones, ownership, and compliance considerations (Uganda DPA)

Quick Start

Provide client details and run the data foundation plan to generate the 90-day roadmap.

Frequently Asked Questions about ai-data-foundation-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build an AI-ready data foundation for marketing?▼

To build an AI-ready data foundation, you must audit existing data assets, assess data quality across sources like CRM and spreadsheets, design a minimum viable customer schema, and create a 90-day implementation action plan.

What is a minimum viable customer schema for AI marketing?▼

A minimum viable customer schema is a structured data model tailored to map core customer attributes. It ensures AI marketing tools have clean, standardized, and accessible data inputs required for targeted campaigns.

How do I assess data quality and readiness for AI tooling?▼

Assessing data quality for AI tooling involves inventorying all data sources, including WhatsApp and CRM systems, evaluating data cleanliness and consent, and mapping tool readiness to ensure compliance with regulations like the Uganda DPA.

Can I use this data foundation planning approach for large East African clients?▼

Yes, this data foundation planning approach is specifically designed for large East African clients across industries such as banks, NGOs, telecoms, and universities, addressing regional compliance like the Uganda DPA.

What is included in a 90-day data foundation action plan?▼

A 90-day data foundation action plan includes concrete milestones, task ownership, and compliance considerations to systematically transition from scattered data assets to an AI-ready marketing infrastructure.

Why do I need a data asset inventory before implementing AI marketing tools?▼

A data asset inventory is required before implementing AI marketing tools to identify all available data sources, evaluate their quality, and ensure they meet consent and compliance standards for secure AI processing.