Data Collection Plan
When to Use This Skill
Use this skill when you need to:
- Plan what data to collect across your business operations
- Design tracking implementations for web, product, or marketing
- Ensure data collection complies with privacy regulations
- Create a data architecture plan for a growing business
DO NOT use this skill for data analysis, dashboard building, or database engineering. This is for planning what to collect, why, and how.
Core Principle
COLLECT DATA WITH PURPOSE — EVERY DATA POINT MUST ANSWER A BUSINESS QUESTION OR DRIVE A DECISION. COLLECTING "JUST IN CASE" CREATES LIABILITY WITHOUT VALUE.
Phase 1: Brief
Required Inputs
| Input |
What to Ask |
Default |
| Business type |
"What does your business do?" |
Must be provided |
| Key decisions |
"What decisions do you wish you had better data for?" |
Must be provided |
| Current data |
"What data do you already collect? Where does it live?" |
Minimal — starting fresh |
| Channels |
"Where do you interact with customers? (website, app, email, social, in-person)" |
Website and email |
| Privacy requirements |
"Where are your customers? (affects GDPR, CCPA, etc.)" |
US-based customers |
| Technical resources |
"Do you have a developer or will you self-implement?" |
Self-implement with no-code tools |
GATE: Confirm brief before proceeding.
Phase 2: Design
Data Collection Framework
Organize by business function:
- Marketing data — traffic sources, campaign performance, ad spend, conversions
- Product/website data — user behavior, feature usage, engagement metrics
- Sales data — leads, pipeline stages, close rates, deal values
- Customer data — profiles, preferences, purchase history, support interactions
- Financial data — revenue, costs, margins, cash flow
- Operational data — fulfillment times, error rates, capacity utilization
Data Priority Matrix
For each data point, assess:
- Value: How much does this data improve decisions? (High/Med/Low)
- Effort: How hard is it to collect? (High/Med/Low)
- Privacy risk: Does this involve personal data? (Yes/No)
Start with high-value, low-effort, low-risk data.
GATE: Present the prioritized data collection plan and wait for approval.
Phase 3: Build
Deliverables
1. Data Collection Inventory
| Data Point |
Source |
Collection Method |
Storage |
Frequency |
Privacy Level |
| Page views |
Website |
GA4 |
Google |
Real-time |
Low |
| Email signups |
Forms |
Zapier → CRM |
CRM |
Real-time |
Medium |
| Revenue |
Stripe |
API sync |
Spreadsheet |
Daily |
High |
2. Implementation Guide
- Step-by-step setup for each data collection tool
- Integration connections (what feeds into what)
- Testing procedures to verify data is flowing
3. Privacy Compliance Checklist
4. Data Quality Rules
- Naming conventions for events and fields
- Validation rules for data entry
- Deduplication strategy for customer records
- Regular audit schedule (monthly data quality check)
Phase 4: Polish
Data Stack Diagram
Create a simple map showing: data sources → collection tools → storage → reporting tools.
90-Day Implementation Roadmap
- Month 1: Core tracking (website analytics, basic CRM)
- Month 2: Marketing attribution (UTMs, conversion tracking)
- Month 3: Customer data enrichment (behavior tracking, segmentation)
Example 1: E-commerce Business
Priority data: Traffic sources, conversion events, AOV, cart abandonment rate, customer purchase history, email engagement. Tools: GA4, Shopify analytics, Klaviyo.
Example 2: Service Business
Priority data: Lead sources, consultation bookings, close rate, project profitability, client satisfaction scores. Tools: GA4, CRM (HubSpot free), Google Sheets for financials.
Anti-Patterns
- Collecting everything — more data means more privacy risk, more storage cost, and more noise. Be selective.
- No privacy consideration — collecting personal data without proper consent and documentation is a legal and financial risk.
- Data silos — customer data in 5 tools that do not talk to each other makes analysis impossible. Plan integrations from the start.
- No naming conventions —
email_signup, EmailSignup, email-signup, and signup_email in different tools creates chaos. Standardize.
- Collecting without reviewing — data nobody looks at is worse than no data because it creates a false sense of being data-driven.
Recovery
- User overwhelmed by options: Start with 3 data points that directly answer their most important business question. Expand later.
- Privacy concerns paralyze action: Focus on aggregated, non-personal data first (page views, conversion rates). Add personal data collection only with proper consent mechanisms.
- No technical ability: Recommend no-code tools (Zapier, Google Forms, native platform analytics). Most essential data collection requires zero code.
- Data already scattered: Begin with an inventory of existing data and create a consolidation plan before adding new collection.
1---2name: data-collection-plan3description: Plans data collection strategies with tracking requirements, privacy compliance, storage recommendations, and implementation steps. Use when building your business data infrastructure.4---56# Data Collection Plan78## When to Use This Skill910Use this skill when you need to:11- Plan what data to collect across your business operations12- Design tracking implementations for web, product, or marketing13- Ensure data collection complies with privacy regulations14- Create a data architecture plan for a growing business1516**DO NOT** use this skill for data analysis, dashboard building, or database engineering. This is for planning what to collect, why, and how.1718---1920## Core Principle2122COLLECT DATA WITH PURPOSE — EVERY DATA POINT MUST ANSWER A BUSINESS QUESTION OR DRIVE A DECISION. COLLECTING "JUST IN CASE" CREATES LIABILITY WITHOUT VALUE.2324---2526## Phase 1: Brief2728### Required Inputs2930| Input | What to Ask | Default |31|-------|------------|---------|32| **Business type** | "What does your business do?" | Must be provided |33| **Key decisions** | "What decisions do you wish you had better data for?" | Must be provided |34| **Current data** | "What data do you already collect? Where does it live?" | Minimal — starting fresh |35| **Channels** | "Where do you interact with customers? (website, app, email, social, in-person)" | Website and email |36| **Privacy requirements** | "Where are your customers? (affects GDPR, CCPA, etc.)" | US-based customers |37| **Technical resources** | "Do you have a developer or will you self-implement?" | Self-implement with no-code tools |3839**GATE: Confirm brief before proceeding.**4041---4243## Phase 2: Design4445### Data Collection Framework4647Organize by business function:48491. **Marketing data** — traffic sources, campaign performance, ad spend, conversions502. **Product/website data** — user behavior, feature usage, engagement metrics513. **Sales data** — leads, pipeline stages, close rates, deal values524. **Customer data** — profiles, preferences, purchase history, support interactions535. **Financial data** — revenue, costs, margins, cash flow546. **Operational data** — fulfillment times, error rates, capacity utilization5556### Data Priority Matrix5758For each data point, assess:59- **Value:** How much does this data improve decisions? (High/Med/Low)60- **Effort:** How hard is it to collect? (High/Med/Low)61- **Privacy risk:** Does this involve personal data? (Yes/No)6263Start with high-value, low-effort, low-risk data.6465**GATE: Present the prioritized data collection plan and wait for approval.**6667---6869## Phase 3: Build7071### Deliverables7273**1. Data Collection Inventory**74| Data Point | Source | Collection Method | Storage | Frequency | Privacy Level |75|-----------|--------|-------------------|---------|-----------|---------------|76| Page views | Website | GA4 | Google | Real-time | Low |77| Email signups | Forms | Zapier → CRM | CRM | Real-time | Medium |78| Revenue | Stripe | API sync | Spreadsheet | Daily | High |7980**2. Implementation Guide**81- Step-by-step setup for each data collection tool82- Integration connections (what feeds into what)83- Testing procedures to verify data is flowing8485**3. Privacy Compliance Checklist**86- [ ] Privacy policy updated to reflect data collection87- [ ] Cookie consent banner implemented (if required)88- [ ] Data processing records documented89- [ ] Data retention periods defined90- [ ] User data deletion process established91- [ ] Third-party data sharing disclosed9293**4. Data Quality Rules**94- Naming conventions for events and fields95- Validation rules for data entry96- Deduplication strategy for customer records97- Regular audit schedule (monthly data quality check)9899---100101## Phase 4: Polish102103### Data Stack Diagram104105Create a simple map showing: data sources → collection tools → storage → reporting tools.106107### 90-Day Implementation Roadmap108109- Month 1: Core tracking (website analytics, basic CRM)110- Month 2: Marketing attribution (UTMs, conversion tracking)111- Month 3: Customer data enrichment (behavior tracking, segmentation)112113---114115## Example 1: E-commerce Business116117**Priority data:** Traffic sources, conversion events, AOV, cart abandonment rate, customer purchase history, email engagement. Tools: GA4, Shopify analytics, Klaviyo.118119## Example 2: Service Business120121**Priority data:** Lead sources, consultation bookings, close rate, project profitability, client satisfaction scores. Tools: GA4, CRM (HubSpot free), Google Sheets for financials.122123---124125## Anti-Patterns126127- **Collecting everything** — more data means more privacy risk, more storage cost, and more noise. Be selective.128- **No privacy consideration** — collecting personal data without proper consent and documentation is a legal and financial risk.129- **Data silos** — customer data in 5 tools that do not talk to each other makes analysis impossible. Plan integrations from the start.130- **No naming conventions** — `email_signup`, `EmailSignup`, `email-signup`, and `signup_email` in different tools creates chaos. Standardize.131- **Collecting without reviewing** — data nobody looks at is worse than no data because it creates a false sense of being data-driven.132133---134135## Recovery136137- **User overwhelmed by options:** Start with 3 data points that directly answer their most important business question. Expand later.138- **Privacy concerns paralyze action:** Focus on aggregated, non-personal data first (page views, conversion rates). Add personal data collection only with proper consent mechanisms.139- **No technical ability:** Recommend no-code tools (Zapier, Google Forms, native platform analytics). Most essential data collection requires zero code.140- **Data already scattered:** Begin with an inventory of existing data and create a consolidation plan before adding new collection.
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