Analytics Tracking
SkillDatabases & dataUse when auditing, planning, or debugging marketing measurement, conversion tracking, GA4, GTM, UTMs, pixels, CRM attribution, funnel reporting, or dashboard trust.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Analytics Tracking skill
What this skill tells your AI
The instructions your AI receives, as published by infinite-labs-ai/infinite-skills in skills/analytics-tracking/SKILL.md and read by ahel’s review.
Check whether marketing tracking is reliable enough to make decisions about budget, funnel performance, and growth.
Start With Decisions
Ask what decisions the data is supposed to support:
- Which channel gets more budget.
- Which campaigns convert.
- Which pages or steps leak users.
- Which leads become revenue.
- Which lifecycle messages work.
- Which experiments win.
Tracking is not trustworthy because tags fire; it is trustworthy when the decision chain is complete.
Inspect The Chain
Trace:
- Source capture: UTMs, referrer, click IDs, campaign naming.
- Event capture: page views, leads, signups, purchases, activation, qualified lead, revenue.
- Identity: anonymous to known user, lead to account, account to deal.
- Destination: analytics, ad platforms, CRM, warehouse, dashboards.
- Definitions: what counts as a conversion, lead, MQL, opportunity, customer.
- Consent and privacy boundaries.
- Reconciliation: totals across systems and expected gaps.
Flag Trust Breaks
- Events fire but are not tied to the business outcome.
- Multiple systems define the same metric differently.
- UTMs overwrite or disappear.
- Test traffic pollutes reports.
- Duplicate conversions feed paid bidding.
- PII leaks into analytics or ad tools.
- Dashboards hide uncertainty.
- Offline revenue never connects back to campaigns.
Judge Data Confidence
For each decision, state:
- Trust level: high, usable with caveats, directional only, not usable.
- Known gaps.
- Acceptable uncertainty.
- Reconciliation owner.
- Next check that would raise trust.
Output
Tracking trust read:
[one paragraph]
Decision chain:
Question -> Required signal -> Source -> Destination -> Owner
Decision trust:
| Decision | Trust level | Known gaps | Acceptable uncertainty | Reconciliation owner |
Trust breaks:
| Break | Evidence | Decision affected | Fix | Priority |
Measurement plan:
| Event | Trigger | Parameters | Destination | Success criteria |
Naming rules:
- [UTM or event rule]
Reconciliation checks:
1. [check]
2. [check]
Privacy risks:
- [risk]
Signals
- GitHub stars
- 43
- Forks
- 4
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
analytics-tracking-infinite-labs-ai- Source
- github.com/infinite-labs-ai/infinite-skills