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samuelgabrielsikorjak-sys
samuelgabrielsikorjak-sysCOMMUNITY
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attribution

Interpret attribution models and reconcile conflicting conversion data across marketing platforms.

Updated Jul 23, 2026
Search Tags:#marketing analytics#attribution#conversion tracking#posthog#first-party data#incrementality#media mix modeling
One-click install
npx skills add https://github.com/samuelgabrielsikorjak-sys/techscope-website --skill attribution-samuelgabrielsikorjak-sys
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: attribution
Source: https://github.com/samuelgabrielsikorjak-sys/techscope-website/tree/main/.claude/skills/marketingskills-main/skills/attribution
Command: npx skills add https://github.com/samuelgabrielsikorjak-sys/techscope-website --skill attribution-samuelgabrielsikorjak-sys

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Marketers lose budget to channels that look good in one dashboard and terrible in another, because Google, Meta, GA4, and the CRM each report different conversion numbers for the same sales. This Skill helps you choose and interpret attribution models, reconcile conflicting sources, and instrument first-party attribution when you control the site or app. ## Core Features & Use Cases - Model interpretation: Compare first-touch, last-touch, linear, time-decay, position-based, and data-driven attribution, and understand how each model distorts credit for long or short sales cycles. - Source reconciliation: De-duplicate overlapping platform claims against a single source of truth (CRM or backend), read directional trends, and use self-reported surveys and incrementality tests as tiebreakers. - First-party instrumentation: Stitch anonymous browsing to conversions using identify/merge calls, metadata passthrough, and webhooks for conversions on third-party domains like SavvyCal or Stripe Checkout. - Use Case: Your Google Ads reports 50 conversions, Meta reports 40, GA4 says 60, and your CRM shows 35 deals. Use this Skill to establish the CRM as the source of truth, explain each platform's bias, and deliver an honest budget allocation with confidence levels. ## Quick Start Ask the assistant to reconcile your conflicting conversion numbers across Google Ads, Meta, GA4, and your CRM and recommend which attribution model fits your sales cycle.

Frequently Asked Questions about attribution

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

FAQPage Schema
How do I reconcile different conversion numbers from Google Ads, Meta, and GA4?▼

Pick one source of truth for the conversion count, usually your CRM or backend where revenue is real, and de-duplicate platform claims against it. Never sum platform-reported conversions, since each platform claims credit for the same sale; read directional trends instead of absolute matches.

First-touch vs last-touch attribution: which model should I use?▼

Neither in isolation. Show first-touch and last-touch side by side, because the gap between them reveals how demand is created versus closed. For long B2B cycles, position-based attribution is a defensible primary model, paired with self-reported surveys.

How do I track conversions that happen on a third-party domain like Calendly or SavvyCal?▼

Append the visitor's anonymous distinct_id to the outbound booking link via the tool's metadata passthrough, then merge it back in the webhook with an identify call plus a conversion event. Only smuggle anonymous ids and fail closed when identity is ambiguous to avoid corrupting profiles.

Why does Meta report high ROAS but my revenue is not growing?▼

Platform-reported ROAS is inflated by self-crediting, view-through conversions, and generous attribution windows, so it is not incremental ROAS. Run an incrementality test such as a geo holdout or on/off test to measure true lift, and use incremental CPA to drive budget decisions.

Is a large share of direct traffic a good sign for my marketing?▼

Direct is a junk drawer of stripped referrers, dark social, and dropped tracking, not a real channel. A large direct share usually means your top of funnel is working but under-measured; use self-reported attribution surveys to surface the hidden sources.

When should I use MMM instead of multi-touch attribution?▼

Use MMM when you have material multi-channel spend including offline channels like podcasts or TV, plus two to three years of weekly data. MTA handles day-to-day tactical optimization, while incrementality tests validate what MMM and MTA claim.

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