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Documentation Index

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Attribution is the practice of determining which marketing touchpoints deserve credit for a conversion — and by how much.
Merchants using Upstack Analytics report finding 15–30% of their ad spend allocated to channels that appear profitable in-platform but underperform when measured with independent multi-touch attribution.

Why It Matters

Every ad platform marks itself as the hero. Meta claims the sale. Google claims the same sale. Klaviyo takes credit too. When you add up each platform’s reported revenue, the total exceeds your actual revenue by 2–3x. This is the double-counting problem — and it makes budget allocation guesswork. The root cause is that ad platforms use self-attributed, last-click models scoped to their own ecosystem. They can’t see the full customer journey, so they assign full credit to their own touchpoint. A shopper who clicked a Meta ad on Monday, a Google ad on Wednesday, and a Klaviyo email on Friday appears as three separate conversions across three dashboards. Independent attribution — measured from your own first-party data — eliminates double-counting. When you own the data pipeline from click to purchase, you can apply consistent models across every channel and allocate credit based on the actual customer journey, not each platform’s self-serving view.

How It Works

Upstack Analytics operates at the Understand stage of the data pipeline. It queries the identity-resolved, enriched event stream stored in your analytics warehouse to build a unified view of each customer’s journey. Attribution models determine how conversion credit is distributed:
  • First-touch — 100% credit goes to the touchpoint that originally acquired the customer. Useful for measuring top-of-funnel acquisition channels.
  • Last-touch — 100% credit goes to the final touchpoint before conversion. Mirrors how most ad platforms report by default.
  • Linear (multi-touch) — Credit is split equally across all touchpoints in the journey. Surfaces mid-funnel contributors that single-touch models ignore.
  • Time-decay (multi-touch) — Touchpoints closer to conversion receive more credit. Balances recency with full journey visibility.
Lookback windows control how far back Upstack searches for qualifying touchpoints. A 7-day window attributes purchases only to clicks within the past week. A 28-day window captures longer consideration cycles common in higher-AOV stores. Channel credit aggregates touchpoint-level attribution up to the channel level (Meta, Google, Klaviyo, organic, direct) so you can compare true ROAS and CPA across your entire marketing mix in a single view.

Key Terms

TermDefinition
Attribution modelA rule set that determines how conversion credit is divided among marketing touchpoints.
First-touch attributionAssigns all credit to the first interaction in the customer journey.
Last-touch attributionAssigns all credit to the final interaction before conversion.
Multi-touch attribution (MTA)Distributes credit across multiple touchpoints based on a weighting rule (linear, time-decay, position-based).
Lookback windowThe time period within which touchpoints are eligible for attribution credit.
ROAS (Return on Ad Spend)Revenue generated per dollar of ad spend — the primary efficiency metric for paid channels.

Analytics Dashboard Guide

Walk through the Upstack Analytics dashboard and its key reports.

Identity Resolution

Learn how Upstack ID builds the unified customer journey that attribution depends on.