Purpose #
This article explains how Shopstars approaches attribution in analytics and advertising. It covers what attribution is, the main models used, why different platforms report different results, and how Shopstars interprets the data to make informed decisions. Clients should use this as the reference for understanding how conversions are credited and why reports may differ across systems.
What Attribution Means #
Attribution is the process of assigning credit for a conversion (such as a purchase or lead) to one or more marketing touchpoints. A customer might interact with multiple ads and channels before purchasing. Attribution determines which interaction gets the credit. Without a clear attribution framework, it is impossible to know which campaigns are truly driving results.
Common Attribution Models #
Last-Click Attribution
- The final interaction before a conversion receives 100% of the credit.
- Simple and easy to interpret, but it undervalues top-of-funnel activities.
- Example: A user clicks a Google Ad, then later buys after clicking a retargeting ad on Meta. Under last-click, Meta gets full credit.
First-Click Attribution
- The first interaction receives all the credit.
- Useful for understanding what initiated a customer journey, but it ignores retargeting and closing ads.
Linear Attribution
- Every touchpoint in the journey receives equal credit.
- Example: If a customer saw three ads before purchasing, each is credited with one-third of the conversion.
Time-Decay Attribution
- Touchpoints closer to the conversion receive more credit.
- Good for recognizing that final interactions often play a larger role than initial discovery.
Position-Based (U-Shaped) Attribution
- The first and last interactions receive the majority of the credit, with the middle touchpoints receiving the remainder.
- Useful when both discovery and closing ads are critical.
Data-Driven Attribution (DDA)
- Uses machine learning to assign credit based on how each touchpoint contributed to conversions.
- Available in GA4 and Google Ads, and increasingly used as the default.
Platform Differences #
Each platform applies attribution differently, which explains why conversion numbers often do not match:
- Meta Ads Manager defaults to a 7-day click, 1-day view attribution window.
- Google Ads offers both last-click and data-driven attribution, with a 30-day window for most conversions.
- GA4 defaults to cross-channel data-driven attribution but can also show last-click views.
- Shopify attributes sales based on last non-direct click.
Because of these differences, Shopstars never relies on a single platform in isolation. Instead, results are interpreted across multiple systems.
How Shopstars Interprets Attribution #
Shopstars applies a comparative approach:
- Review platform-specific conversions to measure performance within each ecosystem (e.g., Meta ROAS, Google CPA).
- Validate against GA4 and Shopify to understand the blended impact across channels.
- Identify patterns such as Meta being stronger at top-of-funnel discovery while Google captures last-click conversions.
- Recommend budget allocation based on cross-platform contribution rather than single-source reporting.
Example Scenario #
- Meta reports 100 purchases attributed to ads.
- Google Ads reports 80 purchases.
- GA4 shows 130 total purchases across all channels.
- Shopify shows 140 orders overall.
Shopstars interprets this by recognizing overlap: some customers touched both Meta and Google before converting. Rather than choosing one platform as “correct,” the blended attribution is considered, and budget allocation decisions are based on efficiency across the funnel.
Client Responsibilities #
Clients should understand that discrepancies between reports are normal and not evidence of incorrect tracking. Attribution models are interpretive frameworks, not exact accounting. Clients are encouraged to review weekly reports in Basecamp where Shopstars explains attribution context and budget implications.
Summary #
Attribution models define how conversions are credited across marketing touchpoints. Shopstars works with multiple models—last-click, first-click, linear, time-decay, position-based, and data-driven—and interprets them across platforms. By comparing Meta, Google, GA4, and Shopify data, Shopstars provides a balanced view that informs smart budget allocation and long-term growth strategy.
