Attribution & Tracking
Attribution Window Discrepancy Estimator
The Attribution Window Discrepancy Calculator explains why Meta and Shopify show different conversion counts by modeling the effect of their different attribution windows. It returns the raw discrepancy and percentage, an expected range based on the window ratio, which platform to trust, the conversions and revenue you may be missing from a window that is too short, and the optimal window length for your industry. The result demystifies the gap between platform and store numbers.
Who it's for: DTC marketers confused by Meta reporting more or fewer conversions than Shopify who want to know which number to trust and how to set their windows.
How the Attribution Window Discrepancy works
You enter Meta conversions, Shopify orders, the Meta attribution window, the Shopify attribution window, your average order value, and your industry. The tool calculates the absolute discrepancy and its percentage, then derives an expected range using the ratio of the two windows so you can tell whether Meta's number is plausible or out of bounds.
If Meta sits inside the expected range the platforms are considered aligned; if Meta is above the range it is likely over-attributing because of a longer window. When Shopify shows more orders than Meta, the difference becomes a missing-conversions estimate, multiplied by AOV to show the revenue your short window may be failing to attribute.
The calculator maps an industry-specific sales-cycle distribution (what share of conversions land by day 1, 7, 14, and 28) and recommends an optimal window, for example 14 days for ecommerce and fashion or 28 days for B2B. A platform comparison table shows how Meta, Google, TikTok, and Shopify each treat windows, and discrepancies over 30 percent are flagged critical.
The formula
Discrepancy = absolute value of (Meta conversions - Shopify orders). Discrepancy % = (discrepancy / Shopify orders) x 100. Expected range uses the window ratio (Meta window / Shopify window) applied to Shopify orders. Missing revenue = max(0, Shopify orders - Meta conversions) x AOV.
Frequently asked questions
Why do Meta and Shopify count conversions differently?+
They use different attribution windows and methods. Meta defaults to 7-day click plus 1-day view and attributes on the click or view date, while Shopify often uses a 30-day default and records the actual order date. A longer window captures more delayed conversions and view-through credit, so the two systems will rarely match exactly.
Which platform should I trust when they disagree?+
For total revenue and order counts, trust Shopify because it records actual transactions. For understanding ad-driven performance you can use Meta, but interpret it through the expected range: if Meta is far above what the window ratio predicts, it is likely over-attributing, and if it is below your Shopify count, your window may be too short to capture delayed buyers.
What is the optimal attribution window for my business?+
It depends on your sales cycle. Fast-moving categories like fashion and beauty convert most buyers within about 14 days, so a 14-day window captures nearly all conversions, while B2B and considered purchases can take up to 28 days. The calculator recommends a window per industry based on how quickly conversions accumulate in that vertical.
How does a short window cost me revenue?+
If your window closes before customers finish a longer consideration cycle, those late conversions go unattributed, so the channel looks weaker than it is and you may cut budget that is actually working. The missing-conversions and missing-revenue figures estimate that uncredited demand using the gap between your Shopify orders and Meta's count multiplied by AOV.