It is normal for the numbers in your Lumo reports not to match those in GA4, the Shopify admin, or your ad dashboards. Each tool measures different things and uses a different measurement method. This article explains why the numbers diverge, from the angles of attribution, measurement method, aggregation period, and how orders are handled.
It Is Normal for the Numbers Not to Match
Lumo's reports and other tools' numbers measure fundamentally different things, so it is normal for them not to match.
Lumo's reports aim to measure how much your LINE broadcasts contributed to revenue and outcomes. GA4, on the other hand, measures activity across your entire site over all channels, and the Shopify admin aggregates the orders that actually occurred. Lining up numbers from tools with different purposes will not make them identical.
A gap between the numbers is not itself a problem. What matters is understanding what each number counts and under what definition, and using each accordingly.
The Attribution Approach Differs
Lumo attributes revenue and outcomes starting from a via-LINE click, using last-click and a 5-day window. Other tools use different attribution models, so the numbers change.
Lumo's attribution rules are as follows:
- Only via-LINE touches are counted: An outcome with a click on a LINE link or QR code is treated as coming via LINE (LINE attribution). Non-LINE routes such as email, ads, and search are not eligible for attribution
- Clicks within 5 days before the order are eligible: Looking back up to 5 days before the date the outcome occurred, attribution happens when there was a LINE click in that window. Clicks earlier than 5 days are not eligible
- Attributed to the last click: When there are multiple clicks within the window, the outcome is assigned to the last click closest to it (last-click)
GA4 measures with its own attribution model that covers all channels. Both the channels it targets and the look-back period differ from Lumo. As a result, even for the same revenue, the amount assigned to LINE will not match. Understand that Lumo counts conservatively, focusing only on the contribution of LINE broadcasts.
The Measurement Mechanism Differs
Web conversion tracking measures outcomes in the same browser where the LINE link was clicked. The constraints of this measurement method also cause the numbers to diverge from other tools.
The main sources of divergence due to the measurement method are as follows:
- Only activity in the same browser is eligible: A friend's identifying information is saved in the browser where the LINE link was clicked. If someone clicks in the in-app browser inside LINE and later purchases in a different browser (such as on a PC), the outcome cannot be attributed to the same friend as is and is missed
- Email addresses can cover some of the gap: If you pass the purchaser's email address in
lumo.conversion(), outcomes on a different browser or device can also be matched. If you don't pass it, purchases in another browser are missed - Ad blockers have an effect: If a visitor uses an ad blocker or tracking-prevention feature, the measurement information may not be sent and the outcome may not be recorded
Because of these constraints, web tracking tends to come out lower than the actual outcomes across your whole site. Revenue attribution via the Shopify integration is based on ID linking between LINE friends and Shopify customers, so it does not depend on the browser and can measure purchases on another device. Even for the same LINE attribution, web tracking and the Shopify integration miss outcomes in different ways. Note that web conversion tracking is currently offered as a beta, so its measurement scope and accuracy may change with future improvements.
The Aggregation Period and Time Zone Differ
The cutoff-date basis and time zone differ by tool, so gaps appear when you slice by period.
- Time zone differences: When the time zone used as the aggregation basis differs by tool, an outcome near a date boundary may land on a different day. Comparing numbers around month-end and month-start makes this effect more likely
- Differences in the counting-date basis: Even within Lumo's reports, the Messaging dataset aggregates by click date, while the Conversions dataset aggregates by the date the outcome occurred. If someone clicks at the end of a month and orders the next month, the month it is counted in changes depending on the dataset
- Differences in reflection timing: Click and outcome data are reflected gradually after they occur. Right after they occur, the reflection is still in progress, and the numbers fall into line over time
Even when you think you are comparing over aligned periods, a difference in the cutoff basis produces a gap. When you compare, align the period and basis as closely as possible.
How Order Cancellations and Refunds Are Handled Differs
Because how cancellations and refunds are reflected differs by tool, revenue numbers diverge.
The Shopify admin shows the latest state, reflecting cancellations and refunds. Web conversion tracking, on the other hand, records an outcome at the moment it occurs, so an order that is later cancelled may remain as is. As a result, during periods with many cancellations, web-tracking revenue can look higher than the Shopify admin.
When you want to reconcile revenue strictly, also check the status of cancellation and refund reflection.
When You Compare Numbers with GA4
GA4 and Lumo differ fundamentally in the channels they measure and their attribution models, so the numbers do not match.
GA4 measures activity across your entire site over all channels and assigns conversions to each channel with its own attribution model. Lumo counts only the portion that LINE broadcasts contributed, using the definition of via-LINE, last-click, and a 5-day window.
- GA4's "LINE" or referral numbers and Lumo's LINE attribution do not match because their aggregation definitions differ
- GA4 measures around sessions and events, while Lumo measures outcomes starting from LINE clicks
- It is not a case of one being right and the other wrong. Use each according to your purpose
We recommend dividing their roles: use Lumo's numbers when you want to evaluate the contribution of LINE broadcasts, and GA4 when you want to see the channel mix across your whole site.
When You Compare Numbers with the Shopify Admin
The Shopify admin shows all orders, while Lumo's LINE attribution shows only the portion judged to have come via LINE, so the numbers look different.
Shopify admin revenue is the total of all orders regardless of source. Lumo's reports show a close figure for total Shopify revenue, but they diverge slightly due to differences in time zone and how cancellations are handled. On top of that, Lumo's LINE-attributed revenue is narrowed by the following conditions:
- Only orders with a via-LINE click within the 5 days before the order are eligible
- Only orders where a LINE friend and a Shopify customer are ID-linked are eligible for attribution. When linking has not progressed, LINE attribution comes out on the conservative side
As a result, comparing the Shopify admin's total revenue directly against Lumo's LINE-attributed revenue makes Lumo's number smaller. This is because it extracts only the portion LINE contributed, and it is correct behavior. As you progress ID linking, the range that can be attributed widens.
When You Use the Numbers Externally
When you use report numbers in internal or external reporting, also indicate which report and which definition the figures come from.
Lumo's attribution is an estimate based on its own definition of via-LINE, last-click, and a 5-day window. Even the same "revenue" means something different from the numbers in GA4 or the Shopify admin. Pulling out numbers alone for comparison invites misunderstanding.
When you use them externally, we recommend adding the definition, such as "Lumo's LINE-attributed revenue (LINE clicks within 5 days before the order, aggregated on a last-click basis)." When you're unsure how to interpret the numbers, ask Marketing Agent "How should I explain the numbers in this report?" and it will organize the key points into a proposal.