Attribution
8 min read
Where did that sale actually come from?
Trace a sale back to the source, page, and session that created it without guessing from payment data alone.
The question
A sale appears in your dashboard. The useful question is not only how much it was worth. The useful question is what caused it.
Payment tools can tell you that money arrived. They rarely tell you which source introduced the buyer, which page convinced them, or which session finally pushed them over the line. That is the gap attribution is meant to close.
Start from revenue
Begin with the transaction, not the traffic chart. A visitor path only matters when it changes a business outcome: a purchase, subscription, upgrade, renewal, or refund.
From there, work backward through customer, session, source, landing page, campaign, and the events before purchase. This keeps the investigation anchored in money instead of pageviews.
The walkthrough
Open Attribution and sort sources by revenue. Click the source that produced the sale, then inspect the buyer path tied to that transaction.
Do not stop at the source label. The next action usually lives one layer deeper: the landing page, campaign, referrer, pricing page, goal event, or checkout session.
Attribution
Last 30 daysRevenue
$37,420
Customers
142
Best source
Organic
Sort by revenue first
Open the source row for session context
1. Find the revenue source
Use the revenue column before traffic volume so the highest-value source is visible first.
2. Open the detail
Review the landing page, campaign, and session context tied to the transaction.
3. Compare nearby events
Look for signup, checkout-start, demo, or goal events that explain the path.
4. Separate introduction from closing
Check whether the source created the first touch or simply appeared right before checkout.
What to check
Look for repeated patterns across sales, not one lucky story. One buyer from a podcast is interesting. Ten buyers who first discovered you from the same podcast and later purchased after visiting pricing is a channel signal.
Also check whether direct traffic is hiding prior demand. A buyer may return directly to purchase after discovering you from search, email, or a partner link.
1. First touch
The source that introduced the buyer. Use it for acquisition and awareness decisions.
2. Last touch
The source or session closest to purchase. Use it for conversion and retargeting decisions.
3. Landing page
The first page that set expectations. Poor message match often shows up here.
4. Revenue event
The payment-backed outcome. This is the reason the path matters.
Common mistakes
The biggest mistake is treating the nearest event as the cause. A checkout click did not create demand. It only finished the path.
The second mistake is treating every unattributed or direct sale as unknowable. Often the context exists earlier in the visitor history, before the final purchase session.
1. Over-crediting checkout
Checkout events show intent, but the source that created the buyer may sit much earlier.
2. Ignoring assists
Email, retargeting, and direct visits may close demand that another source created.
3. Chasing tiny samples
Use individual paths to learn, then wait for repeated patterns before shifting budget.
Decision framework
Scale a source when it repeatedly creates first-touch buyers and those buyers convert into payment-backed revenue. Improve a source when it attracts interested visitors who stall before checkout. Treat it as an assist when it mostly appears late in journeys started elsewhere.
The point is not perfect certainty. The point is enough continuity to choose the next growth action with confidence.
Rule of thumb: scale sources that create new buyers, not just sources that appear nearest to checkout.
Try it in your data
Open Attribution to connect recent revenue back to sources, pages, campaigns, and sessions.
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