Click Tracking
Part of Affiliate fraud and attribution disputes
Identifying unusual click-to-sale patterns
Compare affiliate clicks, orders and click-to-sale timing in context, then inspect individual records before drawing conclusions.
To spot unusual click-to-sale patterns, compare similar traffic and periods, then inspect the orders behind a change. A high or low conversion ratio is an alert, not a fraud score. It may reflect buyer intent, a promotion, a placement change or a tracking problem.
Build a useful comparison
Choose a reporting period and state whether orders are grouped by transaction date or commissions by validation date. For each publisher, compare recorded clicks, tracked orders, approved orders and the time from click to purchase. Keep publisher type, placement, product mix and promotion dates visible. A content guide and a voucher placement may reach customers at different stages of a purchase.
Calculate tracked orders divided by recorded clicks only after checking how both measures are defined and that they cover comparable periods. Allow for orders still pending validation when comparing approved commissions. Compare like periods rather than treating a brief launch campaign and a quiet month as equivalent.
Inspect the change behind the ratio
- Timing:Are credited clicks clustered just before purchases? Review the placements and any earlier touchpoints the platform actually recorded.
- Volume:Did recorded clicks rise without a similar change in site visits or orders? Check the click source, landing destination and the definitions of each metric.
- Order outcomes:Were more affected orders later cancelled, returned or declined? Compare similar products and periods.
- Source:Do available referrer, publisher URL or voucher-code fields fit the activity the partner describes? A blank field is missing evidence, not proof of concealment.
Awin Classic's Transactions report documents fields such as the transaction identifier, publisher identifier, sale amount, commission, date and commission status, and its Touchpoints column shows the touchpoints within the user's path to purchase. Use the fields available in the account rather than assuming a complete customer history.
Steps to inspect unusual click-to-sale patterns
- Confirm reporting period and date grouping (transaction vs validation date)
- Compare clicks, tracked orders, approved orders, and click-to-purchase timing
- Check for clustering of credited clicks just before purchases
- Assess whether click volume increased without proportional site visits or order growth
- Review order outcomescancellations, returns, declines
- Verify referrer, publisher URL, or voucher-code fields match partner claims
Check orders and ask a focused question
Select affected orders and comparable orders outside the pattern. Record their order references, relevant click and purchase times, placements, landing destinations and commission status. Confirm the store orders before discussing publisher conduct. If the change began after a site release or integration change, investigate that timing.
Ask the publisher for the placement or traffic-source detail for the campaign and period in question. Preserve the original records. If a click appears to have displaced another partner's credit, first confirm the events and then apply the credit terms. Record whether the evidence points to a normal campaign effect, traffic-quality concern, tracking fault or an unresolved anomaly.
Key questions to ask when investigating click-to-sale anomalies
- Are the affected orders confirmed in the store before discussion?
- Was there a recent site release or integration change?
- Does the publisher provide placement or traffic-source details for the campaign?
- Is there evidence of displaced credit from another partner?
- Does the data suggest normal campaign effect, traffic quality issue, tracking fault, or unresolved anomaly?
