The elapsed time between an affiliate-referred click and the resulting conversion (purchase, sign-up, or other defined action). Time lag is a key input for setting appropriate affiliate cookie windows and for understanding the true purchase consideration cycle for a product category. How time lag data is used: affiliate networks provide time-lag reports that show the distribution of click-to-conversion times across a program's historical conversions; for example, a time-lag report might show that 50% of conversions occur within 3 days of the click, 75% within 10 days, and 90% within 45 days; the 90th percentile of the time-lag distribution is the recommended minimum cookie window — setting the cookie window at the 90th percentile ensures attribution for the vast majority of affiliate-influenced conversions. Category patterns: high-impulse categories (food, beauty consumables): median time lag of 1-2 days; 90th percentile of 7-10 days. Standard e-commerce (fashion, home décor): median time lag of 5-10 days; 90th percentile of 20-30 days. High-consideration categories (electronics, furniture): median time lag of 14-30 days; 90th percentile of 45-90 days. Financial products: median time lag of 30-60 days; 90th percentile of 90-120+ days. Why time lag matters beyond cookie windows: time lag analysis reveals whether affiliate content is driving immediate purchase decisions or long-consideration purchases; products with long time lags have a larger gap between affiliate traffic and affiliate revenue recognition, which affects cash flow forecasting and program performance reporting; comparing time lag across publisher types reveals whether different publisher audiences have different consideration cycles (a coupon publisher's audience may have shorter time lag than a content blog's audience because coupon seekers have already made their purchase decision).
Related Resources