Analytics

    Multi-Touch Attribution

    Term #214

    An attribution model that gives credit for a conversion to multiple marketing touchpoints along the customer journey. Includes: linear (equal), time-decay (more weight to recent), and data-driven (AI).

    In practice

    A customer saw a Facebook ad → searched Google → got an email → bought directly. Who 'won'? Last-touch: the email. First-touch: Facebook. Multi-touch: everyone. Multi-touch gives a more realistic picture — but is more complex to manage.

    Common misconception

    'Multi-touch is the truth.' Multi-touch is more accurate than last-touch — but still imperfect. Post-iOS 14, pixel data is partial. Cross-device attribution is missing. Dark social isn't measured. No attribution model is perfect — multi-touch is the best of what's available.

    How to fix it

    Multi-touch not driving decisions? (1) Pick one consistent model (data-driven in GA4 if you have enough conversions), (2) Compare against MER as a sanity check, (3) Don't try to be too precise with attribution — decide on 80% accuracy, not 95%.

    Example

    Running store: last-touch → 85% of credit went to Google Paid Search. Multi-touch (time-decay) → Facebook 28%, Google 45%, email 18%, direct 9%. Change: increased Facebook budget that had been deemed 'unprofitable' under last-touch. Overall CAC fell 18%.

    Priority

    Data-driven attribution in GA4 is the recommended setup. Requires 300+ conversions/month. Below that, use linear attribution. Don't invest in advanced attribution tools until you have 500+ conversions/month.

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