Conversion & attribution
What is Attribution modeling?
The rules that decide which touchpoints get credit for a conversion when a customer interacted with several channels before converting.
Definition
Attribution modeling is how credit for a conversion is divided across the touchpoints a customer saw — the ad they clicked first, the email they opened, the search they made last. The model is the rule set: last-click, first-click, linear, time-decay, or data-driven.
Different platforms use different default models and lookback windows, which is the structural reason two tools rarely agree on who "caused" a sale.
Why it matters for agencies
Attribution decides where a client’s budget goes. A last-click model starves the upper-funnel channels that created the demand; a data-driven model spreads credit more realistically but is harder to explain to a client.
Agencies have to both choose sensible models and explain the discrepancies between platforms — because a client who sees Meta claim 40 sales and GA4 claim 25 will ask which is "real."
Attribution modeling in Phloz
Phloz doesn’t pick a model for you, but it makes the inputs auditable: which conversion actions exist, which platforms they report to, and whether the server-side and offline paths that data-driven models depend on are actually wired up.
Frequently asked questions
- Which attribution model should agencies use?
- For most agency clients, the platform’s data-driven model is the sensible default — but the real win is consistency and a clear explanation to the client of why platform numbers differ. The model matters less than the honesty about its limits.
- Why is attribution getting harder?
- Third-party cookie loss, ITP, and consent gating shrink the cross-site signal models rely on. The compensating moves — server-side tracking, enhanced conversions, offline import — are exactly the infrastructure agencies now have to maintain.
Related terms
Other tracking-infrastructure concepts agencies run into alongside this one.
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