Chrome Privacy Sandbox Attribution Loss Forecaster

Estimate how Chrome's Privacy Sandbox rollout will affect your attributed conversions and paid media efficiency. Provide baseline conversions, expected attribution loss, average order or lead value, monthly retargeting spend, and the share of paid media tied to retargeting to surface lost revenue, adjusted ROAS, recommended budget shifts, and the first-party uplift required to stay whole.

Average Chrome-attributed conversions before third-party cookie deprecation.
Percent of conversions you expect to lose as browser signals decay or modeling lags.
Revenue or weighted lead value per attributed conversion in U.S. dollars.
Current monthly media spend dedicated to retargeting campaigns in Chrome.
Optional — defaults to 35.00%. Used to size the total paid media budget when computing uplift targets across channels.

Use for directional planning only. Validate assumptions against live platform diagnostics, incrementality testing, and finance forecasts before reallocating spend.

Examples

  • Scenario 1 – Large ecommerce program: 1,200 baseline conversions, 18.00% loss, $320.00 value, $23,000.00 spend, 35.00% share ⇒ Lost conversions: 216 (18.00% of baseline revenue). Lost revenue: $69,120.00. Adjusted conversions fall to 984, pushing ROAS down to 13.69 from 16.70. Reallocate $4,140.00 of retargeting spend and target a 105.18% first-party uplift across paid media to stay level.
  • Scenario 2 – Lead generation campaign: 650 baseline conversions, 12.00% loss, $180.00 value, $9,000.00 spend, 40.00% share ⇒ Lost conversions: 78 (12.00% of baseline revenue). Lost revenue: $14,040.00. Adjusted conversions fall to 572, pushing ROAS down to 11.44 from 13.00. Reallocate $1,080.00 of retargeting spend and target a 62.40% first-party uplift across paid media to stay level.

FAQ

How should I treat modeled conversions from ad platforms?

If you expect Google Ads or other platforms to recover a portion of lost conversions with modeling, reduce the loss percentage accordingly. The calculator assumes lost conversions are not replaced elsewhere unless you change the loss input.

What retargeting share should I use?

Use retargeting spend divided by your total paid media spend. It helps translate lost revenue into a paid media uplift target so you know how much incremental performance must come from first-party tactics or new acquisition budgets.

Can I model staged Privacy Sandbox rollouts?

Yes. Run separate scenarios with different loss percentages to simulate phased cookie deprecation, then compare the budget shifts and uplift targets over time.

How do I use the uplift target in practice?

Aim to generate the indicated percentage of additional revenue across all paid media through first-party audiences, server-side tagging, creative refreshes, or measurement upgrades so total revenue stays flat despite attribution loss.

Does the tool cover Safari or Firefox cookie restrictions?

No. It isolates Chrome Privacy Sandbox impacts. Run a separate scenario with your Safari or Firefox baselines if you want to quantify those effects alongside Chrome.

Additional Information

  • Lost conversions equal baseline conversions multiplied by the expected attribution loss percentage.
  • Lost revenue multiplies lost conversions by your average order or lead value to show cash at risk.
  • ROAS comparison divides revenue before and after the loss by the same retargeting spend to highlight efficiency drag.
  • Recommended budget shift mirrors the lost share of retargeting spend, while the uplift target applies that revenue gap across the entire paid media budget.
  • All monetary outputs appear in U.S. dollars ($) and ROAS is expressed as revenue divided by spend for clarity in reporting.

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