Know what your ads drive. Back the ones that work.
Prove what's actually driving conversions. Apply it across every campaign. Know which channels to scale and which to cut. The full measurement workflow, without the data science team or the enterprise contract.
No account. No data required. First result in under 5 minutes.
From the sample test
The platform reported
£3.56
per conversion
Holdout measured
£8.87
per incremental order
The platform claimed 18,000 conversions. 7,218 of them were incremental. Every figure on this page comes from running that test in the tool.
This is what a real answer looks like.
The result page, running the sample dataset. 8 weeks, 12 UK regions, 5 of them held out.
"What would we lose if we cut this budget?"
Every performance marketer gets asked. Most can't answer with a number. Holdout gives you a measured, defensible incrementality figure. When the question comes, you're ready.
Three tools, one loop
Use them independently or as a complete measurement workflow.
Test designer
Know which regions to hold out, whether your test has the power to detect real lift, and how long to run. Before you commit any budget.
Design a test →
Post-test analysis
Get a measured, defensible lift number with confidence intervals. Not a platform estimate.
Analyse results →
Incremental reporting
See what every campaign actually costs per real conversion. Compare channels on a level playing field. Move budget to what actually converts.
See real CPIC →
From question to defensible number
The full measurement workflow, start to finish.
Design your test
Upload your historical conversion data by geo. Holdout finds the best holdout regions, tells you how long to run, and shows what lift you can detect.
Run your campaign
Exclude the holdout regions from your ads. Everything else runs as normal. No data science team required.
Measure the lift
Upload your post-test data. Holdout measures the lift your campaign actually drove and gives you a confidence interval. Not a platform estimate.
Apply it to every campaign
Take your test result and apply it across every campaign. See what things actually cost. Know which channels to scale and which to cut.
Will a test work for you?
Two numbers decide whether a geo test can give you a clear answer: your total order volume, and how much of it the channel you want to test claims.
Use the conversions your ad platform reports for that channel.
Based on simulations of UK regional sales data. Your exact threshold depends on how your sales spread across regions. The free designer checks that with your real data.
Simple, transparent pricing
Start free. Upgrade when you're ready to go further.
Free
forever
- Test designer
- Power analysis & MDE curves
- Platform setup checklist
- Test-end reminder email
Pay per test
one payment, one complete test
- Everything in Free
- One complete test: design, activate, run, analyse
- Google Ads connected, orders from Shopify or CSV
- Holdout applied to your Google Ads account for you
- Post-test analysis with measured lift and CPIC
Growth
billed monthly, unlimited tests
- Everything in Pay per test
- Unlimited tests on supported platforms
- Always-on reporting, calibrated by your experiments
- Your numbers reconciled against platform-claimed results
- Per-channel incrementality library
Running tests for clients? Ask about an agency plan →
Presenting at Google Measurement Summit: triangulation of attribution, experimentation and MMM
Built by a practitioner
Proper measurement. Without the price tag.
I'm Jed Wrigley, a senior data scientist. I've spent years watching proper measurement teams get real answers out of marketing data. The brands that invest in it know what's working. The ones that don't are guessing.
I built Holdout to make that accessible without the headcount. It runs a real controlled experiment on your spend. Not a model, not a guess.
I come from both sides: performance marketing and data science. I know what the numbers mean and I know what the marketing team needs to hear. I've spoken on marketing measurement at Google events in London and Tel Aviv.
From question to defensible number.
Start free.
No data team. No enterprise contract. No CSV required to get started. Design your first geo test in under 5 minutes.
Your ads drove 11% more orders.
Your dashboard showed £3.56 per conversion. The experiment measured £8.87 per incremental order. Compare that against your target cost per order.
Your real cost per order
£8.87
The platform's cost per conversion
£3.56
Add the conversion value the platform claimed and a revenue column in your data to see the rest of the correction.
Incremental orders
+7,218
over 8 weeks (+902/week)
Lift
10.6%
range 9.6% to 11.6%
Of what the platform claimed
40%
range 36% to 44%
Spend in the window
£64,000
on the tested campaigns
What happened, against what would have happened
The control blend tracks your treatment regions before the test starts. After the holdout goes live, the gap between the two lines is the effect. The dotted line adds what the platform claimed it delivered, averaged across the test weeks.
Apply this to everything you spend
Correct every campaign row with this measured rate, and keep it corrected between tests.
Test another channel
One rate covers one channel. Brand search, shopping and prospecting each behave differently.
How it was measured
Synthetic difference-in-differences. A blend of your holdout regions is fitted to your treatment regions before the test, then used as the counterfactual after it.
How closely the blend tracked before the test
93%. Above 90% is a strong fit. Below 70% means the result is directional only.
What the range was measured against
Measured against how much your own regions drift in windows where nothing changed, taken from your history before the test.
Precision achieved
Plus or minus 1.0 percentage points around the estimate.
Test window
8 weeks after the holdout went live, against 26 weeks of history before it.
What the platform claimed
18,000 conversions on £64,000 of spend for the tested campaigns in this window.
What this assumes
That nothing else changed in your treatment regions during the window, and that the tested channel's spend and claimed conversions sat almost entirely in those regions because it was switched off in the holdout.