By Tangenix · Published 22 October 2026

How to measure your first-user acquisition experiments

Measure an acquisition experiment by connecting a specific audience, message and source to a useful product outcome. Record visits, signups and activation separately. A signup shows interest; activation means the person completed the core task you defined before the experiment. Use a consistent observation window and keep unattributed visits visible.

Define one experiment before sharing a link

Write down the audience, the problem, the message, the destination and the outcome. An illustrative experiment might invite independent designers to try an invoice reminder workflow. Define activation as completing a real reminder setup, rather than opening the dashboard. This example is a measurement exercise, not a Crany result.

Name your campaign links consistently

Google Analytics documents campaign parameters for identifying referring campaigns. Use utm_source for the source, utm_medium for the marketing medium and utm_campaign for the experiment. An optional utm_content value distinguishes versions. Keep spelling consistent so one source does not fragment into several rows.

For example: https://example.com/?utm_source=founder_newsletter&utm_medium=email&utm_campaign=invoice_reminder_test&utm_content=workflow_demo. This is an illustrative external campaign link. Do not place names, email addresses, customer IDs or private conversation text in campaign parameters.

Test the destination and your analytics reporting before using the link. A UTM parameter does not collect data by itself: the destination needs a working measurement setup. Respect the destination’s consent requirements and your published privacy commitments.

Download the experiment worksheet

Download the blank acquisition measurement CSV. Enter one row per experiment and observation window. Use the same definitions when comparing rows.

• Qualified visits: visits that match the audience and traffic definition you chose.
• Signups: accounts or registrations created during the observation window.
• Activated users: people who completed the predefined core task.
• Paid users: people whose payment succeeded, if payment is part of the experiment.
• Cost and time: actual cash spending and founder hours, recorded separately.

Calculate the rates with explicit denominators

Signup rate is signups divided by measured visits. Activation rate is activated signups divided by signups in the same cohort. Cash acquisition cost is campaign cash spend divided by acquired customers under your stated attribution rule. When the denominator is zero, record the rate as unavailable rather than zero or infinity.

An illustrative cohort has 40 measured visits, eight signups and two activated signups: a 20% signup rate and a 25% signup-to-activation rate. Those are arithmetic examples, not benchmarks. Small samples can change substantially after one additional person, so retain the counts beside the percentages.

Read the failure before changing the channel

Visits without signups suggest checking audience fit, promise and landing-page friction. Signups without activation suggest checking onboarding and the first useful task. Activation without repeat use suggests investigating whether the need recurs. These are investigation paths, not causal diagnoses; talk to users before deciding what failed.

What attribution cannot tell you

Someone may discover you in a conversation, return through search and sign up on another device. Consent choices, blocked scripts and copied links can leave gaps. Keep an “unknown” category and optionally ask how people heard about you. Do not count a referrer label as proof that one campaign caused the purchase.

Sources and editorial method

Tangenix prepared this original worksheet and worked example with AI assistance. The parameter definitions come from Google Analytics campaign URL documentation, consulted on 22 October 2026. The experiment design and diagnostic suggestions are editorial guidance, not vendor benchmarks.

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