A working hypothesis template for A/B tests and product experiments. Get a structured If-Then-Because statement you can plug into your experiment tracker, with the supporting metrics and decision rule attached.
A hypothesis you can fail
Falsifiable by design, so the result is unambiguous either way.
Guardrails, not just a win metric
Catches harm to retention, latency, or revenue before it ships.
Feasibility before you build
A sample-size estimate that tells you if the test can even run.
A feature change, a UX tweak, a copy variation, or a fuller PRD all work as input. The clearer the change and the expected behavior shift, the sharper the hypothesis the template produces.
The AI fills the If-Then-Because slots with your specifics: the experiment intervention (If), the metric movement (Then), and the causal reasoning (Because). Falsifiability is built in, so the hypothesis is testable, not aspirational.
The hypothesis arrives with its supporting parts: primary metric, guardrail metrics, and a decision rule for what to ship. Drop it into your experiment tracker or paste into a doc.
The hypothesis template uses the falsifiable If-Then-Because form so the result of the experiment is unambiguous, not "we learned something."
Every hypothesis comes paired with the one metric that decides the experiment, tied to the change you are testing rather than a vanity number.
The template surfaces what could go wrong (retention drop, latency spike, revenue loss) so a winning treatment that hurts elsewhere does not ship.
A clear "ship if X, hold if Y, kill if Z" rule travels with the hypothesis, so the post-test conversation is short and based on the rule you set up front.
Generic templates give you blank slots like "If __, then __ because __" and leave the writing to you. This template fills the slots from your experiment context, attaches the right metrics, and adds a decision rule, so the output is ready to use.
If-Then-Because is the standard falsifiable hypothesis form used by experimentation teams. "If we change X, then metric Y will move by Z because mechanism W." It forces clarity on the intervention, the expected effect, and the causal mechanism so a result actually means something.
Yes. 2 free hypothesis generations, no sign-up required. Sign in with Google for unlimited access and 30 expert document reviews.
Yes, but it will name the gap. If the input does not state a measurable outcome, the template flags the assumption and proposes a metric to consider, rather than inventing one silently.
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Pick what fits. Start with one.
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Customer Feedback AnalyzerPaste raw customer feedback from support tickets, NPS surveys, app reviews, or user interviews. SPM clusters themes, scores severity, and turns scattered complaints into a prioritized action plan with owners and success metrics.
Problem Statement GeneratorPaste your rough idea or observation. SPM transforms it into a validated, quantified problem statement with root cause, affected users, and measurable impact.
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Product ValidationPaste your feature idea, product concept, or pitch. SPM surfaces the assumptions you are betting on, ranks them by risk, and builds a validation plan with the cheapest test for each one. Find out what could be wrong before you build it.
Feature to Press ReleasePaste your feature description. SPM writes an Amazon-style working-backwards press release with a customer-benefit headline, a problem and solution narrative, executive and customer quotes, and a call to action. Pressure-test the value before you build.
PRD to Release NotesPaste your PRD or feature list. SPM turns it into customer-facing release notes that lead with the benefit, group changes into New Features, Improvements, and Fixes, and end with a clear next step.
PRD to Test CasesPaste your PRD. SPM generates structured acceptance test cases covering every acceptance criterion, happy path, edge case, and failure mode. Designed for PMs who own the definition of done.
Interview Notes to Job StoriesPaste raw user interview notes. SPM extracts structured job stories using the JTBD framework: clear situation triggers, problem-focused motivations, and grounded outcomes.