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Research
Ask a question in a sentence. Get a cited brief back, or a moderated study on any topic.
Scopeout is an intelligent platform for customer value. It studies your product and your users, finds what holds them back and what they would pay for, then designs, tests and ships the change, with your team or on its own.
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Upgrades are up 24% in two weeks. We’re on track for this quarter’s goal.
3.6%free to paid,
on track for the goal
on track for the goal
I’ll roll it to 50% of free users next.
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Reading your goal and the numbers behind itThe problem
AI made shipping fast. Knowing what your users need, and what they’ll pay for, is still slow.
Problems it solves
Run it.
Grow it.
Monetize it.
Activation, upgrades, retention, refunds, support load. Scopeout finds what holds each one back and drives the fix, with your team or on its own. These are examples. Bring your own goal.
Request a use case →
ActivationMore new users reach their first winactivation rate · first order · D1
EngagementUsers come back, and back againweekly active · repeat purchase · DAU/MAU
RetentionFewer leave, because the reasons get fixedday-30 retention · renewals · churn
ConversionEvery funnel step watched and fixedsignup, cart or search funnels
Cross-sell & upsellMore revenue from the customers you haveexpansion ARR · AOV · attach rate
Trial to paidPricing, packaging and paywalls that convertpaid conversion · subscription starts
New experiencesShip a new flow, feature or product line, with proofnew ARR · GMV · revenue per visitor
ReactivationWin back the users who leftrecovered MRR · reorders · reactivated users
Scopeout in one minute
01
One platform, eight capabilities
Everything you need, in one platform.
Each one is part of the same platform and shares what it learns about your product and your users. Open one to see it work.
Experience map · mobile checkoutLand100%Sign up82%Payment41%Done38%
Address46%
Analyze
Turn replays and tickets into experience maps and audits.
Design
Generate screens on your design system. Edit them inline.
Variant B → pull request #48212 tests passedPreview readyBehind a flagMerge
Build
Take the chosen variant to a pull request, behind a flag.
A / B · day 6 of 14A · 3.9%B · 5.8%97% significance
Test
A/B/n with guardrails, plus AI-moderated user interviews. Winners promote once they clear your bar.
Staged rollout · variant BGuardrailsholding · 3 / 3
10%Mon
25%Tue
50%today
100%needs approval
Publish
Roll winners out in stages, with one-click rollback.
Address step · conversion vs baseline bandbaseline bandrelease v4.12−6.2% · outside band
Monitor
Watch every funnel step and release against its baseline.
Run #118 · recordProblemaddress step −6.2%Evidence142 replays · 38 ticketsDecisionship variant BApproverpriyaOutcome+3.4% · promoted
Improve
Keep the record: problem, evidence, decision, outcome.
02
Playbooks
Proven playbooks, ready to run.
Each one turns a tested way to solve a common problem into a workflow on your product.
Find why a funnel step drops
“A step in our funnel is losing people. Find out why and fix it.”
Funnel · replays→Monitor→Research→Analyze→Fix shipped
Try it
Get new users to their first win
“New users stall before they get value. Find the blocker and test a fix.”
Replays · tickets→Journey map→Pain points→Variant→A/B test
Try it
Turn trials into paying customers
“Find the moment users are ready to pay and test the upgrade there.”
Funnel→Research→Design→A/B test→Ship
Try it
Stop users from leaving
“Retention is slipping. Rank the reasons people leave and fix the top one.”
Cohorts→Recordings→Causes→Fix→Test
Try it
Bring users back more often
“Find what makes people come back, and give them more of it.”
Usage→Segments→Hypothesis→Nudge→Test
Try it
Grow revenue per customer
“Find where customers are ready to buy more and test one offer.”
Orders→Moments→Offer→A/B test→Ship
Try it
Win back inactive users
“Find the users who went quiet, why they left, and what brings them back.”
Inactive users→Last action→Reason→Win-back→Test
Try it
Build what customers ask for
“Turn the most requested feature into a shipped, tested experience.”
Requests→Design→Code→Flag→Test→PR
Try it
03
FAQ
Questions, answered.
What does Scopeout do that my analytics, Figma and an AI coding tool don't?
Those tools each cover one step. Scopeout runs the loop between them: it notices the drop, finds out why with cited evidence, draws the fix on your design system, ships it behind a flag, tests it, promotes the winner and writes down what happened. You direct; it runs; the record stays.
What do I need to get started?
Anything. An idea in a sentence, a URL, a screenshot, a Figma file, a repo or a pile of tickets: start with whatever you have and Scout picks it up from there. Connect analytics, your repo, Figma and Slack when you want the full loop; each connector adds a step it can run.
How fast do I get something useful?
A cited research brief in under an hour on day one. A first variant behind a flag in the first week, once the repo and design system are connected. The weekly digest starts the first Monday.
What runs on its own, and what waits for a person?
Every step has a dial. Out of the box: research and analysis run after you approve the plan; design proposes variants for you to pick; build opens pull requests your engineers review; test promotes only past the bar you set; publish waits for a named approver. Turn any of these up as trust grows.
Can it ship something bad to production?
No change reaches users without a flag, a guardrail and a person. Tests stop on a guardrail breach (refunds, errors, support volume), rollouts go out in stages, and any change rolls back in one click. Nothing merges on its own.
Where does the code go, and who reviews it?
Into your repo, as a normal pull request with tests and a preview link, written in the stack and conventions the repo already uses. Your engineers review and merge it like any teammate's PR.
How does it use our design system?
Connect Figma or Storybook and Design generates on your components and tokens, sized to real content, so what the team reviews is what ships. Edit inline or send it to Figma and back.
How does it decide what to work on?
From the goal you give it and from your product model: what your users do by segment and what has worked for whom. It proposes loops ranked by expected lift with the evidence attached; you approve, reorder or drop them.
What is "the record", and who can see it?
Every run writes problem, evidence, decision, approver and outcome as a record in Scopeout, linked to the replays, tickets and PRs behind it. Anyone in your workspace can read it; roles decide who can approve. It exports to Notion, Confluence or PDF.
Is our data used to train models? Where does it live?
Your data is used only for your product and never to train models for other customers. It is encrypted at rest in Scopeout's cloud; enterprise plans add private deployment, SSO and a full audit trail.
What does it connect to?
Analytics (GA4, Mixpanel, Amplitude), support (Zendesk, Intercom), design (Figma, Storybook), code (GitHub, GitLab), docs and chat (Notion, Confluence, Slack), and a browser agent for anything with a URL.
What about a product with years of history?
That is where it does best. It learns your product from what already exists (code, docs, tickets, past experiments) so the first hypotheses come from your evidence, not a blank page.
What does it cost?
Free to try, no credit card, cancel any time. Paid plans scale with the number of runs. Enterprise adds private deployment and SSO; contact us for that.
Stop running the business. Start directing it.
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