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Product Outcomes and Metrics Workbench
Turn feature-based goals into user outcomes, precise success measures, and clear experiment decision rules.
$10.80
Product Outcomes and Metrics Workbench
Example session with this skill installed
CompassFlow: onboarding outcome design
All companies, observations, dates, customer quotes, and numerical values in this fixture are fictional simulation data. They do not describe a real company or a measured customer result.
Source packet
In a mature synthetic cohort of 500 newly eligible accounts, 200 completed a first verified workflow within 14 days of eligibility; 120 of those 200 repeated a verified workflow during days 15-28. The whole cohort has a complete 28-day observation window. A verified workflow means the authoritative workspace contains the requested record with required fields, not an assistant completion message.
The team proposes shipping three onboarding screens, adding an AI assistant, and building an adoption dashboard as its OKR. The decision is what behavior to prioritize over the next quarter. Support costs, retention impact, and intervention effects are unknown. Four of 10 research sessions contained uncertainty about required setup fields. The product has a manual setup route that remains available.
Buyer request
Replace the output-based OKR with one outcome objective and a focused metric set. Distinguish first-workflow completion, repeat rate among completers, and repeat outcome across all eligible accounts. Write numerator, denominator, eligibility, window, authoritative source, segment, and guardrail contracts. Label targets and experiment thresholds as proposed and state the decision they trigger.
- Read your context and instructions
- Compiled the product outcomes
CompassFlow — outcome objective and metric decision canvas
Synthetic example run. All account counts, research findings, and product facts are fictional simulation data from the supplied source packet. New targets, interventions, thresholds, and ownership roles below are proposals. No experiment or customer outcome has been produced by this document.
Recommendation and replacement OKR
Objective: Newly eligible accounts confidently complete a useful, correct workflow and return to complete another without losing access to the manual setup route.
Prioritize repeated verified value across all eligible accounts next quarter. Treat shipping screens, adding an assistant, and building a dashboard as candidate interventions and instrumentation, not objectives or evidence of success. Start by testing clearer required-field guidance against the current manual setup; an AI assistant has no demonstrated incremental benefit in this packet.
Proposed key result: Increase the share of all newly eligible accounts that complete a verified first workflow within 14 days and repeat a verified workflow in days 15–28 from the synthetic baseline
24% to 30%. This is an aspirational planning target, not a commitment or a predicted intervention effect. For another 500-account cohort, 30% would mean 150 qualifying accounts, 30 more than the baseline 120. That calculation explains the proposed materiality; it does not establish feasibility.
Use first-workflow completion to locate early friction and conditional repeat to understand what happens after first value. These are diagnostics of the same objective, not three unrelated goals. Commercial consequences and support cost are unknown; do not claim retention or revenue improvement.
Baseline: three distinct denominators
Source: one mature synthetic cohort of
500 newly eligible accounts, all with a complete 28-day observation window. Exact cohort dates and segment distribution are not supplied. Verified means the authoritative workspace contains the requested record with required fields; an assistant completion message does not count.
| Measure | Numerator | Denominator | Calculation | Interpretation |
|---|---|---|---|---|
| First verified workflow within 14 days | 200 accounts | 500 newly eligible accounts | 200 / 500 = 40% | How many eligible accounts reach first value on time |
| Repeat among first-workflow completers | 120 accounts | 200 accounts completing first workflow within 14 days | 120 / 200 = 60% | Conditional repeat among early completers, not whole-population success |
| First-and-repeat outcome across all eligible accounts | 120 accounts | 500 newly eligible accounts | 120 / 500 = 24% | How many accounts reach first value on time and then repeat |
Identity
40% × 60% = 24%, since the repeat numerator is a subset of the first-completion numerator in this cohort. The 300 accounts without timely first completion remain in the primary denominator. The 80 first completers without a qualifying repeat remain in the conditional denominator. Do not count a late first workflow alone as repeat, or assume nothing happened among the other 300 accounts beyond the supplied definition.
Four of 10 research sessions contained uncertainty about required setup fields. This is directional qualitative evidence, not a 40% prevalence estimate among all eligible accounts and not proof that extra screens or an assistant fix the problem.
Outcome and Metric Decision Canvas
| Owner | Horizon | Population | Decision cadence | Evidence confidence |
|---|---|---|---|---|
| Decision owner unknown; cross-functional Product/Design/Engineering/Data roles proposed | Next quarter; dates unknown | Newly eligible accounts, defined before enrollment; manual and assisted routes included | Weekly data-quality/safety review; outcome decisions only on mature 28-day exposure; quarter planning review | High fidelity to supplied aggregate arithmetic; low confidence in causal effects, segmentation, support cost, and commercial impact |
Objective, behavior, boundaries
Desired behavior: an account supplies the required setup information, creates the requested valid record in the workspace, and later performs another valid workflow. Immediate beneficiaries are newly eligible account users; support may also benefit, but that remains unmeasured. New guidance can add steps for experienced users; an assistant could introduce trust, latency, or correction work. Preserve the manual route and observe whether new friction displaces existing successful behavior.
Why now: the proposed next-quarter goal is currently an output list, while the cohort shows a large gap between eligibility and repeated value. Non-goals: maximize assistant usage, screen views, dashboard visits, raw workflow attempts, or claimed completion messages; infer retention gains; force all accounts through one route.
Foundational pushback: required-field confusion may be one cause, not the dominant bottleneck. Some accounts may lack an immediate task, approval, data, or product fit. Those are hypotheses, not supplied findings. A narrower field-guidance test can distinguish comprehension from broader causes without assuming AI is required.
Outcome chain
| Link | Proposed change and mechanism | Evidence classification | External condition / competing explanation |
|---|---|---|---|
| Intervention → experience | Clearer field descriptions/examples in the existing setup route reduce ambiguity | Recommendation motivated by four of 10 sessions; effect is an assumption | Field schema changes, assistance from another person, device mix |
| Experience → behavior | Accounts submit correct required data and complete the requested workflow | Assumption; verify workspace state rather than guide usage | Account readiness, permissions, task need, support intervention |
| Behavior → durable user outcome | Timely first completion enables another useful workflow in days 15–28 | Inference; 120 of 200 early completers repeat, but this is not causal evidence | Repeat task frequency, customer mix, product reliability |
| User outcome → business consequence | Repeated value might support retention and reduce rescue work | Assumption; no support/retention effect supplied | Pricing, contract cycles, sales selection, other product changes |
The feedback loop changes from checking delivery/adoption to reviewing verified first value, repeated value, and failure reasons. Do not reward support or assistants for creating duplicate records merely to hit a numerator.
Focused metric portfolio
| Role | Metric / baseline | Proposed target | Decision it informs |
|---|---|---|---|
| Primary outcome | Whole-eligible first-and-repeat rate: 24% | Quarter aspiration 30%; causal pilot rule below is separate | Whether the intervention improves repeated value and merits expansion |
| Leading behavior | First-workflow completion: 40% | Planning diagnostic 50%, proposed; not an independent success claim | Whether setup friction improves or the problem lies earlier in eligibility/readiness |
| Learning diagnostic | Conditional repeat: 60% | Proposed monitor around baseline, with cohort mix explained; no automatic target derived from adoption | Whether added first completers also obtain repeated value; inspect dilution and segments |
| Guardrails | Correctness/authority, support burden, and manual-route health | Proposed boundaries below; baselines unknown | Override a nominal primary win if it creates harm or displaces viable access |
The 50% first-completion aspiration combined with unchanged 60% conditional repeat would mathematically yield 30% primary outcome. That is a planning scenario, not a forecast that both will occur. A higher conditional rate alone can reflect selection of fewer easy accounts and need not improve whole-population value.
Full metric contracts
Shared eligibility and timing contract
- Unit is a unique account, counted once at first eligibility in the cohort. Define the actual eligibility rule and authoritative eligibility timestamp before a pilot; neither is supplied in detail.
- Include every genuinely newly eligible account assigned to an arm, including non-users, failures, abandonments, manual-route users, accounts requiring support, and accounts later disabled. Exclude only predeclared invalid/test/duplicate eligibility records with auditable reasons; never exclude poor outcomes after assignment.
- Proposed day convention: day 1 starts at the eligibility timestamp; the first interval is elapsed time
[0, 14 days), and the repeat interval is[14, 28 days). Confirm that this matches source-query boundary semantics before comparing a new query to the 200/120 baseline. Do not silently reinterpret inclusive day labels. - For the three comparable rates, use accounts with complete 28-day follow-up. First completion can be shown provisionally at day 14, but label that immature view and do not combine it with a different cohort's repeat denominator. Right-censored accounts wait for maturity; report their count.
- Attribute by assignment at eligibility, regardless of later route switching. Separate intervention exposure from assignment. Segment by assigned arm, setup route used, intended workflow type, account readiness/experience, and relevant account size where those fields can be collected appropriately. Segment baselines are unavailable; do not invent differences.
- State evidence must include account ID, eligibility timestamp, requested-workflow identity, required-field validation result, verified completion timestamp, and distinct workflow ID. The exact schema is proposed, not an existing capability claim. Retried submissions and duplicate events do not create additional account successes.
- Proposed accountability: Data/Engineering for extraction and reconciliation, Product for the decision, Design/Support for task quality and friction review. Named owners and actual assignments are unknown and required before live testing.
M1 — whole-eligible first-and-repeat rate, primary
Numerator: mature eligible accounts with at least one verified first workflow during the first interval
and a distinct verified workflow during the repeat interval. Denominator: all mature newly eligible accounts in the assigned cohort. Source: authoritative workspace record/validation state joined to eligibility and workflow timestamps. Unit: account; window: 28 days from eligibility; segmentation: shared contract. Baseline: 120/500 = 24% from the supplied mature cohort, exact dates unknown.
Count gross verified completion evidence at the time it meets the requested-record/required-field rule, matching the source definition. Separately report later invalidation, incorrect records, unauthorized changes, and recovery in the fixed 28-day window. Do not relabel gross baseline as sustained net success: that net baseline is unavailable. A net sustained version would exclude accounts whose qualifying record is invalidated without a valid replacement by the window end, using a predeclared rule. It is a future quality analysis, not another established 24% fact.
Planning target: proposed 30%. Weekly review only checks maturity/data quality/safety; evaluate product impact after the predeclared mature exposure. Gaming risk: duplicate, trivial, or unrequested records and revised eligibility to shrink the denominator. Reconcile intent and state; audit exclusions and retries.
M2 — timely first-workflow completion, leading
Numerator: mature eligible accounts with a verified first workflow in the first 14-day interval. Denominator: the same mature eligible cohort as M1. Source/unit/segments/owners as above. Baseline: 200/500 = 40%. Proposed planning target: 50%; this identifies a potential lever, not permission to scale if repeat or quality fails. Gross/net reporting follows M1. Failure mode: making an invalid easy workflow appear complete or hiding manual-route failures. Review reasons for no first value, not just assistant usage.
M3 — conditional repeat among timely completers, diagnostic
Numerator: the same accounts counted in M1. Denominator: the same accounts counted in M2. A zero denominator produces “not estimable,” not 0% success. Source: verified distinct workspace workflows; unit: account; repeat window: days 15–28 under the shared convention. Baseline: 120/200 = 60%; no separate observed target. Proposed review: explain changes from baseline by first-completer mix and route before declaring improvement or deterioration.
Gross/net treatment follows M1, with denominator membership recorded from the original timely completion definition. Gaming risk: reduce first completions to select only high-readiness repeaters. It is not the primary success metric and cannot override a declining whole-eligible outcome.
G1 — correctness and authority guardrail
Numerator: attempted workflows producing an incorrect requested record, missing required fields despite a completion claim, destructive unintended changes, or unauthorized writes. Denominator: all workflow attempts in assigned accounts over days 1–28; report both absolute affected-account counts and rate by route/arm/workflow type. Source: authoritative validation, accepted user intent, access/audit records, and reviewed task samples. An assistant success message is an observation to check, not completion evidence.
Baseline unknown. Proposed hard floor: zero unauthorized writes or destructive unintended changes; either suspends the intervention. Proposed target for noncritical invalid-record/completion mismatch is no deterioration versus concurrent control, with a predeclared uncertainty method and materiality bound TBD before pilot. Unknown outcomes cannot be counted as successful. Proposed Support/Engineering accountability, actual owner unknown; immediate incident review plus weekly quality review. Record gross errors and recovered errors separately; recovery does not erase the original harm. Gaming risk: fewer logged attempts or excluding failed accounts.
G2 — support burden guardrail
Numerator: total observed support/rescue minutes related to setup/workflow completion in days 1–28 for assigned accounts. Denominator: all mature assigned eligible accounts, including those making no workflow attempt. Unit: minutes per eligible account; companion absolute incident count retained. Source: support records with task classification and documented coverage; segments: arm, route, workflow type, and account experience. Baseline and coverage unknown.
Proposed boundary: no material deterioration versus concurrent control; acceptable minutes increase and uncertainty rule must be agreed before exposure, not chosen after results. Count repeat contacts and recovery effort; do not net them against hypothetical saved labor. Proposed Support/Data ownership, named owner unknown. Review weekly and at mature outcome review. Gaming risk: moving rescue into untracked channels or measuring only successful users. Missing coverage blocks a support-saving claim and scale decision.
G3 — manual-route access and completion guardrail
Availability numerator: scheduled checks where an eligible manual-route test can reach the existing setup and submit permitted required fields; denominator: all scheduled checks during the pilot, including failed checks. Completion numerator: assigned manual-route attempts resulting in verified correct records; denominator: all manual-route attempts, including failed/abandoned attempts, within days 1–28. Source: controlled checks plus workspace state, not page loads. Segment by arm, workflow type, and permission state; unit: check or attempt as explicitly named.
Baseline unknown beyond the supplied fact that the manual route remains available. Proposed floor: no intervention-induced loss of the manual route; any such loss stops enrollment until repaired. Proposed completion boundary: no material deterioration versus control, bound to be fixed before test. Keep manual rescue and route switching visible. Proposed Engineering/Design accountability, actual owner unknown; ongoing checks plus weekly/mature review. Gaming risk: hiding the route or steering users away so only easy attempts remain. Gross attempts and eventual corrected completion both reported without dropping failures.
Experiment and explicit decisions
Hypothesis: Clearer required-field guidance for newly eligible accounts increases verified timely first completion and subsequent repeated value compared with the current manual route, without worsening correctness, support burden, or manual access.
Run a bounded account-level randomized test after eligibility/state joins and quality checks work. A proposed initial variant simplifies required-field explanations; screen count is not the objective. If an AI assistant is later tested, isolate its incremental effect in a separate design with explicit permissions and validation; do not combine all proposed features and attribute the outcome to AI.
Proposed causal success threshold: At least a five percentage-point absolute increase in mature M1 versus concurrent control, with the lower bound of a predeclared confidence interval above zero, plus all guardrails satisfied. Five points is a proposed practical significance threshold, not baseline evidence. The planning aspiration of 30% and this experimental contrast answer different questions.
Minimum credible sample, allocation, interval method, clustering/contamination treatment, expected control rate, and support/error materiality bounds are TBD. Data/Product must set them before enrollment using the baseline and anticipated variation. Until set, the experiment is not release-ready. Do not declare success from an underpowered favorable point estimate or optional early stopping; declare one primary comparison and decision time in advance.
| Decision | Proposed trigger |
|---|---|
| Continue bounded learning | Data and safety are sound but primary evidence is immature or inconclusive; maintain agreed cap and wait for 28-day follow-up |
| Modify | Field comprehension improves but verified first value or repeat does not, or fixable friction/support burden appears; investigate the causal link and retest |
| Scale | Predeclared mature exposure meets the M1 causal threshold, guardrails pass, and segment effects show no unexplained material harm; cross-functional decision owner approves |
| Stop | Unauthorized/destructive change, lost manual access, unresolved critical data integrity, or credible evidence of material primary/quality harm. Prefer current route if adequate exposure shows no useful benefit |
Examine composition before aggregation: more low-readiness accounts can lower conditional repeat while whole-population repeated value rises. Conversely, filtering to high-readiness accounts can lift conditional repeat without creating more total value. Show counts and rates for all arms/segments; missing segment instrumentation is a limitation, not evidence of equality.
Instrumentation gaps and concrete next actions
| Gap / action | Risk to decision | Required evidence | Proposed owner / due |
|---|---|---|---|
| Define eligibility and exact interval boundaries | Denominator changes or incomparable baseline | Reviewed eligibility rule, timestamp semantics, and reconstructed 500/200/120 query | Data/Product roles; people unknown; before test approval |
| Verify authoritative completion and requested intent | False assistant messages inflate completion | State reconciliation for valid, invalid, duplicate, retried, and unauthorized cases | Engineering/Data roles; people unknown; before exposure |
| Gather segment baselines and first-value failure reasons | Mix shift or wrong intervention | Cohort counts by predeclared segments and observed required-field tasks | Product/Design/Data roles; people unknown; before final experiment plan |
| Establish support/error/manual-route baselines | A nominal win conceals burden or harm | Coverage-checked support minutes, quality rubric, and manual-route checks | Support/Engineering/Design roles; people unknown; before exposure |
| Agree targets, sample, cadence, and quality bounds | Post-hoc success or underpowered scale | Predeclared experiment plan and named decision owner | Product/Data roles; people/date unknown; before enrollment |
No assignments, experiment approvals, or outcomes are recorded. The immediate decision is to adopt the outcome objective and authorize measurement/field-guidance preparation; the next gate is a reviewable experiment plan with real owners and boundaries.
Delivery review performed: 40%, 60%, and 24% retain their distinct denominators; mature windows and authoritative records are required; the causal portfolio is focused; proposed targets are labeled; support, error, and manual-route guardrails can veto scale. Intervention effects, guardrail baselines, segment results, sample sufficiency, and retention impact remain unknown.
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About this skill
What it helps you do
Turn feature-based goals into user outcomes, precise success measures, and clear experiment decision rules.
Built for product managers, product leaders, founders, and analytics practitioners who need a concrete work product they can inspect and revise.
What is included
- A focused SKILL.md operating workflow with evidence and decision boundaries.
- Original fictional practice material with explicit source definitions and constraints.
- A delivery review for the errors that can change the decision.
- Linked templates or output contracts and a transfer exercise for changed evidence.
How to use it
Give your agent the decision, source material, audience, and requested format. Ask it to use this skill. For a first run, use the included fictional practice packet. The agent separates supplied facts from assumptions, produces the deliverable, and checks decision-critical gaps.
Why this edition
This paid edition extends the creator's original workflow with task-specific practice material and delivery resources. It is intended to help you produce and review the work, not just fill headings. The listing demo uses fictional evidence; it is not an actual customer result.
Boundaries
Works from supplied or authorized evidence; it cannot invent access, facts, benchmarks, or measured business impact. Synthetic fixtures demonstrate the method only. Quality depends on source coverage and the executing agent. Real document page limits require a supported renderer. No customer accounts are required for supplied-context practice. Optional connected research and external writes depend on your tools and authorization.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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