<!-- Anchor artifact: measure-okr-grader (measurement) | scenario activation-q3-close | 2026-06-15 anchor run wf_c1261234-93a, G=1.
     This was the draft all three blind judges scored (anchor run wf_c1261234-93a). The scored original is preserved in git at the 2026-06-15 anchor commit; an operating layer (decisions / owners / maintainer fix-notes) was added 2026-06-15 per maintainer review. -->

---

```markdown
---
phase: measure
cycle: 2026-Q3
team: Activation
skill: measure-okr-grader
version: 1.0.0
---
# OKR Cycle Review: Activation Team, Q3 2026

## Leadership Readout (one page)

> Added 2026-06-15 (maintainer review): a leadership-ready summary so the candid full review below is read, not skimmed past.

**Bottom line: this is NOT a win.** Real activation progress, but a committed instrumentation miss, a conversion KR that cannot yet be scored, and a failed support guardrail. Do not present Q3 as a success.

| KR | Type | Result | Score |
|----|------|--------|-------|
| KR1 - signup-to-activation (22% -> 35%) | aspirational | 30% | 0.62 (in the 0.6-0.7 sweet spot) |
| KR2 - instrument 100% of new teams | committed | ~80% (Android slipped 2 wks) | FAIL (miss) |
| KR3 - free-to-paid in 30d (6% -> 9%) | aspirational | Aug 7%; Sep window closes Oct 15 | Deferred |
| KR4 - support tickets <= 14 / 100 signups | guardrail | 19 / 100 (+36%) | FAIL (reported standalone, not averaged in) |

**Three must-act items:** (1) root-cause the support-ticket spike before any further checklist iteration; (2) close the Android instrumentation gap in Q4 weeks 1-2 (a carry-forward completion, not new KR budget); (3) wait for the Oct 15 KR3 close before making any conversion decision.

**One ask of leadership:** do NOT accept the proposal to reframe KR2 as "done for the platforms that mattered." It is a committed KR; the miss stands. Accepting the reframe would teach the org that committed targets can be moved at grading time. Detail in "Risks in Interpretation" and the decisions table below.

---

## Summary

- Scope: Activation team
- Cycle: 2026-Q3
- Overall interpretation: Mixed. The quarter produced one solid aspirational KR result just below the sweet spot (activation rate), one committed KR miss that the PM has proposed to reframe but the evidence does not support reframing, one KR whose final window extends past cycle close and cannot yet be scored, and a failed guardrail that cannot be averaged away. The cycle should not be presented to leadership as a win. The honest read is: meaningful progress on activation rate, an instrumentation commitment that fell short, a conversion signal that is suggestive but incomplete, and a support-load spike that is unresolved and consequential.
- Evidence confidence: Mixed. Activation rate is well-instrumented (high confidence). Conversion attribution is weaker (low-to-medium confidence). The support-ticket rise has not been root-caused (low confidence on interpretation, though the count itself is reliable).
- Main learning: The onboarding checklist moved activation rate meaningfully but drove a support-ticket surge that has not been diagnosed, making the net impact on user health ambiguous.

---

## Scorecard

- Objective: "New teams reach value fast enough to stick and convert."
  - Rough qualitative read: Partial progress on a hard objective; activation improved but conversion is not yet observable and the guardrail failed, leaving the team without a clean story for any of its three primary KRs.

- KR1 (aspirational; indicator class: lagging): Increase signup-to-activation rate from 22% baseline to 35% target.
  - Actual: 30% (as of Q3 cycle close)
  - Score: 0.62 - calculated as (30 - 22) / (35 - 22) = 8 / 13
  - Evidence confidence: High. Activation is well-instrumented and the measurement definition was stable across the cycle.
  - Interpretation: 0.62 sits within the aspirational sweet spot of 0.6 to 0.7. This is a designed outcome for a stretch KR, not a miss. The result reflects real movement and is the quarter's clearest signal of progress. It does not confirm that the onboarding checklist caused the gain; the checklist shipped on time and correlated with the rate increase, but the connection is apparent, not established.

- KR2 (committed; indicator class: leading): Ship and instrument the new onboarding checklist so median time-to-first-dashboard is measurable for 100% of new teams by end of quarter.
  - Actual: Instrumentation shipped for approximately 80% of new teams; Android rollout slipped two weeks, leaving 20% unmeasured as of cycle close.
  - Score: FAIL. The committed target was 100% coverage. 80% coverage is not 100% coverage. This KR is `not-yet-fully-observable` for the Android cohort (20%); the observed subset is a sub-signal, not a pass.
  - Evidence confidence: High on the coverage count itself; the ship and instrumentation status are known.
  - Interpretation: The PM's proposal to mark this as "done for the platforms that mattered" is a retroactive scope shrinkage on a committed KR. The original commitment named 100% of new teams, not 100% of Android-excluded new teams. This skill refuses that reframing. The KR is a miss. The Android slip has a known two-week lag, which means full observability is achievable early Q4 for the deferred cohort. The appropriate action is to document the slip, note when the gap will close, and carry a completion commitment into Q4 - not to recast the scope.

- KR3 (aspirational; indicator class: lagging): Increase free-to-paid conversion within 30 days from 6% baseline to 9% target.
  - Actual: August cohort at 7% (as of cycle close); September cohort's 30-day conversion window closes October 15 - after cycle end. September is `not-yet-observable`.
  - Score: Deferred. The August cohort provides an interim sub-signal: (7 - 6) / (9 - 6) = 1 / 3 = 0.33 - a provisional reading for August alone. The full-cycle score cannot be computed until the September cohort's window closes October 15.
  - Evidence confidence: Low for the full KR (window incomplete); Medium for the August cohort alone (instrumentation weaker than activation, as noted by the team).
  - Interpretation: The August sub-signal of 0.33 is below aspirational sweet spot but is only one of two cohorts. The final score will depend on September performance, which is not yet observable. A forced cycle-close score would be misleading. The score is marked deferred pending October 15 observability. Conversion attribution is flagged as a measurement weakness; the team should not treat any movement here as confirmed causation from the checklist or connectors without stronger attribution tooling.

- KR4 (operational_health; indicator class: guardrail): Keep new-user support tickets per 100 signups at or below the baseline of 14.
  - Actual: 19 per 100 signups during the checklist rollout.
  - Score: FAIL. The threshold band was 14 or below; actual is 19, a 36% overshoot.
  - Evidence confidence: Medium. The ticket count itself is reliable; the root cause of the spike has not been identified.
  - Interpretation: KR4 has indicator class `guardrail`. Its result is reported here as a standalone signal and is NOT averaged into the primary objective score or diluted by KR1's strong aspirational result. A failed guardrail is a separate finding, not a footnote. The spike coincides with the checklist rollout but causal attribution is unresolved. Until the root cause is identified, the team cannot know whether the checklist design is the driver, whether the support taxonomy shifted during rollout, or whether the spike is a transient new-feature discovery pattern. This is a consequential open question. Presenting the quarter to leadership without surfacing this failure would misrepresent the team's health picture.

---

## Objective Interpretation

- Result: The objective made visible progress on activation (KR1 solid aspirational result) but has three unresolved items: a committed instrumentation miss (KR2), a deferred conversion score (KR3), and a failed support-load guardrail (KR4). The objective cannot be called a win.
- Why: The redesigned onboarding checklist appears to have driven activation rate improvement; the correlation is strong and timing is consistent. Instrumentation coverage fell short because the Android rollout slipped. The conversion signal is incomplete by design (measurement window). The support spike is unexplained.
- What changed during the cycle: Android checklist rollout slipped two weeks (execution dependency, not scope change). The Segment connector did not ship (partial initiative miss). Support ticket volume surged during rollout - unanticipated.
- What the score does and does not mean:
  - Does mean: The team moved activation rate meaningfully within an aspirational framing; the onboarding checklist shipped (for most platforms) and correlates with the rate gain; the commitment to full instrumentation was not met.
  - Does NOT mean: The quarter was a win overall; the conversion thesis is confirmed; the support load is acceptable or transient.

---

## Evidence Quality

- Issue 1: Android instrumentation gap on KR2
  - Impact: 20% of new teams have no time-to-first-dashboard measurement. The team cannot assess whether the checklist effect is uniform across platforms or concentrated in one. Any learning drawn from the instrumented 80% may not generalize.
  - Recommended fix: Close the Android instrumentation gap in the first two weeks of Q4. Before drawing cycle conclusions on median time-to-first-dashboard, verify the Android and non-Android cohorts show comparable activation patterns.

- Issue 2: Conversion attribution weakness on KR3
  - Impact: The 30-day conversion signal cannot be reliably attributed to specific initiatives (checklist, connectors, or other factors). The August 7% interim reading is a count, not an attribution. At current instrumentation fidelity, the team risks crediting the wrong lever.
  - Recommended fix: Instrument conversion by acquisition cohort with initiative touchpoint tagging before Q4 closes the next conversion window. Hand off to `measure-instrumentation-spec`.

- Issue 3: Support ticket spike - unrooted cause on KR4
  - Impact: Without a root cause, the team cannot know whether the checklist design introduced confusion, whether support routing changed, or whether the spike is a discovery-phase transient that resolves after users orient. The guardrail failure could represent a serious UX problem or a temporary signal; the evidence does not distinguish.
  - Recommended fix: Conduct a ticket taxonomy analysis (category, checklist step referenced, time-since-signup). Hand off to `measure-dashboard-requirements` to add a support-by-cohort-and-feature breakdown to the standard health dashboard.

- Issue 4: Single-cycle activation rate reading
  - Impact: KR1's 0.62 aspirational result is encouraging but comes from one quarter. The activation improvement could be a durable effect of the checklist redesign or a cohort-composition artifact (different mix of team sizes, verticals, or acquisition channels this quarter).
  - Recommended fix: Carry activation rate forward as a tracked metric in Q4 to confirm durability. Segment by cohort characteristics to rule out composition effects.

---

## Initiative Review

- Initiative 1: Redesigned onboarding checklist
  - Linked to: KR1 (activation rate), KR2 (instrumentation), KR4 (support tickets - guardrail)
  - Status: Shipped on time (partial platforms; Android slipped two weeks)
  - Apparent contribution: High for KR1 (strong timing correlation), unclear for KR4 (the spike coincides with the rollout; causal link not established)
  - Recommendation: Continue and iterate, but the KR4 spike must be root-caused before the next redesign iteration. Shipping on time and correlating with an activation gain is not a full win while the support-load failure is unresolved.

- Initiative 2: Three integration connectors (Salesforce, HubSpot, Segment)
  - Linked to: KR1 (activation rate), KR3 (conversion)
  - Status: Partially shipped. Salesforce and HubSpot shipped; Segment slipped.
  - Apparent contribution: Unclear. The two shipped connectors went live during the same window as the checklist; no instrumentation isolates their effect on activation or conversion.
  - Recommendation: Rework with a sharper hypothesis. Before building Segment connector in Q4, define a measurable prediction: which user cohort activates or converts at a higher rate when Segment is available, and by how much. Do not count Segment completion as a Q4 KR without a linked outcome hypothesis.

- Initiative 3: Ten onboarding interviews
  - Linked to: KR1 (activation rate) via checklist design input
  - Status: Completed
  - Apparent contribution: Medium. The interviews informed the checklist redesign. If the checklist drove the activation gain, the interviews contributed upstream. The link is plausible but several steps removed.
  - Recommendation: Continue as a standing practice. Document the specific friction points the interviews surfaced and track whether next-cycle design changes address them. The interviews also likely contain signal relevant to the support spike; re-examine the interview notes for confusion patterns that may predict the ticket categories.

---

## Learning

- Validated assumptions:
  - A redesigned onboarding checklist can move signup-to-activation rate within a single quarter. The 0.62 aspirational result is consistent with the hypothesis that structured early-moment guidance reduces time-to-value.
  - User research (onboarding interviews) can feed a high-iteration design cycle within a quarter when scope is focused.

- Invalidated assumptions:
  - "Shipping the checklist is sufficient to instrument the metric for all users." The Android rollout dependency was not adequately risk-managed. A committed 100% coverage target required shipping dependency ownership to be resolved at OKR-writing time, not discovered during rollout.
  - "The checklist rollout will be neutral-to-positive on support load." The support spike invalidates this assumption, at least in the short term. Whether this resolves as users orient or represents a durable design problem is not yet known.

- Surprises:
  - Support tickets rose 36% above baseline during rollout. This was not anticipated and has not been root-caused. The scale of the spike (19 vs. 14 threshold) is large enough that it is not plausibly attributable to noise alone.
  - The Segment connector slip did not visibly depress the activation rate - suggesting that the checklist experience itself, not connector availability, is the primary driver of the observed rate gain (though this inference is weak without cleaner attribution).

- Decision implications:
  - Do not run another checklist redesign iteration until the support spike root cause is resolved. Iterating on a design with an unresolved UX problem risks compounding the issue.
  - Do not use KR3's August interim reading as a basis for conversion-related product decisions; wait for the full September cohort to close October 15 before drawing conclusions.
  - Treat the Android instrumentation gap as a Q4 P0 completion item, not a deprioritization candidate.

---

## Next-cycle Recommendations

1. Close the Android instrumentation gap in Q4 week 1-2. Instrument median time-to-first-dashboard for the Android cohort and backfill the Q3 baseline so the committed KR2 measurement is complete. This is a carry-forward completion, not a new OKR - it should not consume KR budget.

2. Root-cause the support ticket spike before the next checklist iteration ships. Assign a ticket taxonomy review (category, checklist step, time-since-signup). The guardrail failure must have a postmortem before the team iterates on the same surface. Draft next-cycle checklist work only after understanding whether the spike is a design problem, a discovery-phase artifact, or a routing change.

3. Establish conversion attribution instrumentation before Q4's conversion window opens. The current signal cannot support initiative-level attribution. Without this, the Q4 KR3 equivalent will have the same observability weakness.

4. For Q4 OKR drafting: if the September cohort (observable October 15) shows conversion at or above 7.5%, consider carrying a revised conversion target forward. If below 7%, investigate the acquisition funnel for Q3 cohort composition changes. Do not auto-continue the 6% to 9% aspirational target without reviewing the full-cycle Q3 result first.

5. Reconsider the Segment connector as a committed initiative only with a linked outcome hypothesis. Define what measurable activation or conversion effect Segment integration is expected to produce, and for which user segment, before scoping Q4 work.

6. Hand-offs:
   - `iterate-lessons-log` for the Android rollout dependency miss (the pattern of committing to 100% coverage without owning the full rollout dependency chain is an organizational memory item, not just an Activation team note)
   - `iterate-retrospective` for the team-process dimension of the Android slip and the support-spike non-anticipation
   - `define-hypothesis` for: (a) "the support spike is caused by specific checklist step confusion and will resolve after step redesign" and (b) "Segment connector availability increases 30-day conversion rate for data-team personas by X%"
   - `measure-instrumentation-spec` for conversion attribution by initiative touchpoint
   - `measure-dashboard-requirements` for a support-tickets-by-cohort-and-checklist-step health view
   - `foundation-okr-writer` for Q4 drafting, with the October 15 KR3 final score as a required input before activation-to-conversion objective is re-set

---

## Risks in Interpretation

- The 0.62 aspirational score on KR1 could be read by a leadership audience as "the quarter was a win." It should not be. KR2 is a committed miss, KR3 is unscored, and the guardrail failed. The honest framing is that activation progress is real but incomplete and does not yet confirm the full "reach value fast enough to stick and convert" objective.

- The PM's proposal to reframe KR2 as "done for the platforms that mattered" is a retroactive scope shrinkage on a committed KR. If this reframing is accepted without documentation, it teaches the team that committed targets can be redefined at grading time. This undermines the OKR operating system. The miss should be recorded as a miss.

- Presenting the August cohort's 7% conversion rate as the Q3 conversion result is a forced score on a not-yet-observable KR. The September cohort is not yet closed. Any readout that cites a Q3 conversion number is citing an incomplete metric.

- The support ticket guardrail failure has not been root-caused. If leadership receives a "Q3 activation win" narrative without the guardrail finding, they are receiving an incomplete picture. The KR4 result belongs in the readout, surfaced as a separate signal, not mentioned in a footnote.

- The initiative-to-KR contribution inferences in this review are apparent, not causal. The checklist, the connectors, and external factors (seasonal patterns, acquisition mix shifts) were all in motion simultaneously. Any causal claim about which initiative drove which KR movement is beyond what this cycle's evidence supports.

- A single-cycle activation rate reading is suggestive, not confirmatory. The 0.62 result should be carried into Q4 as a tracked metric to test durability before the team builds strategy on the assumption that the activation improvement is durable.

---

## Decisions, Owners & Open Items

> Operating layer (added 2026-06-15, maintainer review): the review's recommendations and integrity calls
> made ownable and dated. Owners/dates are illustrative for this scenario.

| ID | Title | Final decision (summary) | Status | Owner | Due | Last updated |
|----|-------|--------------------------|--------|-------|-----|--------------|
| D-1 | KR2 scope-reframe request | DECIDED - rejected; the miss stands | DECIDED | PM + group PM | Q3 close | 2026-06-15 |
| D-2 | KR3 final score | Deferred to the Sep cohort close | GATED | PM + analyst | Oct 15 | 2026-06-15 |
| D-3 | Support-spike root cause | Pending - ticket taxonomy review | GATED | PM + Support | Q4 wk 2, before next checklist iteration | 2026-06-15 |
| D-4 | Android instrumentation gap | DECIDED - Q4 P0 carry-forward | DECIDED | Eng lead | Q4 wk 1-2 | 2026-06-15 |
| D-5 | Segment connector as a Q4 committed initiative | Pending - only with a linked outcome hypothesis | GATED | PM | Q4 drafting | 2026-06-15 |

### D-1: KR2 scope-reframe request
Status: DECIDED
**Context** - The PM proposed marking KR2 "done for the platforms that mattered" (excluding the 20% Android cohort). KR2 was a committed 100%-coverage target. Value at stake: the integrity of the OKR operating system - accepting a grading-time reframe teaches that committed targets are movable.
**Potential solutions** - (a) accept the reframe (score it a pass); (b) reject it, record the miss, and carry a Q4 completion commitment. Recommendation: (b).
**Final decision** - Rejected. KR2 is a miss; document the Android slip and carry a completion commitment into Q4. Owner: PM + group PM.

### D-2: KR3 final score
Status: GATED follow-up (owned; gate below)
**Context** - The September cohort's 30-day window closes Oct 15, after cycle close; the August interim is 0.33. A forced cycle-close score would be misleading. Value: an honest, complete conversion read before any conversion decision.
**Potential solutions** - (a) score now on August alone; (b) defer to Oct 15. Recommendation: (b).
**Final decision** - Deferred to Oct 15; append the final score then. Owner: PM + analyst.

### D-3: Support-spike root cause (failed guardrail)
Status: GATED follow-up (owned; gate below)
**Context** - Support tickets ran 19/100 vs a 14 threshold (+36%) during rollout, un-root-caused. Value: knowing whether the checklist design is harmful, a routing artifact, or a transient - it gates the next iteration.
**Potential solutions** - (a) iterate the checklist now; (b) run a ticket taxonomy review (category, checklist step, time-since-signup) first. Recommendation: (b) - do not iterate on an unresolved UX problem.
**Final decision** - Pending. Run the taxonomy review before the next checklist iteration. Owner: PM + Support; Q4 week 2.

### D-4: Android instrumentation gap
Status: DECIDED
**Context** - 20% of new teams (Android) lack time-to-first-dashboard instrumentation, so KR2 learning may not generalize. Value: complete, trustworthy measurement.
**Potential solutions** - (a) deprioritize; (b) close it as a Q4 P0 carry-forward (no new KR budget). Recommendation: (b).
**Final decision** - Close in Q4 weeks 1-2 as a P0 carry-forward; backfill the baseline. Owner: Eng lead.

### D-5: Segment connector as a Q4 committed initiative
Status: GATED follow-up (owned; gate below)
**Context** - Segment slipped in Q3; its effect on activation/conversion was never isolated. Value: avoid committing build effort without a measurable outcome thesis.
**Potential solutions** - (a) carry Segment as a committed initiative on completion alone; (b) require a linked outcome hypothesis (which cohort, what lift) before scoping. Recommendation: (b).
**Final decision** - Pending. Do not commit Segment for Q4 without a linked outcome hypothesis. Owner: PM; decide at Q4 drafting.

## Source of Truth

This artifact is a review document, not the canonical OKR record. The authoritative OKR set, baseline definitions, and tracking history live in the Activation team's Q3 OKR tracker (`okr/activation/2026-q3` in the company OKR system); the PM owns linking this review from that page so the two never diverge. Scores and evidence here reflect the review as of Q3 cycle close; the October 15 KR3 final score must be appended once the September cohort window closes (tracked as decision D-2 below).
```
