Draft OKRs

MEMORANDUM

TO: Grace Mensah, Chief Product Officer FROM: Staff Product Manager DATE: October 3, 2024 SUBJECT: Q3 OKR Post-Mortem & Proposed Q4 Product OKRs

*

1. The Disconnect: What Q3 OKRs Actually Tell Us

At our recent all-hands, a product OKR score of 0.81 was celebrated as a “great quarter.” In reality, Q3 was a business failure: * Net Revenue Retention (NRR) dropped from 103% to 102% (Target: 108%). * Quarterly Logo Churn rose from 3.1% to 3.4% (Target: 2.5%).

The 0.81 score is a vanity metric masking acute operational disconnects across four distinct areas:

``` [Output Orientation: 9/16 KRs] ──> Shipped features, missed business outcomes [Metric Manipulation] ──> Completion rate rose via relaxed definition (100% -> 80%) [Activation Breakdown] ──> 31 days to 1st learner (Goal: 14) fuels 45% of churn [Premature Expansion] ──> Pushed upgrade prompts while seat activity fell to 29% ```

#### A. Feature Delivery Was Confused with Value Creation Nine of our 16 Key Results were binary outputs (shipping features or running counts). Teams scored 1.0 on outputs—shipping offline mode, streaks, dashboards, upgrade prompts, and integrations—while customer-facing outcomes collapsed: * Learner App scored 1.0 on features, yet Weekly Active Learners per seat fell from 0.31 to 0.29 (Target: 0.40). * Growth scored 1.0 on experiments and upgrade prompts, yet Seats added in existing accounts fell from 9,200 to 8,100 (Target: 14,000). * Admin delivered 3 HRIS integrations (misclassified as an “outcome”), but the actual outcome—Days from contract to first learner—only improved from 34 to 31 days (Target: 14).

#### B. Vanity Gains and Metric Redefinition Content claimed a 1.0 score by driving Course Completion Rate from 41% to 58% (Target: 55%). However, this was largely engineered by lowering the completion threshold on August 1 from 100% of modules to 80%. Artificially inflating course completions obscured stagnant baseline learner demand.

#### C. Product Neglect Directly Fed Q3 Exit Drivers Our exit interviews across 38 churned accounts reveal direct causation with our product failures: 1. "Our people didn’t use it" (17 accounts / 45%): Directly caused by dropping learner engagement (0.29 weekly active learners per seat). Gamification (streaks/badges) failed to solve core utility. 2. "Moved to HR system’s LMS" (7 accounts / 18%): While we launched 3 HRIS integrations, we treated them as tick-box deliverables rather than driving customer activation. 3. Budget cuts (9 accounts / 24%): When CFOs review seat utilization below 30%, unused seats are cut at renewal. 4. Onboarding Lag: Accounts reaching first learner within 14 days churn at one-third the rate of slower accounts. By taking 31 days to activate, Admin is losing accounts before they even start.

---

2. Strategic Narrative for Q4

We cannot expand accounts that are not using the product. To move NRR to 106% and logo churn down to 2.6%, the product strategy must execute in strict sequence across the account lifecycle:

``` [Admin: Days 1–14] [Learner App: Days 15–365] [Growth: Renewal & Expansion] Compress onboarding to <14d ──> Drive habitual weekly usage ──> Monetize 80%+ utilized accounts (Reduces churn by 66%) (Eliminates "nobody used it") (Reverses NRR contraction) ```

1. Admin (Time-to-Value): Compress onboarding to under 14 days using automated HRIS provisioning to unlock the 66% churn reduction.
2. Learner App (Habitual Engagement): Drive weekly active learners per seat from 0.29 to 0.40 to resolve the #1 churn driver and defend against budget cuts.
3. Growth (Expansion Based on Utilization): Stop spamming low-usage accounts with prompts; identify accounts reaching >80% active seat capacity and drive contract tier expansion.

---

3. Proposed Q4 OKRs (Learner App, Admin, Growth)

``` ┌──────────────────────────────────────────────────────────────────────────────────┐ │ COMPANY OBJECTIVE (CEO) │ │ Grow by keeping and expanding the customers we have │ │ NRR: 102% -> 106% │ Logo Churn: 3.4% -> 2.6% │ └───────────────────────┬──────────────────────────┬───────────────────────────────┘ │ │ ┌───────────────┴──────────┐ ┌───────────┴──────────────┐ ▼ ▼ ▼ ▼ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ ADMIN │ │ LEARNER APP │ │ GROWTH │ │ Time-to-1st- │ │ Weekly Active│ │ High-Utility │ │ Learner <14d │ │ Learners >38%│ │ Seat Growth │ └──────────────┘ └──────────────┘ └──────────────┘ ```

#### A. Admin Team * Objective: Accelerate customer time-to-value to protect new cohort retention. * Context: Closing the activation gap from 31 to 14 days addresses our highest-leverage retention vector. * Key Results: * KR 1 (Outcome): Reduce median Days from contract to first learner from 31 days to 14 days. * KR 2 (Outcome): Increase % of newly signed accounts with active HRIS employee sync within 7 days from 22% to 65% (Baseline: internal onboarding sample). * KR 3 (Outcome): Increase the percentage of invited admins who configure reporting within 10 days of signature from 28% to 60% (Baseline: Q3 dashboard launch data).

#### B. Learner App Team * Objective: Establish enduring learning habits to eliminate non-usage churn. * Context: Attacking the #1 churn reason ("people didn't use it") by lifting routine learner engagement rather than vanity completions. * Key Results: * KR 1 (Outcome): Increase Weekly active learners per seat from 0.29 to 0.38. * KR 2 (Outcome): Increase 4-week active learner retention (learners active in Week 1 who return in Week 4) from 34% to 48% (Baseline: Q3 cohort average). * KR 3 (Outcome): Reduce the percentage of licensed seats with zero activity in the trailing 30 days from 52% to 35%.

#### C. Growth Team * Objective: Capitalize on active accounts to drive sustainable seat expansion. * Context: Expansion must be an outcome of account saturation, not blind in-app prompts. * Key Results: * KR 1 (Outcome): Increase Seats added in existing accounts from 8,100 to 12,500. * KR 2 (Outcome): Increase account-level seat utilization (accounts with >80% active seats in past 30 days) from 19% to 32% (Baseline: Q3 active accounts). * KR 3 (Outcome): Convert 35% of accounts reaching >90% seat capacity into expanded contracts within 30 days (Baseline: 18%).

---

4. OKR Governance Rules for Q4

To ensure we never celebrate a 0.81 score while missing core business commitments again, I propose three immediate operating changes:

1. Zero Pure Output KRs: No KR may simply measure shipping code, closing tickets, or running experiments. Every KR must measure a verifiable shift in customer or business behavior.
2. Target Continuity & Definition Lock: Any changes to metric definitions (such as completion percentages) must maintain restated historical baselines and require Product Operations sign-off.
3. Cross-Functional Dependencies on Onboarding: Admin and Learner App will review weekly leading indicators (TTFL and weekly seat activation) jointly with Customer Success to intercept at-risk renewals early in the contract cycle.

Memo

To: Grace Mensah, CPO Subject: What Q3 OKRs tell us—and Q4 OKRs tied to retention and expansion

What Q3 tells us

Q3 was not a “great quarter” against the company goal. Net revenue retention fell to 102%, below the 108% goal, and logo churn rose to 3.4%, above the 2.5% goal. The 0.81 average team score obscures that miss: many high-scoring KRs measured shipping or activity, not customer value.

The clearest warning is usage. Learner app weekly active learners per paid seat declined from 0.31 to 0.29, missing its 0.40 target. In exit interviews, “our people didn’t use it” was the most common reason for leaving (17 of 38 accounts). That makes engagement a credible retention lever to investigate—not proof that low app usage caused those departures.

Onboarding is another promising lever: time to first learner was 31 days, versus a 14-day target. Accounts reaching a first learner within 14 days churned at one-third the rate of the rest. That association supports prioritizing faster activation, but does not establish causation. Seven of the 38 departing accounts moved to an LMS bundled with their HR system, so integrations may also matter; Q3’s three launches are an output, not evidence of customer adoption or retention impact.

Expansion also underperformed: existing-account seats added were 8,100, below both the 14,000 target and the 9,200 baseline. Running 13 experiments and shipping upgrade prompts did not translate into the intended result. Meanwhile, Content’s completion result is hard to interpret: the definition changed on 1 August, from every module to 80% of modules, so 58% cannot be fairly compared with the 55% target without a consistent-definition view. Strong uptime and course delivery are useful foundations, but do not offset the missed retention and expansion outcomes.

Proposed Q4 OKRs

Keep the company outcome explicit and shared: NRR 102% → 108%; quarterly logo churn 3.4% → 2.5%. These are not numbers that team KRs can literally be summed to produce. They are the outcomes the teams collectively support; the team KRs below are leading indicators. Review company outcomes alongside them, using consistent cohort and revenue definitions.

Use the existing metric definitions and reporting windows for these comparisons; do not count shipped features, experiments, or prompts as substitutes for the outcomes. The Q3 data provided does not show how expansion seats translate into NRR, or how team-level changes affect logo churn. For Q4 reviews, Finance and the teams should make the NRR bridge visible—expansion, contraction, and churn—and check whether faster activation and higher learner activity precede improved retention. That will let us judge whether these team results are actually adding up to the company goal.