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

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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.

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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.

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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%).

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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.

To: Grace Mensah, CPO From: Staff PM, Product Re: What Q3's OKRs tell us, and proposed Q4 OKRs for Learner app, Admin and Growth

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1. Bottom line

Q3 was not a great quarter. Both company key results moved backwards:

• Net revenue retention (NRR) fell from 103% to 102%, against a target of 108%.
• Logo churn rose from 3.1% to 3.4%, against a target of 2.5%.

The 0.81 average hid this because it mixed outputs, which we control, with outcomes, which customers control. We shipped everything we said we would. The customer behaviours those launches were meant to change didn't move, or got worse.

2. What Q3 actually tells us

Outputs scored perfectly. Outcomes didn't.

• All 10 output key results (KRs) scored 1.00. I'm counting "Launch 3 HRIS integrations" as an output; it was labelled an outcome, but it's a launch.
• The 6 genuine outcomes averaged 0.48.
• The three outcomes that link most directly to the company goal averaged 0.05: weekly active learners per seat (0.00), days to first learner (0.15) and seats added in existing accounts (0.00).

The 0.81 doesn't reproduce. The 16 KRs on the scorecard average 0.74. Averaging by team gives 0.75. We should find out how 0.81 was calculated before it's quoted again.

Launches didn't move the metrics they targeted.

One "win" is probably a definition change. Course completion rose from 41% to 58%. But on 1 August, "complete" changed from 100% of modules finished to 80%. Completion climbing while weekly activity fell suggests most of the gain came from the new definition. We should restate Q3 on both definitions before claiming it.

Scoring rewarded going backwards no more harshly than standing still. Weekly activity and seats added both ended below their baselines, yet each scored 0.00, the same as no change. The scorecard couldn't show that we lost ground.

The churn data points to adoption. Of 38 exit interviews:

Accounts that reached a first learner within 14 days churned at one third the rate of the rest. That is a correlation, not proof: healthier buyers may simply onboard faster. Still, it is our strongest signal. Adoption is the lever. More features and more experiments are not, on Q3's evidence.

3. Rule changes for Q4

1. KRs are outcomes only. Launches go in a separate initiatives list and are not scored.
2. Score against the baseline, and allow negative scores. Ending below the baseline should look worse than standing still.
3. Freeze metric definitions for the quarter. Any change gets restated on both the old and new definition.
4. Every KR names the company KR it serves.

4. Proposed Q4 OKRs

Baselines are Q3 actuals where we have them. Three baselines are marked TBC: we don't yet track those metrics, and Data will deliver them by the end of week 2. Each target is set as a fixed increase on its baseline, so the target is fixed as soon as the baseline is known.

Learner app. Objective: the seats customers pay for get used. This serves both churn and NRR.

The second KR matters because it targets the accounts whose renewal decision is being made now.

Admin. Objective: every new customer has learners in their first two weeks. This serves churn.

The HRIS sync KR turns the integrations we shipped into usage. It also addresses the 7 accounts that left for their HR system's bundled LMS.

Growth. Objective: expand where usage proves value, and stop seat losses at renewal. This serves NRR.

Growth should focus expansion on accounts above a usage threshold, to be agreed with Learner app. Q3 showed that prompting low-usage accounts to upgrade doesn't work.

5. How these add up to the company goal, and where they don't

Churn (3.4% → 2.5%). This works through two levers:

• Q4–Q1 renewal accounts. Contracts are annual, so churn this quarter is mostly decided by how accounts used us over the past year. The only lever with a near-term effect is raising usage in accounts renewing soon. That is the Learner app's second KR.
• New-account onboarding. Admin's onboarding KRs act on new accounts, which won't come up for renewal for a year.

To illustrate the size of the onboarding effect: suppose 20% of accounts currently reach a first learner within 14 days, and those accounts churn at one third the rate of the rest. Moving that share to 50% would cut churn from 3.4% to about 2.6%. That only holds once the whole customer base has passed through the new onboarding, and only if the relationship is causal.

Honest read: we will not reach 2.5% churn in Q4. Admin's onboarding work is what gets us there in 2025.

NRR (102% → 108%). NRR gains come from two places: fewer churned and contracted seats (Growth's seat retention KR, plus the Learner app's usage work) and more seats added (Growth's expansion KR).

I can't yet show the arithmetic that closes the 6-point gap. That needs Finance's figures for revenue up for renewal and average price per seat. Even with the 10,000 seats target, I expect Q4 to land nearer 104–105% than 108%.

The remaining 6 churned accounts don't map to these KRs, though the HRIS work partly addresses the bundled-LMS losses:

• Budget cuts (9 accounts) need commercial responses, such as flexible tiers.
• Content fit (5 accounts) belongs to the Content team. Their Q4 KR should be usage of newly published courses, not the number of courses published.

6. Decisions I need from you

1. Approve the four scoring rules, and correct the 0.81 figure with the CEO.
2. Discuss the company targets with the CEO. I suggest keeping 108% NRR and 2.5% churn as the year-end destination, with Q4 checkpoints of 104–105% NRR and 3.0% churn, so the scorecard tells the truth.
3. Ask Finance and Data to deliver the TBC baselines and the NRR arithmetic by the end of week 2. I'll lock the targets the same day.