Marketing
KPI / OKR Review#KPI#OKR#retroMarketing KPI Quarterly Review · Signal vs Noise
Marketing KPI reviews typically die on 'which metric matters'. Use north star + leading + lagging + signal vs noise lens. Stop letting the dashboard drive you.
Pain addressed · Marketing quarters bury you in data, but the conclusion you ship is usually 'channel X is up' — leadership still can't tell whether the north-star metric is healthy.
Marketing KPI Quarterly Review · Signal vs Noise
You're my marketing KPI quarterly review partner. Help me synthesize the quarter's data into a decision-ready retro.
# This quarter's metrics (north star + 3-5 supporting)
{paste_metrics_with_data}
# Marketing actions this quarter (campaign / channel / message changes)
{marketing_actions_this_quarter}
# Business context (product launches / market shifts / competitor moves)
{business_context}
# Output five sections
## 1. North star verdict (50 words)
Up or down? Is the cause our marketing or the market? Separate marketing-driven from market-driven.
## 2. Leading vs lagging audit (50 words each)
- Leading (CTR / engagement / interview show-rate): how much did it move? Where's the signal?
- Lagging (LTV / payback / revenue): how much? Does it match the leading?
- Key finding: which leading metrics didn't translate to lagging?
## 3. Signal vs noise (3, 60 words each)
What's real signal vs noise:
- e.g. "BFCM week conversion spike" = seasonal noise, not signal
- e.g. "new channel held 10% conversion across week 3" = real signal
Test: multi-week consistency + unrelated to external events.
## 4. One right bet, one wrong bet (60 words each)
- Right bet: highest-ROI action with attribution
- Wrong bet: biggest budget/time waster. Why you bet at the time, what hindsight says.
## 5. 3 things for next quarter (30 words each)
- One DOUBLE-DOWN (v2 of the right bet)
- One STOP (the wrong bet)
- One EXPLORE (small bet from a new signal)
# Boundaries
- Don't take all credit (acknowledge market-driven moves).
- Don't hide the wrong bet.
- North star claim must have attribution, not just "numbers went up".Open directly on your favourite AI
One click copies the prompt and opens the platform in a new tab — just paste (⌘/Ctrl + V). Recommended platforms are ordered by content fit.
Workflow · 5 steps
- 1
End of quarter: dump north star + 3-5 supporting metrics + marketing actions + business context into one block.
- 2
Run in Claude (best at attribution reasoning) or DeepSeek. Fill the 3 placeholders.
- 3
Signal vs noise is the highest-value section. Too many marketers mistake seasonality for skill — push the model to cite specific evidence.
- 4
Right bet + wrong bet must both be there. No wrong bet = you're not reflecting.
- 5
Bring next-quarter's 3 actions to the CMO standup as input for next-Q planning.
Verify before you ship
AI's "almost right" is the #1 pain. Tick these off so reviewers can't find the obvious holes. (Checkbox state stays local — we don't track it.)
Why this prompt works
This prompt isn't a generic “write me a KPI / OKR Review”. It folds in the concrete context a Marketing actually faces (target reader, info density, deliverable format). LLMs deliver an order-of-magnitude better answer when they get role × scenario × constraints together — they can make the right tradeoffs about what to spotlight and what to cut.
When to use
Best moment: you know roughly that you need to do a KPI / OKR Review, but you're stuck on “how do I even ask the AI?” Muscle memory has no template. Copy this card, tweak 2-3 fields per the workflow, and get a first revisable draft in 30 seconds.
Common pitfalls
- Send without tweaking placeholders · the draft reads as default-GPT and your reviewer spots it in 3 seconds.
- Skip the verify checklist · “almost right” failures usually hide in a thing you assumed the model handled but it didn't.
- Stop after the first answer · a single follow-up like “make section X tighter / more formal” usually pushes a 70 → 90.
Variants & extensions
Want to use this card more aggressively? Three extensions:
- Swap languages: both EN/ZH prompts ship in the card — use the EN version when shipping to a Western audience.
- Swap platforms: the same prompt has slightly different taste on ChatGPT / Claude / Kimi. The recommended-platform pill marks the best fit.
- Stack the checklist: paste the verify checklist back into the chat and ask the AI to self-audit — error rate drops sharply.
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