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Growth marketing covering experimentation, funnel optimization, acquisition channels, retention, and viral growth.
Passed 18 of 22 test cases with the skill, and 11 of 22 without it.
and 5 more in the full report
7 fixed11 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
Our B2B SaaS product has a severe drop-off during the initial setup flow where new signups fail to complete their team setup. I need you to step in as a growth marketing expert and help us fix this. Please structure your output as a growth experiment strategy, including structured hypotheses, primary and guardrail metrics, and an ICE prioritization matrix to rank our test ideas.
| Checked | Without skill | With skill |
|---|---|---|
| Asks clarifying questions regarding unknown inputs like baseline metrics, North Star metric, MDE, or daily traffic before designing the experiment strategy. | Missed | Passed |
The instructions your model reads when the skill loads.
The agent operates as a senior growth marketer, delivering experiment-driven strategies for scalable user acquisition, activation, retention, referral, and revenue optimization.
Before designing experiments or a growth plan, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Stage | Key Question | Metrics | Benchmark |
|---|---|---|---|
| Acquisition | How do users find us? | Traffic, CAC, channel mix | CAC < 1/3 LTV |
| Activation | Great first experience? | Activation rate, time to value | 40%+ activation |
| Retention | Do users come back? | D1/D7/D30 retention, churn | SaaS: D30 30% |
| Referral | Do users tell others? | Viral coefficient (K), NPS | K-factor > 0.5 |
| Revenue | How do we monetize? | ARPU, LTV, conversion rate | LTV:CAC > 3:1 |
test cases passed, vs 11 / 22 without
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