All 12 systems · System 11
Paid acquisition engine
A paid acquisition engine buys controlled experiments in audience, problem framing, creative, and offer, then scales only combinations that produce retained economic value. It fits businesses with a proven activation path, sufficient gross margin, reliable attribution, and enough conversion volume to distinguish signal from platform noise.
Causal engine
Form a specific audience-message-offer hypothesis → buy a bounded amount of qualified attention → carry message continuity through the landing page → measure activation and downstream value by cohort → cut weak combinations and diagnose the constraint → produce new creative from the learning → increase spend gradually while CAC, payback, and retention remain inside guardrails.
Preconditions
- The product converts and retains at least one identifiable audience without paid traffic
- Click, lead, activation, revenue, refunds, and gross margin can be joined at the cohort level
- A realistic CAC ceiling and payback window are defined before campaigns launch
- The founder can produce and test multiple substantive creative angles, not cosmetic variants
Anti-patterns
- Increasing budget because click-through rate is strong while activated-user CAC is unknown
- Sending every audience to a generic homepage that breaks the ad's promise
- Changing audience, creative, offer, and landing page simultaneously so no lesson survives
- Judging campaigns before the conversion window closes or scaling a short-lived winner too quickly
Solo-founder translation
Each week, spend one capped $200 budget on a single audience-message-offer hypothesis with two meaningfully different creatives and one matching landing page. Review individual conversions, interview at least one activated and one unqualified lead, then write the next test from the observed objection rather than platform suggestions. Measure qualified cost per click, activated-user CAC, cohort retention, payback, and spend that meets your guardrails; do not scale on leads alone.
$200 paid learning experiment
$200 paid learning experiment
Hypothesis
Offer and destination
Test cells
Keep audience, offer, bidding, and landing page fixed so the creative angle is the tested variable.
Budget and timing
Decision rules
Scorecard
View raw markdown
# $200 paid learning experiment
## Hypothesis
For independent bookkeeping firms with 3–15 employees, the message **“Finish month-end client updates without chasing five spreadsheets”** will produce activated trials below a $100 CAC because the audience already pays in staff hours for the delay.
## Offer and destination
Offer a 14-day trial preloaded with a month-end update template. Send traffic to a dedicated page that repeats the ad promise, shows the finished update, names the 15-minute setup requirement, and uses **Create your first update** as the only primary CTA.
## Test cells
1. **Creative A — Cost:** screenshot of the five-source reconciliation with the headline “Your update is late before you start writing.”
2. **Creative B — Outcome:** 30-second screen recording showing source import through client-ready update.
Keep audience, offer, bidding, and landing page fixed so the creative angle is the tested variable.
## Budget and timing
- Total budget: $200 over seven days.
- Split: $100 per creative.
- Do not edit during the first $50 per cell unless tracking or delivery is broken.
- Allow seven additional days for activation and paid conversion attribution.
## Decision rules
- **Kill:** zero qualified landing-page sessions after $50, or zero activations after $100 per cell.
- **Iterate:** activations occur but CAC exceeds $100; interview converters and drop-offs to locate the mismatch.
- **Repeat:** at least two activations and projected payback under six months; rerun with one new creative before increasing budget.
- **Scale:** two consecutive cohorts meet CAC and day-30 retention guardrails; raise spend no more than 30% per week.
## Scorecard
Record spend, qualified sessions, activation count, activated-user CAC, day-7 retained users, paid conversions, gross-margin payback, and the exact customer language learned. Cheap clicks and raw leads are diagnostic metrics, never the win condition.