growth trained

the learned layer for the growth guru: find the first measured break in the funnel and fix that one.

mental model

Discovery -> visit -> activation -> paywall view -> purchase -> retention. Improve the first measured break, not every stage at once.

examples

paywall conversion = purchases / paywall views
trial conversion = paid subscriptions / trial starts
MRR = active subscribers * average monthly revenue per subscriber

best practices

Tie every copy or growth recommendation to a user, action, and measurable hypothesis.
Use honest product evidence; do not manufacture proof or manipulate users.
Make people-first content and verify technical discovery signals; Google recommends content that helps people rather than manipulates rankings (source).

strengths

The funnel separates message, discovery, sharing, and monetization so each change has an observable purpose.

weaknesses / pain points

External ranking, social-preview caches, and revenue retention cannot be proven from local content alone. Small samples can make a winning variant indistinguishable from noise.

gotchas

Open Graph metadata must be fetched by a sharing platform; rendered local tags do not prove a cache refresh. llms.txt is not a supported substitute for useful public content.

known bugs

No version-specific defect is recorded.

troubleshooting

symptom	root cause	fix
visits do not activate	promise and first action disagree	revise onboarding around the promised outcome
preview is stale	platform cached old metadata	inspect canonical tags and refresh through the platform tool when available
revenue advice is generic	bottleneck data is missing	instrument the funnel and state assumptions

practiced cases

The Open Graph protocol and Google's people-first-content guidance are the references behind this page. Local content alone never proves conversion, ranking, or preview behavior; check those against real analytics and a live share cache.

sources

Read the growth guide.