Value Stories
How diagnostic-as-berley creates value. Each story is an intent flow: a scenario triggers an intention, actions produce artifacts, outcomes prove value.
Does the site render from data?
Market-leader quality marketing site from a content brief and theme config — not custom engineering.
Content brief is ready but every new venture site requires weeks of custom React engineering — typed data objects sit in a doc while developers hand-build pages.
Render a market-leader quality marketing site from a typed content brief and theme config, not custom code.
Standard marketing site producible from data, not custom code — matches market leader quality.
Site renders with fallback/placeholder text in required sections — means brief validation is broken. Sign-up form missing or non-functional.
Does the diagnostic create value?
Self-qualification that earns trust. Genuine insight, not a form disguised as value.
Lead gen forms convert at <10% because they demand contact info before giving any value — visitors bounce before the site earns trust.
A diagnostic that gives genuine insight first and earns self-qualification through value, not friction.
Self-qualification produces genuine value — completion rate >30% vs typical form completion at <10%.
Diagnostic accepts submission with 0 sections completed. Empty scores array returned. Summary shows only scores without recommendations — provides no genuine value.
Visitor completes the diagnostic and shares contact info, but scraped leads arrive with a name and nothing else — sales calls cold into unknown pain.
Every contact lands in CRM with full diagnostic scores, consent, and source so sales knows the pain before calling.
Every contact arrives with full diagnostic context vs scraped contacts with name + email only.
Contact created with null diagnostic_scores — pipeline drops context. Contact created without consent flag — legal exposure. Contact created without source field — multi-site attribution impossible.
Does lead quality improve?
Sales team rates leads higher than traditional lead gen. Per-site analytics prove the funnel.
10+ diagnostic leads sit in CRM but sales sees a flat list with no way to distinguish high-pain prospects from tire-kickers — CPL doesn't justify the contact time.
Filter leads by diagnostic score, highest-pain section, and source site so sales spends zero time on unqualified contacts.
Sales team spends zero time on unqualified leads — quality rating >= 7/10 vs historical average.
All leads shown as flat list with no filtering. No source site filter — multi-site leads are mixed.
Media spend is split across sites but analytics aggregate everything — no way to tell which site's diagnostic converts and which bleeds budget.
Per-site event tracking with site_id attribution across the full diagnostic funnel.
Per-site berley performance measurement — optimize spend by conversion stage vs aggregate metrics with no per-site attribution.
Events fire without site_id — cross-site analytics impossible. diagnostic_start fires but diagnostic_complete never fires — funnel is broken.
Does the generator scale?
Site N+1 requires zero new components. Configuration, not engineering.
Second client signs up but building their site means another multi-week engineering project — the berleytrails patterns are trapped in one app with no extraction path.
Run a generator that produces a deployable marketing site from config with zero new components.
Marginal cost of site N+1 approaches zero — configuration not engineering vs weeks of custom work per site.
Generator creates files that fail to compile. Requires manual file edits after running. New React components created in apps/stackmates/ — site-specific code leaked.
Generated site is ready to ship but deploying it triggers a redeploy of the first site — coupled infrastructure means one change risks both clients.
Independent site lifecycle where each site deploys, scales, and dies on its own domain without affecting others.
Independent site lifecycle — each site deploys, scales, and dies alone vs coupled deployments.
Deploying stackmates redeploys berleytrails — sites are coupled. stackmates uses berleytrails theme — theme isolation failed.
HRV pilot lead quality rating <5/10 after 30 leads. If the diagnostic doesn't produce leads sales teams prefer, the model is wrong. Do NOT extract the generator until berleytrails proves the pattern.
Who this is for
| Who | Job | Outcome |
|---|---|---|
| Business owner | Qualified leads who know their problem | Pipeline of pre-qualified prospects with consent |
| Media agency | Lead gen product that works | Revenue from CPL on qualified leads |
| Diagnostic visitor | Understand my situation | Genuine insight + clear next step |
| Platform team | Generate site in one command | Manual site creation = commissioning failure |
Questions
What happens when the generator produces sites that are technically correct but lack the craft that made berleytrails convert?
- Is "zero new components" the right constraint — or does it force every site into the same mold?
- At what scale does the generator pattern break — 10 sites? 50?
- If Sneakers can sell this to any advertiser, what prevents diagnostic quality from degrading as it scales?