Feature deep dive · Fixes
Each fix appears only when your own weekly data calls for it. An empty queue means you are winning — which costs an upsell and earns trust.
Short answer
Because the objection-buster answers the exact sentence the engine quoted — the fastest path from loss reason to corrected answer. A versus blueprint is powerful but slow; shipping the five-minute answer on Monday can move the following Monday cycle, while the blueprint is still in review. Time to value is the ranking function, not effort prestige.
Triggers. Each tier fires only on an observed condition: a forensic gap reason, a missing llms.txt, a passing-only mention, a competitor first-choice win, a deciding citation domain. No trigger, no task. The queue would rather be empty and honest than full and flattering.
Then we leave a marker. Generated assets use only observed crawl and citation facts; unverified pricing, counts or badges arrive as explicit placeholders you complete. A verification script fails the build if a zero-price offer template ever reappears — the fastest way to lose assistant trust is to be caught overstating.
The ladder
Width encodes relative effort; order encodes payoff speed.
The no-fabrication rule
Observed facts only. Placeholders for the rest. A build-breaking check enforces it — marketing cannot quietly reintroduce invented offers.
Answer + llms.txt
Entity schema
Versus blueprint
Outreach
A ≤45-word direct answer to the exact objection the engine raised, plus FAQPage JSON-LD.
Trigger · A forensic gap reason was extracted from an engine answer.
A complete /llms.txt file: proposition, capability matrix, pricing, key pages, contact.
Trigger · The AI Health Check finds /llms.txt missing.
Organization JSON-LD with sameAs slots and step-by-step placement instructions.
Trigger · Your brand is only mentioned in passing, or cautioned against.
An honest comparison page with a capability matrix, when-to-choose-each, and migration friction.
Trigger · A tracked competitor took first choice on a commercial query.
A non-promotional, affiliation-disclosing contribution draft for the source that decided the answer.
Trigger · A Reddit thread or review site was the deciding citation.
Proof
Marking done freezes the score. Next complete cycle writes the after-value.
Publish the answer, deploy the file, paste the schema — then mark done in the queue or via MCP.
Current visibility score locks as impactBefore. It cannot drift afterwards, even if the week is partial.
A real later snapshot writes impactAfter. Until then the action reads awaiting measurement — never a win.
Impact view shows before, after and delta per fix. Fixes that did nothing appear as plainly as wins.
Self-serve vs sprint
The queue is identical. Who publishes changes.
Your team copies assets from the queue. Best when someone owns publishing and unblocks quickly.
Our engineer implements all five tiers, seeds citation authority and reports lift per baseline. Best when tasks keep sliding.
Fix questions
Quoted verbatim via FAQPage markup.
Objection-buster FAQ in five minutes, llms.txt production asset in five minutes, entity disambiguation in ten minutes, versus blueprint in two hours, then ongoing citation authority outreach. Each fires only when its trigger is observed in your own data — an empty queue means you are winning.
No. Asset generation is bound by a no-fabrication rule: facts come only from observed crawl and citation data, and anything unverified is emitted as an explicit placeholder marker for you to complete. A verification script fails the build if a zero-price offer template appears.
You do on self-serve — copy the answer and its JSON-LD, deploy the file, paste the schema. On a managed sprint our engineer implements all five tiers, seeds citation authority and reports measured lift against each locked baseline.
Ship the smallest fix
The objection-buster is drafted from your own loss reason — copy it, publish it, lock the score. Fourteen days free.