Playbook — Sales

You work prospects cold-to-close. The platform's job for you: walk in knowing their competitive landscape, and turn a one-line question into a full meeting-prep read in ~60 seconds.

Your front doors

  • Roam — the daily driver on the move: name a business, get a rank read.
  • HubSpot card — once a deal exists, the brief is precomputed on the record.
  • Claude Code skills/prospect, /proposal, /area-map, /insites, /seo-gap-audit.

Hero flows (the gold patterns)

Goal Prompt
60-second rank check "How does [business] rank for [keyword] in [town]?" → 25-point SERP grid + rank summary + top competitors
Competitor ID "Identify three primary local competitors to [business] in [town]" → then "enrich the top three" (services, photos, FCR-client flags)
Cold meeting prep "Meeting a [trade] in [town] tomorrow — what should I know?"
Market read "Prospect intel for [trade] in [county]" — similar FCR-built sites, ads terms + CPC, keyword volumes, area intel, review priorities
Area snapshot "[Town]" — just the name — triggers the area map (demographics + reachable audience) to show in the meeting
Rank check / publish "Run an LRC for [business] in [town]" → "publish the map" for the client artefact

What's new since the v1 deck

  • HubSpot card + deal brief — the moment a deal is created, the rep has the full prospect picture on the record (GBP, website crawl, similar paying clients, similar past deals).
  • Maps & LRC stack — the FCR SerpAPI grid is canonical; Discovery (Alpha) is the stepped builder; /prospect is the multi-grid meeting-prep flow. See ../../maps-and-lrc.md.
  • Greenfield framing — for a brand-new, digitally-invisible prospect, the advisor now leads with the opportunity (build GBP → SitePro → SayMore → SEO), not "no data."
  • Proof points are honest — "similar clients" are split from free directory listings; only paying clients are shown as clients.

Don't waste the tool

  • New business = new grid (cache is target-scoped; a mismatched publish is refused).
  • Vague ask = thin answer — name the timeframe, surface, and the decision.

Full prompt library: ../../AI_ADVISOR_GUIDE.md.


Customer experience, retention & voice

(Folded in under Sales — flat org.) Beyond winning the deal, the platform helps you keep the relationship and learn from every win and loss across the book.

Want How
Why are we winning/losing a segment? extract_deal_patterns / "what's killing [category] renewals?" — recurring win + loss themes, backed by verbatim rep notes (never the dishonest closed-lost dropdown), with a shareable /deal-patterns/{slug} report
Reviews & reputation /gbp-check, reviews data, NPS gold-standard clients (proof points by county+category)
Retention risk suspensions, DEA/Setup expiry, zero-conversion accounts, health scores in the AM Portfolio
The approved voice 15 curated case studies in the Commercial Director's own voice (cited verbatim, never paraphrased); the email-template tiers (personal → team → house fallback)
What customers care about the CATEGORY_CUSTOMER_PRIORITIES / CATEGORY_REVIEW_PRIORITIES inputs feeding the keyword KB

The guardrails are the point: the advisor refuses to invent a case study, paraphrase the approved voice, or treat phone-tap "conversions" as leads without the caveat — the refusals are what make the answers trustworthy.

How to update case studies / templates: ../../data-feeds-and-knowledge.md.

FCR Dashboard documentation · generated from docs/ · keep counts verified, not guessed.

Ask the docsRAG over this site
Ask anything about the FCR Dashboard platform — architecture, BigQuery, the worker routes, billing rules, the LRC stack, scoring… Answers are grounded in this documentation, with source links.
How does the deal-brief refresh work? Which routes are Worker vs n8n? How is account health scored?