Local lead prospector

DM 1 — Web Client Prospecting

Finds and scores local businesses that (a) NEED a website and (b) can AFFORD one, then writes decision-ready leads to Notion for cold calling and emailing. Core offer is a website; booking, chatbot, automation and analytics are add-ons flagged only from a free signal.

Goal: a short list worth calling, each with a phone number, a ready hook, and the gap already filled in. Not volume.

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Inputs

• Location (required) — town or county (e.g. "Mallow", "Galway").
• Business type (optional) — one trade to focus on. If omitted, sweep the category list below.
• Country (optional, default Ireland) — see Portability.

Ideal client

Established local SMEs with real revenue but a weak or absent web presence. High NEED × high ABILITY-TO-PAY. A busy 200-review clinic on a Facebook page beats a brand-new sole trader every time.

High-value categories (priority order): plumbers, electricians, builders, roofers, painters, solicitors, accountants, estate agents, dentists, physios, salons, barbers, beauty clinics, spas, gyms, vets, cafés, restaurants.

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Token budget — tick this before every fetch

1. Discovery fetches used:  __ / 2 max
2. Enrichment fetches used: __ / 6 max, and __ / 1 per lead
3. Confirm queries used:    __ / 3 max
4. Add-on fetches:          MUST be 0
5. CRO / registry fetches:  MUST be 0 unless the user explicitly asked

Once enrichment hits 6, stop enriching and write the rest on free signals. COOL and SKIP leads get ZERO enrichment fetches.

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Search pipeline

1. Build URL list. From the location, build Golden Pages URLs goldenpages.ie/<category>/<town>-<county>/. One category if a type was given, else take enough from the priority list for ~20–40 candidates. FETCH: no.

• Slug quirks: a city in its own county doubles up — Cork city is cork-cork-county (not cork). Categories are plural nouns (barbers, solicitors) but some don't exist (gyms 404s — try fitness-centres). If a URL 404s, adjust the slug or fall back to a DuckDuckGo "<category> <town>" search; don't spend more than one retry.

2. Discovery fetch. WebFetch ONE Golden Pages results page. Parse ~20 rows: name, phone, address+eircode, category, description, star rating, review count, and whether a Website link is present. Socket closes? Run permission-bypass-apple once, retry. Do NOT fetch google.com/search, Cylex, Yell-IE, CRO or social pages. FETCH: yes (1–2). STOP: after 1–2 pages.

3. Free filter. DISCARD rows with a modern custom-domain site (Modern-skip; log as deduped). KEEP: no link (None), only facebook/instagram (Facebook-only), only a listing/booking platform (Platform-only), http/stale/builder-subdomain (Outdated/Basic). FETCH: no.

4. Free score + tier. Score every kept row (see Scoring). Assign HOT/WARM/COOL/SKIP. FETCH: no. STOP: COOL and SKIP get no enrichment — write them to Notion now.

5. Confirm (WARM+ only). Enrich each WARM/HOT lead once:

• If Google Places is set up (a key in GOOGLE_PLACES_API_KEY or ~/.claude/google_places_api_key.txt), call places_lookup(name, area) (see SETUP.md). One call returns rating + review count + website + phone — set Review Count from it, confirm/flip Website Status, set Scoring Confidence = high, then recompute Priority Score and Tier. This is what lets a lead reach HOT.
• If no key, run one html.duckduckgo.com/html/?q=BusinessName Town ireland query (no quotes) to confirm the no-website guess and grab an email only if a snippet shows one. Leads stay review-blank (cap WARM). If review data would materially change the ranking, print one line and offer to open the console: "No Google Places key — enable it at https://console.cloud.google.com/apis/library/places.googleapis.com and make a key at https://console.cloud.google.com/apis/credentials (full steps in SETUP.md). Want me to open those pages?"

FETCH: yes (1 per lead). CAP: 3 confirm/enrich lookups per run — if more than 3 qualify, do the top 3 by score and set the rest to Scoring Confidence = low.

6. Promote (HOT only). Fetch a homepage ONLY when the lead is HOT AND has a real custom-domain https site AND snippets are unclear on redesign-worthiness. Extract six things: viewport tag, http-vs-https, real copyright year, services+contact/booking nav, builder fingerprint, dated-vs-current. Set Fetched=yes, then recompute Priority Score and Tier before writing. Never fetch None/Facebook-only/Platform-only leads or any WARM/COOL/SKIP lead. FETCH: yes (counts as this lead's 1 enrichment). STOP: one homepage, six items, done.

7. Add-on flags. Map Sector → Add-on Flag from the table. FETCH: no — never query for add-ons.

8. Dedupe & write. Query the DB once for existing Business Name + Phone. Dedupe on phone, then eircode, then name+town. Write every non-duplicate kept lead (including COOL) with add_prospect; omit unknown fields. Print the summary. FETCH: no (one dedupe query).

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Scoring

NEED (cap 15) — from Website Status

Website Status	Points
None (no website)	+8
Facebook/Instagram-only	+7
Platform-only (Fresha/Treatwell/JustEat/Yelp)	+6
Outdated (http, stale ©, builder subdomain)	+4
Basic (custom domain, thin/dated)	+2
Confirmed no mobile viewport (homepage fetch)	+4
Confirmed no lead-capture form (homepage fetch)	+2
Modern-skip	disqualifier

ABILITY-TO-PAY (cap 15) — revenue proxies

Signal	Points
Review count 200+	+8
Review count 80–199	+5
Review count 30–79	+2
Review count under 30 (confirmed)	+0
Review count BLANK	+0, set Scoring Confidence = low, cap tier at WARM
Rating ≥4.3 AND ≥50 reviews	+2
Premium sector (dentist, clinic, solicitor, accountant, jeweller, wedding venue)	+3
Higher-ticket sub-sector (wedding venue, cosmetic clinic, private healthcare)	+2
Established (since 19XX / over N years / family-run; 200+ reviews implies it)	+3
Multiple locations (bank only once independence confirmed; else tag "confirm independence")	+3
Wealthy catchment (affluent town/eircode)	+2
Paid/enhanced Golden Pages listing	+3
Commercial/B2B trade descriptor	+2

Priority Score = NEED + ABILITY (each capped at 15; total 0–30). This is the sort key and is never blank. If a need signal is not fetch-confirmed, use the table value as-is and set Scoring Confidence = low. No half-math, no other caps.

Tiers

HOT requires BOTH:
  (a) Priority Score >= 15, AND
  (b) at least ONE of: Review Count >= 80  /  confirmed 2+ locations  /  (premium sector AND established)
  If (b) is false, cap at WARM.  (In practice HOT = a no-website business with 80+ reviews.)
WARM = score >= 11   (also the ceiling for blank-review leads)
COOL = score >= 6    (or any real business we can't confirm — still written)
SKIP = score < 6, or a disqualifier

Disqualifiers

• HARD SKIP (always): modern mobile https site with booking/lead-capture (offer ops upsell only); dormant/closed.
• SOFT (keep as WARM/COOL, tag "confirm independence"): looks like a chain/franchise but the name is ambiguous. Only a confirmed chain is a hard SKIP.
• Sole trader with no site, no reviews, no ability signal → COOL/SKIP, never HOT on need alone.

Missing data

Never drop a lead for missing data. Blank reviews → +0, confidence low, cap WARM. Missing sector → no fetch, leave Add-on Flags empty. Missing years/staff/catchment → +0, never a penalty. Phone AND email both missing → route to Needs Contact Info view. Only true duplicates and confirmed Modern-skip sites are excluded (park SKIPs, never delete).

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€ Budget (ability-to-pay only — NOT call order)

A separate select column showing likely deal size. Priority Score stays the sort key. Deterministic from Review Count + Sector:

R = Review Count (blank = MISSING).  premium = Sector in {Professional, Health/Fitness} (reliably high-ticket).
1. R >= 200                    -> €€€€
2. R >= 80                     -> €€€€ if premium else €€€
3. R 30–79                     -> €€€  if premium else €€
4. premium, few/no reviews     -> €€€   (a premium practice is high-ticket even with no review data)
5. non-premium, R MISSING      -> €€
6. non-premium, R < 30         -> €
Then ONE optional +1 bump (max once, never past €€€€) if Notes contains any of:
  "multi-location","2 locations","3 locations","branches","since 19","since 20","established","family-run".

Meaning: € starter/price-sensitive · €€ standard 4–6 page build · €€€ multi-page + add-ons, tailored proposal · €€€€ premium/high-ticket, top package. (Beauty/Wellness is NOT auto-premium here — a barber and an aesthetic clinic differ; reviews lift them.)

Golden Pages carries NO review counts (every listing shows "0 stars"). So Review Count is usually BLANK from discovery, ability leans on premium sector + established/paid-listing markers, and most Golden Pages leads cap at WARM. The confirm query (step 5, WARM+ only) is where a real Google review count/rating can be grabbed. To get reliable review data (and let leads reach HOT), plug in the Google Places API — one-time, optional, see SETUP.md.

Website Status → pitch (short, sayable on a call)

Status	Say
None	"You've no site yet, so one page turns your reviews into booked jobs."
Facebook-only	"You don't own your Facebook audience. Your own site keeps those customers with you."
Platform-only	"The platform owns your bookings and takes a cut. Your own site keeps the repeat business."
Outdated	"Your site is dated and losing you mobile visitors. A refresh sorts that."
Basic	"Your site isn't pulling its weight on mobile or booking. I can make it book jobs."
Modern-skip	Not a web lead. Automation/analytics upsell only.

Add-on flags (Sector → flag, no fetch, zero points)

Sector	Add-on
Beauty/Wellness, Health/Fitness, Hospitality/Food	Booking
Professional	Chatbot/Lead-Capture
Trades	Automation
Retail	Analytics

Best time to call (by sector — caller guidance)

Trades: early (8–9am) or after 5pm. Beauty/Health: mid-morning Tue–Thu. Professional: 9–11am Tue–Thu. Retail: mid-morning/early afternoon. Hospitality: 2–4pm.

Hook

Write one sayable line from the pitch table, add the owner's first name if it's free, prefix with » . One line only.

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Notion integration

Credentials: the Notion token + database ID are not stored here. prospect.py loads them from NOTION_TOKEN / NOTION_DB_ID env vars or ~/.claude/prospecting_config.json. First-time users run the one-time setup in SETUP.md. Never hardcode a token in this folder.

Node.js is EPERM-blocked in the Apple sandbox. Use Python that writes each payload to a temp file and runs curl -d @file (also handles apostrophes). Never inline JSON in a bash string.

Auto columns: Business Name (title) · Priority Score (number) · Euro Budget (select €/€€/€€€/€€€€) · Tier (select) · Scoring Confidence (select) · Sector (select) · Area (select) · Phone · Email · Website · Website Status (select) · Add-on Flags (multi-select) · Hook · Source Link (url, mandatory) · Decision-maker Name · Review Count (number) · Reviews · Notes · Status (always "Not Contacted") · Fetched (checkbox). Manual columns: Stitch Link (Google Stitch prototype URL, left blank by the script) · Last Contacted · Call Notes. Filled by DM_2: Draft Email (a click-to-open Gmail compose link) — run DM_2's refresh_draft_links.py after a prospecting run to populate it for leads that have an email.

Stored helpers — import, don't re-type

All scoring, € budget, hooks, dedup, Places enrichment and the Notion write live in prospect.py (in this skill folder). Import it — never paste this logic into a run:

import sys, os; sys.path.insert(0, os.path.expanduser("~/.claude/skills/local-lead-prospector"))
from prospect import add_prospect, existing_keys, places_lookup

names, phones = existing_keys()                 # dedup once per run

# For each business you observed, pass the FACTS — add_prospect scores, tiers,
# picks the € band, writes the hook, and creates the Notion page itself:
ok, meta = add_prospect(
    name="Example Dental Practice", sector="Health/Fitness", area="Yourtown",
    website_status="None", source_link="https://www.goldenpages.ie/dentists/<town>-<county>-county/",
    phone="021 555 0100", review_count=None, rating=None,
    established=False, multi_loc=False, commercial=False,
    notes="No website — dental practice")        # -> meta = {score, tier, euro, confidence}

add_prospect args: name, sector, area, website_status, source_link (required) then optional phone, email, website, review_count, rating, reviews_text, dm_name, notes, established, multi_loc, commercial, addons, tier_override. Skip a category by matching names/phones from existing_keys().

Enrich with real Google reviews (needs Places key — see SETUP.md)

After writing leads, pull live ratings/review counts so leads can reach HOT:

python3 ~/.claude/skills/local-lead-prospector/enrich.py          # Places lookup + re-score
python3 ~/.claude/skills/local-lead-prospector/enrich.py --retier # re-score from stored data only (no API calls)

enrich.py guards against wrong-business matches (skips rows whose Places phone differs). Dedupe first with one /v1/databases/{DB}/query (body {}), collect existing Business Name + Phone, skip case-insensitive matches. New Area towns auto-create as options on first write.

Views to set up in Notion (one-time, manual — the API cannot create views)

1. Call List (daily driver) — filter Status = Not Contacted AND Phone is not empty AND Tier ≠ SKIP; sort Priority Score ↓, Review Count ↓; group by Area; show Business Name, Phone, Euro Budget, Hook, Notes, Tier.
2. Needs Contact Info — filter Phone is empty AND Email is empty AND Tier ≠ SKIP; sort Priority Score ↓.
3. Cold Email — filter Email is not empty AND Phone is empty AND Tier ≠ SKIP; sort Priority Score ↓; show Business Name, Email, Euro Budget, Hook, Stitch Link.
4. Call Follow-up — filter Status is Contacted OR Interested OR Meeting; sort Last Contacted ↑; show Business Name, Phone, Email, Last Contacted, Call Notes, Stitch Link.
5. Pipeline — board grouped by Status; sort Last Contacted ↓, Priority Score ↓.

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Output (after writing)

Print a table sorted by Priority Score: # · Business · Sector · Tier · € · Score · Website Status · Phone · Reviews · Hook. End with ✓ X leads added (H HOT / W WARM / C COOL), Y skipped (duplicates), Z parked (SKIP). Fetches: D discovery + E enrichment.

Next step

Pick a lead and run cold-email-drafter to draft the email and (optionally) create a Gmail draft.

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Portability (non-Ireland)

Default is Ireland. For another country, swap the discovery source, keep everything else:

• UK: Yell.com category+town pages; Companies House for established-status.
• Anywhere: Google Maps/Places (name, phone, website-present flag, review count, rating in one view) — heavier per fetch, so lean harder on the free filter. Review-count bands and the affluent-area list are Ireland-tuned; adjust per market.

What not to do

• Don't chase volume — a short scored list beats a long dump.
• Don't exceed the fetch budget — write the rest on free signals.
• Don't deep-scan sites, hunt emails with dedicated queries, or run CRO by default.
• Don't discard a lead for missing data — park SKIPs, never delete.