The Lead-Scoring Model

Worked example below uses an invented business, city, and phone number for teaching only — not a real lead, not drawn from any real list.

---

Calling down a list in the order it happens to export is calling in random order. A score fixes that — but only if you understand why it's built the way it is, because a score you don't trust is a score you'll quietly stop using the first time it disagrees with your gut.

#1. The four things being weighed, and why

The model sums four factors that a lead-generation professional actually weighs, then subtracts negatives:

SCORE (0–100) = PAIN + VALUE + FIT + REACH − NEGATIVES

• PAIN (up to ~32 points) — how strong is the web-status signal itself. This is weighted highest because it's the most direct evidence of the actual problem you solve. A business with a noindex tag or no site at all has a provable gap; a business with a merely dated-but-functional site has a much softer one.
• VALUE (up to 30 points) — what does this category typically pay. A dental or legal practice supports a $1,500–3,000 build; a barber shop supports a $997 one. This isn't about which business deserves more — it's about matching your build effort to what the deal is actually worth, which is the entire logic behind the volume-play/value-play split in the next lesson.
• FIT (flat 20 points) — is this an in-market category you're actually set up to serve. Kept flat and simple on purpose: it's a yes/no gate, not a spectrum, so it doesn't need graduated scoring.
• REACH (up to 15 points) — does a local, direct number exist. A lead you can't actually reach a decision-maker through is worth far less regardless of how strong the other three factors are — reachability isn't a nice-to-have, it's the gate every other point has to pass through.

Grade bands: A = 85+ (build the demo before calling — call this week) · B = 70–84 (full call + email + SMS sequence) · C = 55–69 (light nurture only) · D = below 55 (skip).

#2. The point table

PAIN (web status)                          VALUE (category ability-to-pay)
  No real site (placeholder/social)   28      Dentist / medical / legal      30
  Facebook-only                       30      Plumber / trades / auto        18
  Outdated real site                  32      Restaurant / food              16
  (noindex, or stale by the checklist  in §3) Barber / nails / salon         12
  Aging but real site                 20
  Dated but maintained template       12
  "No link shown" on one directory    20    FIT   = 20 flat (in-market category)
  Modern, responsive site              0    REACH = 15 if a local direct number exists, 3 if toll-free/out-of-area

NEGATIVES: modern site already in place −40 · no working contact method −15 · known franchise −25

Notice "No link shown on one directory" scores lower (20) than "Facebook-only" or "placeholder page" (28–30), even though on the surface all three mean "no real site." That's the accuracy caveat from Module 2 built directly into the scoring, not just mentioned as a warning: a single directory failing to show a link is the least reliable of the three signals, so it earns fewer points until you've personally verified it.

#3. The outdated-site checklist (for anything that already has a website)

Each signal below is a proxy for something a real visitor — or Google itself — would actually notice, which is why it's worth checking rather than eyeballing a site and guessing "looks old":

A site failing the viewport check or carrying noindex or showing a copyright year three-plus years old counts as Outdated = Yes. Free tools (a mobile-friendliness checker, a page-speed checker) do this per-URL without writing anything yourself; at real volume, most scraping platforms return the site URL so you can run a small script over the whole list at once.

#4. Worked example — two invented leads, scored step by step

Lead 1 — "Marchetti's Auto Detail," a fictional shop in a fictional town. Facebook page only, no real site. Auto-services category. A local direct number on the listing. One recent review, no owner replies to reviews, not running ads, 34 total reviews.

PAIN   (Facebook-only)              = 30
VALUE  (auto/trades)                = 18
FIT    (in-market category)         = 20
REACH  (local direct number)        = 15
ENRICH (one recent review, +5;
         no owner replies, +0;
         no ads running, +0;
         under 100 reviews, +0)     =  5
NEGATIVES                           =  0
──────────────────────────────────────
TOTAL                               = 88  →  Grade A

An 88 clears the A threshold — build this one's demo before you dial.

Lead 2 — "Ridgeline Barber Co.," also fictional. No website link shown on a single directory listing (unverified signal), barber category, a toll-free number is the only contact listed, no recent review activity, no ads.

PAIN   ("no link shown," capped)    = 20
VALUE  (barber/salon)               = 12
FIT    (in-market category)         = 20
REACH  (toll-free/out-of-area)      =  3
ENRICH (nothing recent to add)      =  0
NEGATIVES                           =  0
──────────────────────────────────────
TOTAL                               = 55  →  Grade C, right at the boundary

A 55 lands exactly on the C/D line — light nurture at most, and worth the 20-second Google verification from Module 2 before you spend any real time on it, precisely because its PAIN score rests on the least reliable signal in the model.

#5. The optional sharpening layer

Once you're pulling review data alongside the basics, add: a recent review (+5), the owner replying to reviews (+5), the business running paid ads (+6), and 100+ total reviews (+4). Review activity is worth adding because it now outranks a bare website check as a "this business is alive and paying attention" signal — an owner who replies to reviews is an owner who'll answer a text about their website, too.

Score =
  SWITCH(WebStatus, "none",30, "social",30, "placeholder",28,
                    "outdated",32, "aging",20, "maintained",12,
                    "modern",0, 20)                                    // PAIN
+ SWITCH(CategoryTier, "high",30, "midtrade",18, "food",16, "low",12, 15) // VALUE
+ 20                                                                     // FIT
+ IF(LocalDirectNumber, 15, 3)                                          // REACH
+ IF(RecentReview,5,0) + IF(OwnerReplies,5,0) + IF(RunsAds,6,0)
    + IF(Reviews>=100,4,0)                                             // ENRICH
- IF(ModernSiteAlready,40,0) - IF(Franchise,25,0) - IF(NoContact,15,0)  // NEGATIVES
→ cap 0–100