Leadkaun

Lead Scoring Engine

How Leadkaun grades
every lead. A–F, in real time.

Not all leads are equal. Leadkaun scores every lead on three independent dimensions, Fit, Intent and Quality, and turns them into one grade with one action. Below is the real thing, not a diagram.

Sample lead

Textile exporter enquiry

Surat · replied on WhatsApp

ACall now

Fit

78/100

Intent

71/100

Quality

82/100

Total score81 / 100

All three scores clear the Grade A threshold, so this one goes to the top of the queue.

01The live product

Open a lead and see the score for real.

This is the actual product, not a video. It opens on a lead's page with its live Fit, Intent and Quality breakdown. Log a call or a WhatsApp reply and watch the grade and the Priority Queue re-rank.

LeadkaunLead3
PS

Priya Sharma

Sunrise RealtyWebsite formQualified

₹42L

Expected

Lead Score

Fit

33/40

Intent

22/30

Quality

26/30

A

Total 81/100 · Grade A needs Fit 65, Intent 60, Quality 60

Inquiry / Notes

Asked for pricing on WhatsApp

  1. Lead imported and graded

    on arrival

Details

Phone

+91 981000 100021

Email

priya@sunriserealty.in

Source

Website form

Assigned to

Aditya Rane

Added

14 Apr

First contact

not yet

Score Evolution

CImported and gradedon arrival
BReplied on WhatsAppday 2
ALatest signalnow

Quick answer

How does Leadkaun's lead scoring work?

Leadkaun grades every lead A–F in real time from three independent 0–100 scores — Fit (ICP match), Intent (live engagement, which decays when a lead goes silent) and Quality (data reliability). A published threshold matrix turns the three into one grade, Quality below 20 forces F, and each grade maps to a fixed next action.

02Anatomy of a grade

Three scores in. One grade, one action out.

The exact score bars a rep sees on a lead. Illustrative leads, real scoring logic.

Sample lead

Textile exporter enquiry

Surat

ACall now

Fit

78/100

Intent

71/100

Quality

82/100

Strong ICP match, replied on WhatsApp this morning, and the phone and email are clean. All three scores clear the Grade A bar.

Sample lead

D2C brand enquiry

Jaipur

CNurture

Fit

62/100

Intent

34/100

Quality

70/100

Good fit and usable data, but silent for a week so Intent has decayed. A nurture cadence, not a drop-everything call.

Sample lead

Web form, no company

unknown

FArchive

Fit

55/100

Intent

40/100

Quality

12/100

Looks average on Fit and Intent, but the phone number is invalid. Quality under 20 caps it to F, whatever the other two say.

The bar on each score fills toward 100. Quality below 20 forces Grade F, whatever Fit and Intent say.

03Three independent scores

Fit. Intent. Quality.

Each score is 0–100, independent and auditable. Together they determine the grade.

Score

Fit Score

0 – 100

How well the lead matches the ICP you set. It only moves when new firmographic information arrives.

  • Industry match30 pts
  • Geography20 pts
  • Business type20 pts
  • Role / decision-maker15 pts
  • Budget signal15 pts
Score

Intent Score

0 – 100

How engaged the lead is right now. It spikes on signals and decays with silence.

  • Source baselinebase
  • Call answered, interested+20 pts
  • WhatsApp reply+10 pts
  • Meeting booked+25 pts
  • Silent ≥ 1 day−3 / day
Score

Quality Score

0 – 100

Is the data usable? Below 20 forces Grade F and drops the lead out of the queue.

  • Valid phone30 pts
  • Valid email15 pts
  • Company name15 pts
  • Inquiry clarity20 pts
  • Source reliability10 pts

04The Grade Matrix

Every grade maps to a fixed action.

The same matrix every rep sees. The action is a fixed map, not an AI suggestion, so it is predictable.

Grade
Condition
Fixed action
A
Fit ≥ 65 · Intent ≥ 60 · Quality ≥ 60
Call now
B
Fit ≥ 55 · Intent ≥ 40 · Quality ≥ 50
Follow up today
C
Fit ≥ 40 · Intent ≥ 30 · Quality ≥ 40
Nurture
D
Fit ≥ 30 · Intent ≥ 15 · Quality ≥ 25
Light touch
E
Below D, with Quality ≥ 20
Light touch
F
Quality < 20 (junk / incomplete data)
Archive

05The intent decay rule

Silent leads drop automatically.

Without decay, a Grade A lead from two weeks ago stays Grade A forever, while newly-hot leads wait below it. That is how real teams lose deals.

With decay, silence has consequences. Intent drops −3 pts / dayafter the engagement threshold, so last week's Grade A becomes a B by Wednesday. A re-engagement signal spikes it back up.

Worked example
Day 0−3 / dayDay 9
ADay 0 · initial contact
74
ADay 5 · silence
59
BDay 8 · still silent
50
ADay 9 · WhatsApp reply +10
60

06Import to graded

A list comes back as a distribution, not a pile.

Import a CSV and the whole account comes back graded. Instead of scrolling a flat list, you see how many A, B and C leads you actually have, and where the effort should go first.

Lead grades

77 leads

A14
B23
C19
D11
E6
F4

Illustrative distribution.

07Confidence & freshness

A thin lead is not a bad lead.

A rep opens a lead with a first name and a mobile number and nothing else. Most systems score it low, which says the lead is weak. That is usually the wrong claim, the honest position is that there is not enough here to judge yet. So Leadkaun keeps two readings apart from the grade.

Confidence

How much we actually know

Separate from the grade. A weighted read across eight fields, with a prioritised list of what to ask for next, so a thin lead becomes a qualifying call instead of a shrug.

Confidence38 / 100

Next, ask for: company budget band

Freshness

How current the signal is

A list collected months ago and imported this morning looks identical to a fresh enquiry until something says otherwise. Every lead carries an ageing band that keeps moving.

Ageing band

Fresh7 days30 days90 daysStale

Both readings are visible on the lead and frozen into the score timeline whenever a grade changes. See the full guide to lead data trust.

08FAQ

Questions about scoring.

10In their words

Nobody switches over a score. They switch over one lead they lost.

Before

Forty portal enquiries a day, and the one we called first was whoever had messaged most recently.

We were never short of leads. We were short of an order to work them in. The first morning the queue told us to call a site visit from nine days ago before any of the fresh ones, and that settled an argument we had been having for two years.

Mandar Deshpande

Director of Sales, Vaastavik Realty

Pune · Real estate

Product mechanics, published in full at /methodology

A–F

Every lead graded, in real time

3 scores

Fit, Intent and Quality, published weights

Same day

To your first graded lead

Flat ₹

Priced per account, not per seat

11 · Ready when you are

See your leads graded the same day.

Import a CSV and Leadkaun grades every lead A–F within the hour. Free tier, no card, live the same day.

Free ₹0 · no card · same-day setup