How does it handle PLG self-upgrade events?

Trigger a 'self-upgrade' signal manually or via API; scoring surfaces the user for expansion conversations.

Does it integrate with our trial signup flow?

Webhook or CSV; we'll publish a SaaS-specific onboarding guide.

Does it work for multi-product cross-sell?

Product-level ICP and pipeline per product.

Is the lead scoring a black-box AI model?

No. The score is three transparent 0–100 components, Fit, Intent and Quality, combined on fixed, published thresholds. The weights are identical for every account, so any rep can see exactly why a lead earned its grade, rather than trusting an opaque AI number.

Can I tune the scoring to my kind of business?

You configure your ICP, the industries, states, business types, decision-maker roles and budget bands that define a good customer, and that drives every Fit score. The underlying weights stay fixed and auditable by design, so the grade remains explainable and comparable across accounts.

How do leads get into Leadkaun?

CSV import or manual entry today, plus a generic webhook. Indian phone formats are normalised and duplicates caught on insert. Native Google Sheets sync and IndiaMART / Facebook Lead Ads connectors are on the roadmap; for now those sources come in via CSV export. Every lead is graded A–F the moment it lands.

Do I pay extra for each sales rep?

No. Pricing is flat per account, so a five-rep team and a fifteen-rep team on the same tier pay the same. That's deliberate: it means you can put every rep on Leadkaun without the per-seat maths that makes teams ration access.

How does the A–F grade get decided?

Three transparent 0–100 scores, Fit (how well the lead matches the ICP you set), Intent (engagement and signal events), and Quality (data reliability), combine into a single A–F grade. Intent decays as a lead goes silent, and the weights are fixed and auditable for every account, so a rep can always see exactly why a lead is Grade A.

Lead Scoring

Lead Scoring for SaaS Teams in Ambattur.

Leadkaun's lead scoring is built for how Ambattur-based saas teams actually sell, Indian phone handling, WhatsApp as a first-class lead signal, ₹ figures in Indian formatting throughout.

In short

In Ambattur, a saas lead is warmest the moment it lands. Leadkaun's lead scoring grades it instantly, drops it into the assigned rep's Priority Queue, and decays stale intent automatically, so nothing quietly ages out of view.

Start free→See pricing →

Quick answer

What is Leadkaun's lead scoring for saas teams in Ambattur?

01What lead scoring does

What it does for saas teams.

01
Three-dimensional scoring: Fit (ICP), Intent (engagement), Quality (data reliability)
02
Transparent weights. Every rep can see why a lead is Grade A, not a black-box AI score
03
Intent decays automatically when leads go silent, stale grades drop without manager intervention
04
{industry}-specific ICP templates built for Indian market defaults
05
Grades in real time as each lead lands, so the queue is ready before the rep opens it

02On lead scoring

What lead scoring actually solves.

Lead scoring is how a team decides which enquiry to work first when far more arrive than anyone can call. Done well, it replaces gut feel and recency bias with a defensible ranking: the freshest lead isn't automatically the best one, and the lead that's been sitting for a day might be the ₹40-lakh deal about to go cold.

Leadkaun scores every lead on three transparent 0–100 dimensions, Fit against the ICP you configure, Intent from real engagement signals, and Quality from data reliability, then combines them into an A–F grade. The weights are fixed and identical for every account, so it's never a black box: a rep can always see exactly why a lead is Grade A, and intent decays automatically when a lead goes silent so the grade stays honest over time.

SaaS in Ambattur

In Ambattur, saas teams typically work leads from inbound website, demo requests, trial signups, with deal sizes in the ₹10k–₹20L ARR range and sales cycles of 1–60 days (self-serve to mid-market). Leadkaun's lead scoring is calibrated for those realities, not a generic US B2B default.

In Ambattur, Tamil Nadu, B2B demand concentrates in manufacturing, saas, real estate. Leadkaun grades and queues every enquiry here on fit, intent and quality, so a Ambattur rep works the highest-probability leads first.

Industrial estate and IT park; Chennai suburb, context Leadkaun's grading accounts for when it ranks a Ambattur saas pipeline.

Commercial activity clusters around Ambattur Industrial Estate, SIDCO Industrial Estate, Pattaravakkam, with the local economy built on one of Tamil Nadu's largest industrial estates for auto components, engineering and textiles, the areas a Ambattur saas pipeline most often draws from. Leadkaun grades and queues those enquiries so the highest-intent ones surface first, wherever they land.

03How the grade works

How every saas lead is graded A–F.

No black box. Each grade is three transparent 0–100 scores combined against fixed, auditable thresholds, and stale leads surface as ₹ at risk before they go cold.

Fit

0–100

How closely the lead matches the ICP you set, industry, state, business type, decision-maker role and budget band. This is the part you shape: you configure who a good customer is, not the maths behind it.

Intent

0–100

Engagement and signal events, source strength, WhatsApp replies, pricing-page visits, callbacks. Intent decays as a lead goes silent, so a hot lead that stops responding cools automatically instead of sitting falsely high.

Quality

0–100

Data reliability, completeness, phone and email validity, junk and duplicate detection. If Quality is too low the lead is capped down the grades, so bad data can never masquerade as a good lead.

The threshold

A lead is Grade A when Fit ≥ 65, Intent ≥ 60 and Quality ≥ 60, the rest step down through B–F on the same fixed cut-offs. Because the weights are identical for every account, the grade stays explainable and comparable: no per-customer tuning, no hidden model.

For SaaS, Fit is company size, sector and the seniority of whoever filled the form, a founder and an intern do not score the same.

04Who signs off

Who decides, on a SaaS lead in Ambattur.

The people who decide what happens to a SaaS enquiry in Ambattur are not one audience. Each is asking their own question of it.

Founder

senior

Wants to know whether this enquiry is worth anyone's afternoon before the team spends one.

Head of Sales

senior

Cares less about the single lead than about whether the team is working the right ones this week.

Account Manager

mid

Is checking whether this is genuinely new or an existing account arriving through a second door.

This is why Fit is scored separately from Intent: how keen someone sounds and whether they are the person you can actually sell to are two different questions. Both are published with their weights.

05What lead scoring touches