How does it handle PLG self-upgrade events?

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

Can we export to our analytics stack (Segment, Mixpanel)?

Not in Phase 1; CSV export available.

Can we track account-level vs. user-level?

Lead record supports primary + associated contacts; account-level roll-ups available.

Does Leadkaun replace my CRM?

No. Leadkaun runs alongside your CRM. Your CRM stays the system of record for what happened; Leadkaun is the behaviour layer that decides what happens next, grading every lead A–F, ranking each rep's Priority Queue, and surfacing the ₹ at risk. Most teams import a CSV and run both in parallel to measure the difference first.

How long does it take to get started?

You can be set up the same day. A short onboarding wizard captures your ICP industries, states, business types, decision-maker roles and budget bands, then you import a CSV and every lead is graded A–F immediately. No implementation project, no dedicated admin.

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.

SaaS · Bengaluru

SaaS Lead Management in Bengaluru.

Bengaluru-based saas teams use Leadkaun to grade every lead A–F, build each rep's Priority Queue, and surface missed revenue in rupees. Setup the same day.

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Quick answer

How does Leadkaun help saas teams in Bengaluru manage leads?

Leadkaun grades every saas lead in Bengaluru A–F across fit, intent, and quality in real time, then builds each rep a live Priority Queue so the highest-intent enquiries get worked first. WhatsApp is a first-class 3-tap signal, and missed revenue surfaces in rupees. Setup happens the same day, at flat INR pricing.

Typical deal size

₹10k–₹20L ARR

Sales cycle

1–60 days (self-serve to mid-market)

Primary channels in Bengaluru

inbound website · demo requests · trial signups

01Why Bengaluru saas teams lose deals

The patterns we see every week.

Trials expire before anyone calls

User signs up, tries for 2 days, goes silent. No one from sales reaches out. Trial expires. Churn happens before the sales cycle begins. 60% of self-serve trials follow this shape.

Expansion signals rot in product data

An existing customer just added 5 seats, hit an API limit, and invited a new department. All expansion-ready signals. Nobody on the sales team sees any of it.

Content-spike chaos

A viral LinkedIn post drops 400 trial signups in a day. Sales has no triage. 350 go cold over the next week. Six figures of ARR walks away.

02How Leadkaun helps saas teams in Bengaluru

What we configure on day one.

01
Trial signups imported via CSV (including webhook exports and Google Sheet exports), graded A–F by company size, stack signals, and role as soon as they land
02
Intent decay tuned for SaaS: a trial user silent for 10 days is a strong negative signal; someone who invited 3 teammates is a Grade A spike
03
Expansion-opportunity detection flags existing customers with usage, role-add, or seat-limit signals as separate lead type
04
Morning Brief: '12 trial users hit day-7 without a sales call. ₹3.2L ARR at risk, Priya owns 8, Rajesh owns 4'
05
Multi-seat deal threading: an SDR's initial contact flows to an AE's closing thread without losing context

Bengaluru context

SaaS teams in Bengaluru, Karnataka typically source leads from inbound website, demo requests, trial signups. India's Silicon Valley, densest B2B SaaS and EdTech market. All of those channels flow into Leadkaun via CSV upload or manual entry in minutes (a Google Sheets connector is on the roadmap), where every enquiry is scored and graded A–F before it reaches a rep.

Commercial activity in Bengaluru clusters around Whitefield, Electronic City, Outer Ring Road, Manyata, with the local economy built on IT parks and software exports across the Whitefield and ORR corridors, the areas a saas pipeline here most often draws from.

What this looks like in practice

“When trial follow-ups are queued and never forgotten, fewer trials go cold in the gap between signup and the first real conversation.”

Illustrative scenario

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 Bengaluru.

A SaaS enquiry in Bengaluru is rarely decided by one person. Two or three read it, and they are not reading it for the same thing.

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 a team here uses most