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Automate Lead Scoring with AI: A 0 to 100 Score and a Reason on Every Lead

For founders and sales managers with more leads than callers: grade the whole list in minutes and give every executive a ranked day.

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When you automate lead scoring, the question changes from 'who should I call?' to 'is this score right?'. That is a better question. A manual scoring sheet with points for company size and source is hard to keep up, and it ignores what the lead actually wrote.

Most Indian SMEs have a backlog of leads nobody has looked at properly: old campaign responses, website forms and imported lists.

Apragya's CRM scores leads with AI, in bulk or one at a time. This page covers how it works, an illustrative example and where people stay in control.

Why points-based scoring falls short

Rules go stale

Point tables are written once and rarely updated.

Text is ignored

The enquiry note, the richest signal, earns no points.

Backlogs stay cold

Old leads are never rescored, so nobody revisits them.

No explanation

An executive sees 62 points but not why.

An example: a Bengaluru SaaS reseller clearing a backlog

Take an illustrative reseller of business software with 600 unscored leads from a year of webinars and forms. The sales manager scored them in batches over an afternoon.

What one lead's score is built from

Lead score

0 to 100, with a hot, warm or cold segment.

  • Company and industry

    A 40-person distributor.

  • Role

    Finance head, a likely decision maker.

  • Enquiry note

    Asked about moving off spreadsheets.

  • Source

    Webinar on GST invoicing.

  • Recency

    Last contact four months ago.

The reason saved with the score names the signals that mattered.

About 70 leads came back hot, many of them finance heads who had asked specific questions months earlier. The manager split them across three executives, and the reason on each lead gave the caller an opening line. Cold leads stayed in a nurture sequence, and the manager planned to rescore them next quarter.

Three trays of cards with the red stack divided into three bundles
The hot leads from the backlog were split between three callers, each with a reason to open the call.

How AI lead scoring works in Apragya

Step 1 of 5

Pick the leads

Choose unscored leads for a batch, or score a single lead.

  1. Pick the leads: Choose unscored leads for a batch, or score a single lead.
  2. Grade: AI reads each lead's details and notes in one pass.
  3. Save: A 0 to 100 score, a segment and a reason go on the lead.
  4. Sort: Lists and reports can be ordered by score or segment.
  5. Review: Managers check the hot list before calls are assigned.

Building a lead scoring model you can trust

A score is only useful if people believe it. Check a sample of hot and cold leads against what your best sellers would say, and look at the reasons. The same score fields are used by the deeper Lead Qualifier agent, so there is one scoring idea across the CRM.

Points sheets, against Apragya

FeaturePoints sheetApragya
Signals usedFixed fields onlyFields and the enquiry text
Old leadsLeft unscoredScored in batches
ExplanationA totalA reason on each lead
UpkeepManual rule changesInstructions adjusted when needed
Where it livesA spreadsheetOn the lead record

Checked against public information on 16 September 2026.

What sets Apragya apart for predictive lead scoring in India

One record

Scores follow the lead into contacts, accounts and deals.

Fast batches

Many leads graded in a single call.

Deeper checks

The Lead Qualifier applies BANT on new leads.

Credits enforced

Scoring checks the AI Credit balance before it runs.

Access by role

Only people allowed to update leads can score them.

Reports

Pipeline and lead reports read the same scores.

Scores sit on the leads record and feed CRM reports. Read more on AI-powered CRM software.

Getting started

  1. Import leads with their enquiry notes intact.
  2. Score a first batch of unscored leads.
  3. Check twenty hot and twenty cold leads by hand.
  4. Assign the hot list to your callers.
  5. Rescore the backlog each month.

Keeping the enquiry notes during import matters more than any other field.

What it costs to start

Free
Up to 3 users
CRM included, with HR and Vendor Onboarding
1,000
AI Credits a month
On the free plan
INR 3,999
Starter, a month
Up to 10 users and 2,000 AI Credits

Automating lead scoring, answered

How many leads can be scored at once?
Leads are scored in batches of up to 25 per call, and you can run as many batches as you need.
What do hot, warm and cold mean?
They are segments saved alongside the 0 to 100 score, so lists can be sorted simply.
Is the scoring the same as the Lead Qualifier?
They write the same score fields. Bulk scoring is fast; the Lead Qualifier looks at one lead in more depth.
Does scoring use AI Credits?
Yes. Each scoring run is metered against your AI Credits, and the balance is checked first.
Can a manager override a score?
The score is guidance. Managers assign and move leads as they see fit, and the reason on the lead helps them judge when the score is wrong.
Should we rescore old leads?
Yes. A lead's situation changes, so rescoring the backlog every month or quarter keeps the ranked list honest and brings forgotten buyers back into view.
What does it cost to start?
CRM is part of the free plan, which covers up to 3 users with CRM, HR and Vendor Onboarding and 1,000 AI Credits a month. Starter, at INR 3,999 a month, covers up to 10 users, adds a choice of enterprise apps, and is where ready-made AI agents start to run.

Score your backlog this afternoon

Import your leads, grade them in batches, and hand out a ranked call list.

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