AI ranks every lead by fit and intent, work the right ones first.
Every lead is not meant to have sales potential and this can be identified only by an AI lead scoring tool. DataKart understands the importance of this tool and enables businesses to identify and prioritise prospects depending on the fit, intent, engagement, and business relevance. This empowers sales teams to focus on leads that are more likely to convert without manually reviewing hundreds of contacts. The lead qualification process is done with the help of scoring models by assessing company data, behavioural activity, ICP alignment, and buying signals. This only enhances efficiency, reduces time spent on low-quality leads, and provides stronger outbound prioritisation workflows.
Score per lead returned
+ intent combined in one score
ICP definition per campaign
Score reasoning per lead
How it works
From enriched list to prioritised pipeline.
Businesses help define ICP attributes, engagement signals, and scoring priorities.
What you get
50 structured account records per reference
Every lookalike account comes back with full firmographic data and a similarity score so you know exactly why it matched.
Full name
Text
Job title
Text
Company
Text
LinkedIn URL
URL
Location
City / Country
Signal source
LinkedIn / Job / Web
Signal snippet
Text excerpt
Signal date
Date
Matched keyword
Text
Intent score
High / Medium / Low
Company size
Range
Industry
Category
Who uses Lead Scoring — and why.
Any team with at least one good customer reference can unlock pipeline they didn't know existed
Outbound Prospect Prioritization
Help SDR teams focus on stronger-fit leads first.
Account-Based Sales
Identify accounts showing higher intent or engagement activity.
CRM Lead Qualification
Improve lead organization and routing within sales systems.
Marketing Qualified Lead Scoring
Rank inbound leads according to engagement and ICP alignment.
Revenue Intelligence Workflows
Support sales forecasting and pipeline prioritization using lead quality signals.
AI Lead Scoring Tool
From enriched list to prioritized pipeline.
AI lead scoring evaluates every prospect against your ICP definition and assigns a score based on how well they match — combining firmographic fit (are they the right type of company and role?) with intent signals (are they actively in-market?). The result is a ranked list that tells your team exactly where to focus their time.
Traditional lead scoring uses rigid rules and point systems — "give 10 points for company size 100–500, subtract 5 points for outside the US". These rules require constant maintenance and can't evaluate nuanced signals like "posted about the problem last week" or "new CRO just hired".
Datakart's Lead Scoring uses AI to reason about fit and intent holistically — not just matching criteria but weighing signals in context. The score includes an explanation of the reasoning, so you understand why a lead ranked where it did and can audit the output.
Integrations
Works with your existing workflow
Export your data and connect seamlessly with your CRM, outreach, and automation tools.
No disruption. No complex setup.
Clay
HubSpot
Salesforce
n8n
Make
Zapier
Instantly
Smartlead
Any AI agent
FAQ
Common questions.
Related Tools
Build the richest scoring context.
Find Company
Pull the right company details
Company Intent
Find accounts showing buying signals in your category right now.
Email Waterfall
Add verified emails to every contact. Pay per valid result only.
Email Personalization
After scoring, run Email Personalization on your Tier 1 accounts for highest-converting outreach.
News Research
Company news and trigger events — personalise outreach at the account level.
Account Research
Full account intelligence brief — everything you need before the first touch.
Not all leads are equal. Start working the ones that will actually close.
100 free credits. No credit card.