Score and prioritize leads from your CRM data
Not all leads are equal. Treating them the same wastes the time of your best reps on the wrong accounts. Give Kuse your lead list and your criteria. It ranks them with reasoning.
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Reps spend time on leads that will never close
- Without scoring, all leads get treated the same. The rep who calls the bottom of the list spends as much time as the one who calls the top, for a fraction of the result.
- Manual scoring models are built once and never updated. The ICP evolves. Closed-won patterns change. The scoring stays frozen.
- Scores without context do not help. A number on a lead does not tell a rep why it matters or what angle to use.
Lead list in, scored priorities out
Describe the work in plain language
Tell Kuse your scoring criteria, the signals that matter, and where high-intent leads should be routed.
Connect your apps
Connect your CRM (HubSpot) and Slack. Kuse reads new lead data and pushes scored alerts to the right Slack channel.
Set a schedule or run it anytime
Score new leads as they arrive or run a batch score on your full pipeline every morning.
Get finished results in your workspace
Scored leads with tier labels and fit reasoning land in Slack and update in your CRM — ready for the sales team.
Kuse Workflows
Your best leads, surfaced before your team even wakes up.
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50,000+ professionals use Kuse every day
A practical guide to AI lead scoring
01
What is AI lead scoring?
AI lead scoring uses AI to evaluate each lead against your ideal customer profile and behavioral signals, then ranks them by likelihood to convert. Instead of applying a static point system, Kuse reads your closed-won patterns and ICP definition and applies that judgment to every new lead automatically.
02
Who is AI lead scoring for?
- Sales teams with high inbound volume and limited rep capacity
- RevOps teams managing CRM hygiene and pipeline quality
- SDR teams that need to prioritize outreach sequences
- Founders doing outbound who need to work the best names first
- Marketing teams qualifying MQLs before passing to sales
03
What signals matter for lead scoring?
- Company size, industry, and revenue range vs. your ICP
- Job title and seniority of the contact
- Recent company signals: hiring, funding, product launches
- Engagement history: email opens, page visits, demo requests
- Fit with closed-won patterns in your CRM history
04
How to set up AI lead scoring effectively
Upload your ICP document and a sample of your best closed-won accounts. The more context Kuse has about what a great customer looks like, the better the scoring. Define your tier labels (Tier 1, 2, 3 or Hot, Warm, Cold) in the prompt so the output is ready for your team to act on. Connect your CRM as the source and Slack as the delivery channel for instant alerts on Tier 1 leads.
05
Common mistakes to avoid
- Scoring without a documented ICP: The model is only as good as the criteria you give it
- Never updating the scoring criteria: Your best customers evolve — your model should too
- Treating scores as decisions: Scores guide priority, they do not replace rep judgment
- No Slack routing for top leads: High-intent leads need instant visibility, not a daily batch report
06
Why AI lead scoring works better in Kuse
Static scoring tools apply fixed rules. Kuse applies your context. Because your ICP definition, closed-won analysis, and territory notes live in your workspace, every batch of leads gets evaluated against the same judgment your best rep would apply. And because scoring runs as an automated workflow, every new lead gets evaluated the moment it arrives — not the next time someone remembers to run the model.
07
Frequently asked questions
Can Kuse score leads directly from HubSpot?
Yes. Connect HubSpot as a source in your workflow. Kuse reads new leads, scores them, and can push results back to your CRM or to a Slack channel.
How often should the scoring workflow run?
Daily morning runs work well for most sales teams. You can also set it to trigger on new lead creation if your CRM supports webhooks.
Can I see why a lead received a particular score?
Yes. Kuse includes reasoning with each score — which signals matched your ICP and which raised or lowered the fit assessment.