Lead Scorer

Automatically score and prioritize leads based on fit, engagement, and intent signals so reps focus on the deals most likely to close, not the loudest inbox.

For Sales Reps Sales Managers Marketing Teams Revenue Operations
Sample prompt to Joy's Assistant

Score these leads against our ideal customer profile and rank them by fit, engagement, and intent. Tell me which ones sales should contact first: [leads or CRM list].

What it can look like

An illustrative example. Your output will reflect your own sources, data, and prompts.

Score these leads against our ideal customer profile and rank them by fit, engagement, and intent. Tell me which ones sales should contact first: this week's inbound leads from HubSpot.

Here's the scoring board Visual Intelligence assembled from your CRM, marketing engagement, and firmographic data, ranking this week's inbound leads by fit, engagement, and intent.

148
Leads scored
▲ 22 vs last week
22
Sales-ready (Hot)
▲ 5 vs last week
61
Nurture (Warm)
steady
63
Avg fit score
▲ 2 pts
LeadCompanyScore
Sarah ChenAcme Corp92
Dana JohnsonTechFlow87
Priya MenonNorthBridge81
Lisa ParkDataCo68
David OseiVertex59
Alex RiveraStartupXYZ34
LeadCompanyScoreWhy
Sarah ChenAcme Corp92 HotVP title, pricing page 3x, demo request
Dana JohnsonTechFlow87 HotICP match, case study download, replied to email
Priya MenonNorthBridge81 HotStrong fit, two demos attended
Lisa ParkDataCo68 WarmGood fit, moderate engagement, no intent yet
David OseiVertex59 WarmRight-size fit, a few email opens, no pricing or demo activity yet
Alex RiveraStartupXYZ34 CoolToo small (12 employees), single page view

Three leads clear the sales-ready bar this week and should be worked today. Sarah Chen at Acme Corp tops the list at 92, a VP who hit the pricing page three times and just submitted a demo request, so she is actively comparing options. Dana Johnson (87) and Priya Menon (81) follow on strong ICP fit and content engagement. Alex Rivera scores 34: a 12-person company with a single page view, so route that one to nurture rather than sales.

Want me to draft Sarah Chen's outreach, a first-touch email that references the pricing pages she viewed?

Score leads on the signals that matter

Your reps treat every lead the same, whether it's a VP at a perfect-fit company or a student researching for a class project. Without scoring, they chase whoever's loudest in their inbox. Marketing passes over leads that aren't ready, and sales ignores leads that are. Meanwhile, your best prospects go cold while reps chase tire-kickers.

  1. Connect your data sources

    Connect JoySuite to your CRM, marketing automation, and website analytics. Joy pulls in lead data, engagement history, and firmographic details. Learn about Visual Intelligence →

  2. Define your scoring criteria

    Tell Joy what makes a good lead for your business: company size, industry, title, engagement level, content consumed. Joy helps you weight each factor based on your historical win data.

  3. Generate scores automatically

    Joy calculates a score for every lead combining fit (are they your ICP?), engagement (are they interested?), and intent (are they ready to buy?). Scores update as new signals arrive.

  4. Prioritize and take action

    Reps open a ranked list with clear reasons each lead is hot, warm, or cold, so they can see at a glance who to call first. Joy surfaces the ranking; your team decides who to work now and who to leave for later nurture.

  5. Make it one click for your team

    Save this ask as a custom command on the assistant your team already uses, so anyone can run it in one step.

Make it yours

Multi-Signal Scoring

Combine fit, engagement, and intent signals into a single score that reflects true buying readiness.

Explainable Scores

Every lead score includes clear reasoning so reps understand why a lead is hot, warm, or cold.

Real-Time Updates

Scores update automatically as new engagement signals arrive from email, website, and content interactions.

Data Source Integration

Connect your CRM, marketing automation, website analytics, and firmographic data for comprehensive scoring.

Inbound Lead Scoring

Score marketing-generated leads based on content engagement and form submissions.

Outbound Prospect Prioritization

Rank cold outreach targets by ICP fit and likelihood to respond based on signals.

Re-engagement Scoring

Identify dormant leads showing renewed interest based on recent activity spikes.

Account-Based Scoring

Score entire accounts by aggregating signals across multiple contacts at target companies.

Frequently Asked Questions

What is lead scoring?

Lead scoring assigns numerical values to leads based on their likelihood to become customers. It combines fit signals (company size, industry, title) with engagement signals (email opens, website visits) and intent signals (pricing page views, demo requests) to prioritize sales outreach.

How does AI improve lead scoring?

AI analyzes historical win/loss data to identify which signals actually predict conversions for your business. It continuously updates scores as new engagement data arrives and explains why each lead received its score, helping reps prioritize effectively.

What data sources feed into lead scoring?

JoySuite's Lead Scorer connects to your CRM, marketing automation, website analytics, and firmographic data providers. It analyzes company fit, contact title, email engagement, content downloads, website behavior, and intent signals.

How do I know if lead scoring is working?

Track conversion rates by lead score tier. Effective scoring should show higher conversion rates for high-scored leads. JoySuite helps you monitor scoring accuracy and refine weights based on actual win/loss outcomes.

What's the difference between lead scoring and lead grading?

Lead scoring typically measures engagement and intent (behavior), while lead grading measures fit (demographics). JoySuite combines both approaches, scoring leads on fit (ICP match), engagement (interest level), and intent (buying signals).

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