Can you automate lead scoring in HubSpot?

Automating Lead Scoring in HubSpot

HubSpot provides lead scoring to automatically rank contacts by their likelihood to convert. As of April 2026, manual lead scoring requires Marketing Hub Professional ($800/month); predictive scoring requires Enterprise ($3,600/month).

Manual Lead Scoring Setup

1. Go to Settings > Properties
2. Search for "HubSpot Score" (built-in property)
3. Click "HubSpot Score" > "Add criteria"

Positive Score Criteria (Add Points)

• Visited pricing page: +10 points
• Downloaded whitepaper: +5 points
• Opened 3+ marketing emails: +5 points
• Submitted demo request form: +20 points
• Job title contains "Director" or "VP": +10 points
• Company size 50-500 employees: +8 points
• Industry matches target vertical: +5 points

Negative Score Criteria (Remove Points)

• Unsubscribed from emails: -15 points
• No website visit in 30 days: -5 points
• Job title contains "Student" or "Intern": -10 points
• Free email domain (gmail, yahoo): -3 points

Using Scores in Workflows

Create workflows that trigger based on lead score thresholds:

• Score reaches 50 → Assign to sales rep (MQL threshold)
• Score reaches 80 → Create task "Call within 24 hours" (SQL threshold)
• Score drops below 20 → Enroll in re-engagement email sequence

Predictive Lead Scoring (Enterprise)

HubSpot's AI-powered predictive scoring analyzes thousands of data points across all contacts to identify patterns that predict conversion. It creates two scores:

• Likelihood to close: Probability the contact becomes a customer
• Contact priority: Tier ranking (Very High, High, Medium, Low)

Predictive scoring updates automatically as new data comes in and improves over time as more contacts convert.

Multiple Score Properties

On Professional plans, create up to 25 custom score properties for different scoring models:

• Marketing Qualified Lead (MQL) Score: Based on engagement and fit
• Product-Qualified Lead (PQL) Score: Based on product usage data
• Customer Health Score: Based on product adoption and support interactions

Best Practices

• Start with 5-10 scoring criteria, not 50 (simplicity improves accuracy)
• Review and adjust scores quarterly based on actual conversion data
• Set clear MQL and SQL thresholds agreed upon by marketing and sales teams
• Use negative scoring to decay scores for inactive contacts
• Document the scoring model so both teams understand what drives the score