Build Lead Scoring Model
Create a two-score lead scoring model using HubSpot's new Lead Scoring tool: a Fit score (ICP company fit + persona match) and an Engagement score (behavioral signals with time decay). This enables sales to prioritize by company fit and marketing to prioritize by engagement recency.
Why This Matters
Without scoring, every lead looks equally (un)important. Sales has no ranked list of who to call first, marketing cannot trigger stage progressions based on engagement, and there is no way to differentiate between a senior decision-maker at a target-vertical enterprise and a generic contact who has never opened an email.
Prerequisites
- - Super Admin permissions in HubSpot
- HubSpot Marketing Hub Professional or Enterprise
- ICP Tier property created and workflows processed (create-icp-tiers skill must be completed first)
- Access to Marketing > Lead Scoring (the new tool, NOT the deprecated "HubSpot Score" property)
Critical: Old vs New Lead Scoring
The old "HubSpot Score" property is deprecated. Score properties stopped being editable as of July 2025 and stopped updating as of August 2025. Do NOT reference the old HubSpot Score property in any workflows, lists, or reports.
The new Lead Scoring tool (Marketing > Lead Scoring) supports:
- - Score groups with max point limits
- Engagement decay (points reduce over time automatically)
- Separate Fit vs Engagement score types
- Up to 5 total scores per portal
Interview: Gather Requirements
Before executing, collect the following information from the user:
Q1: What job titles/personas are most valuable to you?
- - Examples: CEO, COO, CFO, CTO, CRO, VP of Operations, VP of Marketing, Director of Operations, Director of Marketing, Head of Procurement, Engineering Manager
- Default: C-suite and VP-level leaders get the highest scores, followed by Director and Manager-level roles
Q2: What engagement actions matter most?
- - Examples: Email opens, email clicks, form submissions, website visits, content downloads, webinar registrations
- Default: Form submissions (+30), email clicks (+25), website visits (+20), email opens (+15)
Q3: What negative signals should reduce scores?
- - Examples: Unsubscribe, hard bounce, competitor domain, no activity in 6+ months, free email domain (gmail, yahoo)
- Default: Global unsubscribe (-100), hard bounce (-50), no activity 6+ months (-20), missing company name (-10)
Q4: What score threshold should trigger MQL status?
- - Examples: Fit > 30 AND Engagement > 20, combined score > 50, any threshold that matches your sales handoff criteria
- Default: Fit Score > 30 AND Engagement Score > 20
Plan
- 1. Review any existing scoring models in the portal
- Create the Fit Score (company fit + persona match)
- Create or update the Engagement Score (behavioral signals with decay)
- Allow 4-6 hours for HubSpot to recalculate all contacts
- Verify scoring distribution and accuracy (after state)
Before State
- 1. Navigate to Marketing > Lead Scoring
- Note any existing scores (you have a limit of 5 total)
- Review existing score criteria — decide whether to update or replace
- Check that ICP Tier property is fully populated on companies (run create-icp-tiers after state check)
Execute
Create the Fit Score
- 1. Go to Marketing > Lead Scoring
- Click Create score
- Select Fit as the score type
- Select Contact as the scored object
- Name it descriptively (e.g., "Lead Fit Score")
Score Group 1: ICP Company Tier
Use Associated company property > ICP Tier:
These are starting points -- calibrate based on your actual conversion data after 30 days.
| Criteria | Condition | Points (suggested range) |
|---|
| Primary ICP Company | ICP Tier is "Tier 1 - Primary ICP" | +25 to +35 |
| Secondary ICP Company |
ICP Tier is "Tier 2 - Secondary ICP" | +15 to +25 |
| Tertiary ICP Company | ICP Tier is "Tier 3 - Tertiary ICP" | +5 to +15 |
| Not ICP Company | ICP Tier is "Not ICP" | -10 to -20 |
Score Group 2: Persona / Job Title
Use Contact property > Job title > contains any of:
These are starting points -- adjust titles and weights to match your buyer personas.
| Criteria | Example Title Values | Points (suggested range) |
|---|
| C-Suite Executives | CEO, COO, CFO, CTO, CRO, CMO, Chief Revenue Officer | +20 to +30 |
| VP-Level Leaders |
VP of Operations, VP of Marketing, VP of Sales, VP of Finance | +20 to +30 |
| Director-Level | Director of Operations, Director of Marketing, Head of Procurement, Director of Finance | +15 to +25 |
| Manager-Level | Engineering Manager, Operations Manager, Marketing Manager, Procurement Manager | +10 to +20 |
| Other Relevant Titles | Analyst, Coordinator, Specialist (if relevant to your sales process) | +5 to +10 |
Customize these titles based on your buyer personas. The point values should reflect how likely each persona is to be a decision-maker or champion for your product. The ranges above are starting points -- review after 30 days and adjust based on which titles actually convert.
Score Group 3: Negative Fit Signals
| Criteria | Condition | Points |
|---|
| Missing Company Name | Company name is unknown | -10 |
| Hard Bounced |
Hard bounce reason is known | -50 |
| Globally Unsubscribed | Unsubscribed from all email = True | -100 |
- 6. Set the overall score maximum (recommended: 100)
- Save and turn ON
Create the Engagement Score
- 1. Click Create score (or edit existing engagement score)
- Select Engagement as the score type
- Select Contact as the scored object
- Name it descriptively (e.g., "Lead Engagement Score")
Positive Engagement Criteria
| Criteria | Condition | Points | Decay |
|---|
| Opened Marketing Email | Last marketing email open date within last 30 days | +15 | Monthly |
| Clicked Marketing Email |
Last marketing email click date within last 30 days | +25 | Monthly |
| Visited Website | Number of Sessions > 0 | +20 | Quarterly |
| Submitted a Form | Number of Form Submissions > 0 | +30 | Quarterly |
Negative Engagement Criteria
| Criteria | Condition | Points |
|---|
| No Email Activity 6+ Months | Last marketing email open date > 180 days ago | -20 |
- 5. Set the overall score maximum (recommended: 100)
- Save and turn ON
Example Combined Scoring Framework
For reference, here is how the two scores work together to prioritize contacts:
| Contact Profile | Fit Score | Engagement Score | Priority |
|---|
| CEO at Tier 1 company, clicked email this week | ~60 | ~55 | Highest |
| Director of Operations at Tier 2 company, form submission |
~40 | ~50 | High |
| Unknown title at Tier 3 company, email open only | ~10 | ~15 | Medium |
| No title, Not ICP, no activity in 6 months | ~-25 | ~-20 | Lowest |
For Lifecycle Progression
If you want to automatically progress contacts through lifecycle stages based on scoring:
- - Define a combined threshold (e.g., Fit Score > 30 AND Engagement Score > 20 = MQL; typically the combined threshold falls in the 40-60 range, but calibrate based on your pipeline)
- Build this as a separate workflow (not part of the scoring model itself)
- This is a separate task from building the scoring model
After State
Allow 4-6 hours for HubSpot to fully recalculate all contact scores. The new Lead Scoring tool processes asynchronously, and large databases take time.
Verification
- 1. Go to Contacts > Contacts
- Click Edit columns and add both score properties to visible columns
- Sort by Fit Score descending
Check the top 20 contacts:
- - Job titles should be target personas (CEO, VP of Operations, Director of Marketing, etc.)
- Associated companies should be Tier 1 or Tier 2
- If a non-relevant contact appears at the top, review the scoring criteria for issues
Check the bottom contacts:
- - Sort ascending (lowest scores first)
- Bottom contacts should be unsubscribed, bounced, or at Not ICP companies
- If relevant contacts appear at the bottom, review negative signal weights
Check score distribution:
- - Filter Fit Score > 50: High-priority fit (should be your best prospects)
- Filter Fit Score 20-50: Medium fit
- Filter Fit Score 1-19: Low fit
- Filter Fit Score <= 0: Disqualified (should be unsubscribed, bounced, or bad data)
Sanity check:
- - Pick 3 contacts at random
- Manually calculate their expected scores based on your criteria
- Compare to actual scores
- Investigate any discrepancies
Key Technical Learnings
- - The old "HubSpot Score" property is frozen. It will not update. Do not reference it in workflows, lists, or reports. Use the new Lead Scoring tool scores instead.
- Two separate scores are better than one. Fit and Engagement serve different purposes: Fit tells you WHO to talk to (company and persona match), Engagement tells you WHEN to talk to them (behavioral recency). Combining into one number obscures both signals.
- Score decay is a major improvement. Enable it on engagement criteria so scores naturally decrease over time. Without decay, a contact who clicked one email two years ago looks the same as one who clicked yesterday.
- Allow 4-6 hours for recalculation. Do not panic if scores show 0 immediately after creation. The new tool processes asynchronously across the entire database.
- Limit of 5 scores per portal. Plan carefully. You may want to reserve slots for future scores (e.g., product-specific engagement scores).
- Tune the model after 30 days. Review whether top-scored contacts are actually converting. Adjust point values based on real conversion data. Lead scoring is iterative, not one-and-done.
- Negative signals are as important as positive ones. Hard bounces and global unsubscribes should carry heavy negative weight to push these contacts to the bottom regardless of other factors.
- ICP Tier is the highest-leverage scoring input. It captures firmographic fit in a single property. Without it, the Fit score has no company-level signal and relies entirely on persona matching.
构建潜在客户评分模型
使用HubSpot新的潜在客户评分工具创建一个双评分潜在客户评分模型:契合度评分(ICP公司契合度+人物画像匹配)和参与度评分(带时间衰减的行为信号)。这使得销售团队能够按公司契合度进行优先级排序,营销团队能够按参与度时效性进行优先级排序。
为何重要
没有评分,每个潜在客户看起来同等(不)重要。销售团队没有优先联系谁的排名列表,营销团队无法基于参与度触发阶段推进,也无法区分目标垂直行业企业的高级决策者和从未打开过邮件的普通联系人。
前提条件
- - HubSpot中的超级管理员权限
- HubSpot营销中心专业版或企业版
- 已创建ICP层级属性并处理工作流(必须先完成create-icp-tiers技能)
- 可访问营销 > 潜在客户评分(新工具,非已弃用的HubSpot评分属性)
关键:旧版与新版潜在客户评分
旧的HubSpot评分属性已弃用。 评分属性自2025年7月起停止编辑,自2025年8月起停止更新。请勿在任何工作流、列表或报告中引用旧的HubSpot评分属性。
新的潜在客户评分工具(营销 > 潜在客户评分)支持:
- - 带最高分数限制的评分组
- 参与度衰减(分数随时间自动减少)
- 独立的契合度与参与度评分类型
- 每个门户最多5个总分
访谈:收集需求
执行前,向用户收集以下信息:
Q1:哪些职位/人物画像对您最有价值?
- - 示例:CEO、COO、CFO、CTO、CRO、运营副总裁、营销副总裁、运营总监、营销总监、采购主管、工程经理
- 默认:C级高管和副总裁级领导获得最高分,其次是总监级和经理级角色
Q2:哪些参与行为最重要?
- - 示例:邮件打开、邮件点击、表单提交、网站访问、内容下载、网络研讨会注册
- 默认:表单提交(+30)、邮件点击(+25)、网站访问(+20)、邮件打开(+15)
Q3:哪些负面信号应降低分数?
- - 示例:取消订阅、硬退信、竞争对手域名、6个月以上无活动、免费邮箱域名(gmail、yahoo)
- 默认:全局取消订阅(-100)、硬退信(-50)、6个月以上无活动(-20)、缺少公司名称(-10)
Q4:什么分数阈值应触发MQL状态?
- - 示例:契合度 > 30 且 参与度 > 20、综合分数 > 50、任何符合您销售交接标准的阈值
- 默认:契合度评分 > 30 且 参与度评分 > 20
计划
- 1. 审查门户中任何现有的评分模型
- 创建契合度评分(公司契合度+人物画像匹配)
- 创建或更新参与度评分(带衰减的行为信号)
- 等待4-6小时让HubSpot重新计算所有联系人
- 验证评分分布和准确性(状态后)
状态前
- 1. 导航至营销 > 潜在客户评分
- 记录任何现有评分(您总共限制5个)
- 审查现有评分标准——决定是更新还是替换
- 检查公司上的ICP层级属性是否已完全填充(状态后检查运行create-icp-tiers)
执行
创建契合度评分
- 1. 前往营销 > 潜在客户评分
- 点击创建评分
- 选择契合度作为评分类型
- 选择联系人作为评分对象
- 命名描述性名称(例如:潜在客户契合度评分)
评分组1:ICP公司层级
使用关联公司属性 > ICP层级:
以下是起始点——30天后根据实际转化数据校准。
| 标准 | 条件 | 分数(建议范围) |
|---|
| 主要ICP公司 | ICP层级为层级1 - 主要ICP | +25至+35 |
| 次要ICP公司 |
ICP层级为层级2 - 次要ICP | +15至+25 |
| 三级ICP公司 | ICP层级为层级3 - 三级ICP | +5至+15 |
| 非ICP公司 | ICP层级为非ICP | -10至-20 |
评分组2:人物画像/职位
使用联系人属性 > 职位 > 包含任一:
以下是起始点——调整职位和权重以匹配您的买家人物画像。
| 标准 | 示例职位值 | 分数(建议范围) |
|---|
| C级高管 | CEO、COO、CFO、CTO、CRO、CMO、首席营收官 | +20至+30 |
| 副总裁级领导 |
运营副总裁、营销副总裁、销售副总裁、财务副总裁 | +20至+30 |
| 总监级 | 运营总监、营销总监、采购主管、财务总监 | +15至+25 |
| 经理级 | 工程经理、运营经理、营销经理、采购经理 | +10至+20 |
| 其他相关职位 | 分析师、协调员、专员(如果与您的销售流程相关) | +5至+10 |
根据您的买家人物画像自定义这些职位。分数值应反映每个人物画像成为您产品决策者或支持者的可能性。以上范围是起始点——30天后审查并根据实际转化的职位进行调整。
评分组3:负面契合度信号
硬退信原因已知 | -50 |
| 全局取消订阅 | 已取消所有邮件订阅 = 是 | -100 |
- 6. 设置整体分数上限(建议:100)
- 保存并开启
创建参与度评分
- 1. 点击创建评分(或编辑现有参与度评分)
- 选择参与度作为评分类型
- 选择联系人作为评分对象
- 命名描述性名称(例如:潜在客户参与度评分)
正面参与度标准
| 标准 | 条件 | 分数 | 衰减 |
|---|
| 打开营销邮件 | 上次营销邮件打开日期在最近30天内 | +15 | 每月 |
| 点击营销邮件 |
上次营销邮件点击日期在最近30天内 | +25 | 每月 |
| 访问网站 | 会话次数 > 0 | +20 | 每季度 |
| 提交表单 | 表单提交次数 > 0 | +30 | 每季度 |
负面参与度标准
| 标准 | 条件 | 分数 |
|---|
| 6个月以上无邮件活动 | 上次营销邮件打开日期 > 180天前 | -20 |
- 5. 设置整体分数上限(建议:100)
- 保存并开启
示例综合评分框架
供参考,以下是两个评分如何协同工作以对联系人进行优先级排序:
| 联系人画像 | 契合度评分 | 参与度评分 | 优先级 |
|---|
| 层级1公司的CEO,本周点击了邮件 | ~60 | ~55 | 最高 |
| 层级2公司的运营总监,提交了表单 |
~40 | ~50 | 高 |
| 层级3公司职位未知,仅打开过邮件 | ~10 | ~15 | 中 |
| 无职位,非ICP,6个月无活动 | ~-25 | ~-20 | 最低 |
生命周期推进
如果您希望基于评分自动推进联系人通过生命周期阶段:
- - 定义综合阈值(例如:契合度评分 > 30 且 参与度评分 > 20 = MQL;通常综合阈值在40-60范围内,但根据您的管道校准)
- 将其构建为单独的工作流(不属于评分模型本身)
- 这是与构建评分模型分开的独立任务
状态后
等待4-6小时让HubSpot完全重新计算所有联系人评分。 新的潜在客户评分工具异步处理,大型数据库需要时间。
验证
- 1. 前往联系人 > 联系人
- 点击编辑列并将两个评分属性添加到可见列
- 按契合度评分降序排序
检查前20个联系人:
- - 职位应为目标人物画像(CEO、运营副总裁、营销总监等)
- 关联公司应为层级1或层级2
- 如果非相关联系人出现在顶部,请审查评分标准是否存在问题
检查底部联系人:
- - 升序排序(最低分优先)
- 底部联系人应为已取消订阅、已退信或非ICP公司的联系人
- 如果相关联系人出现在底部,请审查负面信号权重
检查评分分布:
- - 筛选契合度评分 > 50:高优先级契合度(应为最佳潜在客户)
- 筛选契合度评分20-50:中等契合度
- 筛选契合度评分1-19: