An AI-powered skill designed to automate lead qualification and scoring matrices within major CRM platforms.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lead-scoring
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install lead-scoring using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Lead Scoring Autopilot?
Lead Scoring Autopilot provides a systematic framework for assigning numerical values to leads based on their conversion probability. By integrating directly with CRMs like HubSpot and Salesforce, this skill allows teams to combine explicit demographic data with implicit behavioral signals.
Using Openclaw Skills, businesses can transform their raw lead data into actionable insights, ensuring that sales teams focus exclusively on high-intent prospects. The skill provides the logic needed to build complex scoring matrices, implement engagement tracking, and manage lead lifecycle stages automatically.
Lead Scoring Autopilot Use Cases
- Defining and automating MQL and SQL criteria for better sales and marketing alignment.
- Implementing behavioral engagement scoring for website visits, content downloads, and email interactions.
- Creating demographic fit scores based on company size, industry, and job seniority.
- Automating lead lifecycle transitions within HubSpot, Salesforce, or Pipedrive.
- Setting up automated lead decay to deprioritize inactive prospects over time.
How Lead Scoring Autopilot Works
- The skill analyzes historical conversion data to identify the attributes of successful customers.
- It establishes a dual-axis scoring model covering Fit (demographics) and Interest (behavior).
- Configuration of custom CRM properties and number fields occurs to store scoring data.
- Automation workflows are triggered by contact activities to update scores in real-time.
- Thresholds are set to automatically flag leads as sales-ready when they reach specific score milestones.
Lead Scoring Autopilot Setup
To begin using this lead scoring solution within the Openclaw Skills framework, configure your CRM credentials:
# For HubSpot Integration
export HUBSPOT_ACCESS_TOKEN='your_hubspot_token'
# For Salesforce Integration
export SALESFORCE_ACCESS_TOKEN='your_salesforce_token'
Ensure your CRM has custom number properties created for Lead Score, Demographic Score, and Behavioral Score before initiating the automation workflows.
Lead Scoring Autopilot Data Schema & Taxonomy
The skill organizes data through a structured set of properties and metadata to ensure consistency across CRM platforms:
| Property | Data Type | Description |
|---|---|---|
| Lead Score | Number | The aggregate score (typically 0-200) reflecting overall quality. |
| Demographic Score | Number | Points assigned based on firmographic and professional fit. |
| Behavioral Score | Number | Points accumulated through engagement actions and intent signals. |
| Last Score Update | DateTime | The timestamp of the most recent automated scoring calculation. |
| Lifecycle Stage | String | The current status (e.g., Lead, MQL, SQL) based on score thresholds. |
Lead Scoring Autopilot Advanced Features
- Predictive Lead Scoring using machine learning models like Random Forest or XGBoost for historical data analysis.
- Account-Based Scoring (ABM) to aggregate engagement across multiple contacts within the same organization.
- Dynamic Scoring Adjustments for seasonal peaks or campaign-specific engagement boosts.
- Integration with marketing automation for score-based email drip triggers and personalized content display.
SKILL.md
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