Manufacturing Lead Scoring Rules (JSON)
Plug-and-play JSON config for manufacturing lead scoring. Prioritize by company size, tech stack, and engagement.
JSON Configuration
Ready to import directly into your CRM or marketing automation tool
"{\n \"$schema\": \"https://optif.ai/schemas/lead-scoring-v1.json\",\n \"name\": \"Manufacturing Lead Scoring\",\n \"version\": \"1.0\",\n \"description\": \"Lead scoring optimized for manufacturing industry\",\n \"industry_specific\": {\n \"plant_indicators\": {\n \"multiple_facilities\": 15,\n \"expansion_signals\": 20,\n \"equipment_refresh_cycle\": 10\n },\n \"production_volume\": {\n \"high\": 20,\n \"medium\": 10,\n \"low\": 5\n }\n },\n \"role_scoring\": {\n \"Plant Manager\": 25,\n \"Operations Director\": 20,\n \"Procurement Manager\": 15,\n \"Quality Manager\": 10,\n \"Production Supervisor\": 5\n },\n \"buying_signals\": {\n \"rfq_submitted\": 30,\n \"spec_sheet_download\": 15,\n \"case_study_manufacturing\": 10,\n \"calculator_used\": 20\n },\n \"timing_signals\": {\n \"fiscal_year_end\": 15,\n \"budget_cycle\": 10,\n \"expansion_announced\": 25\n },\n \"disqualifiers\": {\n \"wrong_industry\": -50,\n \"too_small\": -30,\n \"competitor_customer\": -20\n }\n}"💡 Usage Tip
Paste the copied JSON into a text editor, save as .json format, then import into your CRM.
Usage Tips
- 1Review the complete structure before importing into your system
- 2Back up your current configuration before applying changes
- 3Start with default values and iterate based on your data
- 4Share with your RevOps team for validation before go-live
- 5Monitor performance metrics for 2 weeks post-implementation
Example Use Cases
New RevOps hire needed to understand existing scoring logic quickly.
Downloaded this config and used it as documentation. Onboarded and making improvements within first week.
Team wanted to A/B test different scoring approaches.
Used this config as control group, tested variations. Found 23% improvement in MQL-to-SQL conversion.
Who It's For
👤 Manufacturing-General Sales Ops
Pain Points:
- •Inconsistent follow-up from team members
- •Difficulty measuring ROI of sales activities
- •Reps spending too much time on manual tasks
- •Pipeline visibility and forecasting challenges
- •Slow response times to inbound leads
Goals:
- •Ensure 100% follow-up compliance
- •Prove ROI of sales initiatives
- •Free up 10+ hours/week per rep
- •Improve forecast accuracy to 90%+
- •Achieve <5 minute lead response time
How to Use
- 1
Review the configuration
Understand each field and how it affects behavior.
- 2
Customize values
Adjust thresholds, weights, and rules for your use case.
- 3
Test in sandbox
Apply the config to a test environment first.
- 4
Monitor results
Track how the configuration affects outcomes.
- 5
Iterate based on data
Refine values based on observed performance.
Related Resources
Frequently Asked Questions
Have more questions? Feel free to contact us.
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