When to use this prompt
When standardizing lead scoring definitions across marketing and sales
When onboarding new sales/SDR team members
When refining qualification workflows for manufacturing environments
When improving alignment between demand-generation and sales operations
The prompt
Provide an explanation of lead scoring criteria in the context of [INDUSTRY_TYPE] B2B leads. Identify what behaviors or attributes signal a high-quality lead, and describe how teams should prioritize follow-ups based on these indicators. The final output should be framed as a brief internal guide, written in a professional and structured tone, to support both sales and marketing alignment.
Variables to replace:
Real-life example of how to use this prompt
To start, let’s assume I’m a senior marketer at ABB Motion. The prompt in the context of ABB Motion would look like:
As you can see, I emphasized clarity around behavioral and attribute-based scoring while framing the output as a practical internal guide that supports consistent follow-up prioritization.

Example output from ChatGPT for this prompt
And here's the output:
Below is a concise, professional internal guide tailored for alignment between Sales and Marketing at ABB Motion.
Internal Guide: Lead Scoring Criteria for Manufacturing B2B Leads
Purpose: Establish shared expectations between Sales and Marketing for identifying, prioritizing, and following up with high-quality manufacturing leads.
1. Overview of Lead Scoring in a Manufacturing Context
Lead scoring helps quantify the quality and readiness of a manufacturing-sector prospect by evaluating both fit (attributes) and engagement (behaviors). A higher score indicates stronger alignment with ABB Motion’s target profile and a higher likelihood of progressing toward an opportunity.
2. Attribute-Based Criteria (Lead Fit)
These criteria evaluate whether the organization matches ABB Motion’s strategic focus areas.
A. Company Profile
Industry Alignment: OEMs, system integrators, and end users in sectors such as HVAC, water/wastewater, pulp & paper, mining, and industrial automation.
Revenue & Size: Mid-market and enterprise organizations with complex motion control needs.
Installed Base Potential: Existing electric motors, drives, or rotating equipment where modernization or retrofit opportunities are likely.
B. Role & Decision Influence
Primary Targets: Engineering managers, maintenance managers, operations leaders, procurement leads, and automation specialists.
Buying Center Fit: Involvement in specifying motors, drives, condition monitoring, or energy-efficiency initiatives.
C. Strategic Potential
Long-Term Value: Multi-site operations, planned expansions, recurring maintenance needs, or alignment with sustainability/energy optimization mandates.
Technology Maturity: Organizations actively pursuing digitalization (monitoring, predictive maintenance, connectivity).
Indicators of High Fit:
Operates in ABB Motion’s priority verticals
Has significant equipment lifecycle or modernization needs
Strong technical decision-maker engaged early
Demonstrates interest in energy efficiency, reliability, or automation outcomes
3. Behavior-Based Criteria (Lead Engagement)
These criteria measure intent and readiness based on the lead’s actions.
A. High-Intent Behaviors
Requesting a product quote, engineering consultation, or site assessment
Downloading technical datasheets, specification packages, or system design guides
Completing forms related to RFQs, retrofit inquiries, or project scopes
Engaging in configurators, ROI calculators, or product selectors
Participating in technical webinars, demos, or events focused on drives/motors optimization
B. Medium-Intent Behaviors
Opening multiple emails related to a product family
Viewing product pages for motors, drives, lifecycle services, or digital solutions
Returning to the website repeatedly over multiple days
Downloading whitepapers related to energy optimization, reliability, or predictive maintenance
C. Low-Intent Behaviors
General newsletter signups
Single content downloads with broad topics
Basic contact-us forms without detail
Indicators of High Intent:
A clear project timeline mentioned
Engagement with tools that imply near-term purchasing
Behavior signaling internal research for modernization or upgrades
4. Scoring and Prioritization Guidance
Tier 1: Sales-Ready Leads (High Fit + High Intent)
What they look like:
Strong industry and role fit
Clear project, budget, or timeline signals
Technical asset downloads or direct consultation requests
Actions:
Immediate outreach within 24 hours
Prepare conversation around project scope, technical requirements, and site conditions
Sales logs feedback to Marketing for refining score thresholds
Tier 2: Marketing-Qualified but Not Yet Sales-Ready (High Fit + Medium/Low Intent)
What they look like:
Perfect target profile but limited behavioral activity
Early-stage research or broad content consumption
Actions:
Marketing continues nurturing with technical content and case studies
Sales receives visibility but waits for higher-intent trigger before outreach
Trigger examples: configurator use, RFQ form, multiple product-page visits
Tier 3: Low Fit Leads
What they look like:
Industries outside ABB Motion’s priority segments
Roles with minimal influence on drive/motor selection
Broad, consumer-like engagements
Actions:
Low or no sales involvement
Marketing keeps in long-term nurture streams
Excluded from short-term sales pipeline metrics
5. Process Alignment Between Sales & Marketing
Weekly review: Validate lead quality, identify patterns, adjust scoring.
Feedback loop: Sales communicates which leads converted, which did not, and why.
Consistency: Both teams use the same definitions of “MQL,” “SQL,” and “Sales-Ready.”
Refinement: Scoring rules update quarterly to reflect market conditions and product focus areas.
6. Key Takeaways
High-quality manufacturing leads show strong fit and intent.
Prioritize leads with technical engagement and clear project indicators.
Maintain a strong feedback loop to continually improve accuracy.
Sales and Marketing must share one consistent framework to ensure efficiency and trust.
Or to be more specific:

Pro tips
Add specific behaviors (e.g., demo requests, asset downloads) to tailor the scoring
Combine demographic and engagement scoring for more accuracy
Use this as a foundation for building your scoring model in CRM or MAP tools
Review scoring criteria quarterly as buyer behavior and markets evolve
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