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ChatGPT Prompt for B2B Manufacturing Lead Scoring Guide

This prompt lets ChatGPT create a clear internal guide explaining lead scoring criteria for B2B manufacturing leads.

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:

[INDUSTRY_TYPE]

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:

Provide an explanation of lead scoring criteria in the context of manufacturing 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, structured tone, to support alignment between sales and marketing at ABB Motion.

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.

ChatGPT Prompt for B2B Manufacturing Lead Scoring Guide

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:

ChatGPT Prompt for B2B Manufacturing Lead Scoring Guide Output

Pro tips

0.

Add specific behaviors (e.g., demo requests, asset downloads) to tailor the scoring

1.

Combine demographic and engagement scoring for more accuracy

2.

Use this as a foundation for building your scoring model in CRM or MAP tools

3.

Review scoring criteria quarterly as buyer behavior and markets evolve

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qualified demand.

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