INDUSTRY CAPSTONE
AI Lead Qualification & Next-Best-ActionEngine for a Small Business
Build a lightweight lead-scoring workflow that ranks inbound prospects, explains the score, and recommends the next sales action using realistic CRM-style data.
Portfolio Project
Decision Making
Enrollment Closed
Enrollment for this capstone is closed right now. Get an email the moment it reopens.
Duration2 Weeks
DeliverySelf Paced + Mentor Review
LevelBeginner–Intermediate (Applied Business AI)
ResourcesSynthetic CRM dataset, scoring notebook, sales playbook template
Professional Capability Objective
Build a lightweight lead-scoring workflow that ranks inbound prospects, explains the score, and recommends the next sales action using realistic CRM-style data. The capstone is designed around a build-and-validate workflow so the learner produces working evidence, not only conceptual recommendations.
Industry Challenge
Small sales teams cannot deeply research every inbound lead. The challenge is prioritizing opportunities without creating a black-box score that salespeople do not trust.
Your analysis must consider:
- ▶Define what “qualified” means for the target SME.
- ▶Engineer features from source, engagement, company profile, timing, and prior outcomes.
- ▶Compare simple rule-based scoring with a predictive model.
- ▶Explain the top drivers behind each score.
- ▶Set thresholds for nurture, sales follow-up, and deprioritization.
- ▶Design a human override and feedback loop so the scoring improves over time.
Why Employers Value This
Demonstrates your ability to:
- ▶Build a practical lead-scoring dataset and model.
- ▶Explain predictions in sales language.
- ▶Set action thresholds based on business capacity.
- ▶Design feedback loops between sellers and the model.
- ▶Set thresholds for nurture, sales follow-up, and deprioritization.
- ▶Design a human override and feedback loop so the scoring improves over time.
Skills You'll Develop
Lead feature design
Create meaningful model inputs from raw operational or business data while avoiding leakage and noise.
Classification / scoring
Adapt proven models to a focused business or technical use case and measure class-level performance.
Explainability
Explain model outputs in language and evidence that business or technical reviewers can understand and challenge.
Sales workflow design
Connect AI scoring or recommendations to realistic seller actions, feedback loops, and pipeline processes.
Threshold selection
Choose operating thresholds that balance missed events, false alerts, capacity, and business consequences.
Professional Portfolio Deliverables
Lead Scoring Prototype
A working model or rules+ML hybrid that assigns conversion propensity to inbound leads.
Seller Action Board
A ranked pipeline showing score drivers, recommended action, and follow-up priority.
Sales Playbook
Qualification thresholds, human overrides, monitoring metrics, and rollout guidance.
Industry-Recognized Certificate
Stand out with a verified certificate from NetZeroX AI.
What You Will Learn
- Build a practical lead-scoring dataset and model.
- Explain predictions in sales language.
- Set action thresholds based on business capacity.
- Design feedback loops between sellers and the model.
Program Delivery & Engagement: 4 Stages
STAGE 1
Capstone Kick-off
Define ICP and qualification labels.
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STAGE 2
Build & Analysis
Build and validate the scoring logic.
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STAGE 3
Practitioner Review
Create ranked pipeline and next-best-action rules.
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STAGE 4
Final Submission & Demo
Present pilot metrics, rollout plan, and demo.
Completion standard: submit the working artifact, evaluation evidence, limitations, and a short final presentation. The certificate should reflect demonstrated capability rather than content consumption alone.
Analyse. Compare. Recommend. Lead with Confidence.
Build in-demand commercial and analytical skills. Solve real energy & AI challenges.
Enrollment Closed
Enrollment for this capstone is closed right now. Get an email the moment it reopens.
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