A data-driven framework for managing proof-of-concept engagements in enterprise media sales. Built to replace ad-hoc POC management with a systematic approach — from scoping success criteria through making the Go/No-Go call.
In media sales, proof-of-concept deals are where large contracts are won or lost. Most teams run POCs with spreadsheets, email chains, and gut-feel decisions. This tool brings structure:
- Consistent evaluation — every POC is scored against weighted criteria, not vibes
- Early risk detection — status dashboards surface "At Risk" and "Blocked" POCs before they fail silently
- Defensible decisions — the Go/No-Go engine produces a recommendation with per-criterion reasoning that stakeholders can review
- Repeatable process — templates ensure every POC follows the same lifecycle
graph LR
A[Scope & Propose] --> B[Define Success Criteria]
B --> C[Build RACI & Timeline]
C --> D[Execute POC]
D --> E[Track Progress]
E --> F{Go/No-Go Decision}
F -->|PROCEED| G[Convert to Paid]
F -->|EXTEND| H[Focused Extension]
F -->|TERMINATE| I[Document & Close]
H --> E
style A fill:#4a90d9,stroke:#2c6faa,color:#fff
style B fill:#4a90d9,stroke:#2c6faa,color:#fff
style C fill:#4a90d9,stroke:#2c6faa,color:#fff
style D fill:#5cb85c,stroke:#4cae4c,color:#fff
style E fill:#5cb85c,stroke:#4cae4c,color:#fff
style F fill:#f0ad4e,stroke:#eea236,color:#fff
style G fill:#28a745,stroke:#1e7e34,color:#fff
style H fill:#ffc107,stroke:#e0a800,color:#333
style I fill:#dc3545,stroke:#c82333,color:#fff
Input company, product, timeline, and stakeholders. The builder auto-generates:
- Success Criteria — tailored to the product category, weighted by customer goals
- RACI Matrix — maps stakeholder responsibilities across every milestone
- Milestone Timeline — evenly distributed checkpoints from kickoff to decision
- Evaluation Scorecard — ready-to-use scoring template
Real-time overview of all engagements:
- Status indicators: On Track / At Risk / Blocked
- Completion percentage with progress bars
- Days remaining with overdue alerts
- Expandable details showing stakeholders, milestones, and current scores
Score each criterion on a 1-10 scale and get a weighted recommendation:
┌─────────────────────────────────────────────────┐
│ │
│ RECOMMENDATION: EXTEND │
│ Composite Score: 6.15/10 │
│ │
├─────────────────────────────────────────────────┤
│ │
│ CTR Improvement ████░░░░░░ 5/10 Needs │
│ Brand Safety █████████░ 9/10 Exceeds │
│ Integration Effort ████░░░░░░ 4/10 Critical │
│ CPM Efficiency ██████░░░░ 6/10 Needs │
│ │
│ Critical Gaps: Integration Effort │
│ Strengths: Brand Safety │
│ │
│ → Extend 4 weeks, focus on integration │
│ → Weekly check-ins with technical lead │
│ → Must reach 7.5 composite to proceed │
│ │
└─────────────────────────────────────────────────┘
Decision thresholds:
| Composite Score | Recommendation |
|---|---|
| >= 7.5 | PROCEED — Convert to paid engagement |
| 5.5 - 7.4 | EXTEND — Address gaps, re-evaluate |
| < 5.5 | TERMINATE — Fundamental misalignment |
Safety valve: any single criterion scoring <= 4 triggers review, even if the composite is high.
Downloadable markdown templates for:
- POC Proposal
- Weekly Status Report
- Executive Summary
- Go/No-Go Scorecard
git clone https://github.com/cjf-iii/poc-success-tracker.git
cd poc-success-tracker
chmod +x run.sh && ./run.shOr manually:
pip install -r requirements.txt
streamlit run app.pyOpen http://localhost:8501 in your browser.
poc-success-tracker/
├── app.py # Main Streamlit application (4 tabs)
├── engine/
│ ├── criteria_builder.py # Success criteria, RACI, timelines, scorecards
│ └── decision_engine.py # Go/No-Go scoring with weighted criteria
├── data/
│ └── sample_pocs.py # 3 sample POC records (media industry)
├── requirements.txt
├── run.sh
└── README.md
Three realistic POC scenarios from media technology:
| POC | Customer | Product | Status |
|---|---|---|---|
| POC-2024-001 | Paramount Global | AdVantage Analytics Platform | On Track |
| POC-2024-002 | iHeartMedia | PrecisionTarget AI | At Risk |
| POC-2024-003 | ESPN / Disney | StreamSync Distribution Hub | Blocked |
CJ Fleming — Media sales leader with 15+ years of experience spanning digital advertising, sports media, and SaaS. Holds a Columbia University certification in Artificial Intelligence. Built this tool to demonstrate how structured frameworks and data-driven decision-making improve POC conversion rates in enterprise sales.