Batch School Risk Analysis
Upload a CSV with one school per row. All schools are scored instantly. Click any row for a full AI deep-dive narrative.
📂
Click to upload or drag and drop your CSV
Columns: school_name, pending_dues_pct, product_usage, hardware_pct...
| School | Score | Tier | Red Flags | Pending Dues | Product Usage | Hardware | Training | Size |
|---|
Click a school row to generate the AI narrative.
Analyse schools directly from your Google Sheet
Paste your public Google Sheet URL below. The tool pulls your data and scores all schools instantly — no CSV download needed.
1
Get the template
Open our pre-filled Google Sheet with 40 sample schools, or download the CSV and import it.
2
Make it public
In Google Sheets: Share → Anyone with the link → Viewer. Copy the URL.
3
Paste and analyse
Paste the Sheet URL below and click Analyse. All schools are scored in seconds.
🔒 Your data is never stored. It is fetched, scored in your browser, and discarded when you close the tab.
| School | Score | Tier | Red Flags | Pending Dues | Product Usage | Hardware | Training | Size |
|---|
Click a school row to generate the AI narrative.
How to use this tool
Single School Analysis
1
Load demo or fill the form
Click Load Demo Data for an instant example, or fill in your own school metrics. Every field shows the valid range and what to enter.
2
Click Analyse School Risk
The risk score is calculated instantly in your browser using domain-weighted scoring — no AI call needed for the score itself.
3
Read the risk card and breakdown
See the score, tier, any red flags triggered, and a bar chart showing exactly which metrics are driving the risk.
4
Get the AI narrative
Claude writes a 3-sentence narrative: current situation, root cause, and one specific action for the field team this week.
Batch Analysis (CSV or Google Sheet)
1
Get the template
Download the 40-school CSV sample, or open the Google Sheet template and make a copy. Both have the correct column structure.
2
Fill in your school data
Replace the sample rows with real data. Keep column headers exactly as they are.
3
Upload CSV or paste Sheet URL
For CSV: use the Batch Upload tab. For Google Sheet: share as Anyone with link can view, then paste the URL in the Google Sheet Sync tab.
4
Filter, sort and deep dive
Filter by Red/Amber/Green. Sort by risk. Click any row to generate an AI narrative for that school.
Risk Tiers Explained
● Red — High Risk
Score ≥ 65 OR any red flag
Immediate intervention required. Field visit within 48–72 hours. Account likely to churn without action.
● Amber — Watch
Score 35–64, no red flags
Early warning signals. Proactive check-in within 2 weeks. Monitor closely at renewal.
● Green — Healthy
Score < 35, no red flags
School is engaged and on track. Maintain regular cadence. Good candidate for upsell or referral.
Metric Definitions & Weights
Higher weight = more impact on score. A red flag on any metric forces the tier to Red regardless of the calculated score.
| Metric | Weight | What to enter | Good | Warn | Red Flag |
|---|
Pending Dues % | 35% | % of annual billing unpaid. E.g. ₹3L of ₹10L = 30. | <25% | 50–75% | ≥75% |
Product Usage | 30% | Select: High / Medium / Low / None | High | Low | None |
Hardware % Classes | 10% | % of classrooms with working hardware (0–100) | >75% | <50% | <25% |
Training Done | 10% | Sessions done this year (0–4) + days since last session | 4/4, ≤45 days | 1/4, >45 days | 0 ever or ≥90 days |
Open Tickets | 5% | Count of open tickets + age of oldest (days) | 0 tickets | 2+ | ≥10 or oldest >45 days |
NPS | 5% | Latest + previous NPS score (0–10) | ≥8 | <5 | 2 consecutive <5 |
Student Performance | 3% | Average marks % across classes using the product | >70% | <70% | <50% |
Teacher Attendance | 2% | % attending last two training sessions | ≥75% | <75% | 2 consecutive <75% |
Face Change | Flag only | Yes/No + days since new rep visited | No | Yes | Yes + no visit >15 days |
School Size | 0% — info only | Total enrolled students — for prioritisation only | Any | — | No flag |