Predict Enrollment Before It Happens
Our AI analyzes historical patterns, current pipeline data, and conversion trends to forecast exactly how many students will enroll per grade — weeks before the admission deadline.
- ML-powered enrollment predictions per grade
- Historical trend analysis across years
- Conversion probability for pipeline leads
- What-if scenario modeling
- Capacity planning recommendations
- Weekly forecast accuracy tracking
Sound Familiar?
- Guessing enrollment numbers until the last day: AI predicts final enrollment 4-6 weeks before deadline with 85%+ accuracy
- No capacity planning — sections decided reactively: Proactive section planning based on demand forecasts per grade
- Marketing budget set without data: Forecast-driven budget allocation to grades needing more enquiries
Complete Enrollment Forecast Features
Everything you need to modernize your school's enrollment forecast.
- ML Prediction Engine: Analyzes 3+ years of historical data, current pipeline velocity, and seasonal patterns to forecast enrollment.
- Grade-Wise Forecasts: Individual predictions per grade with confidence intervals and trend direction indicators.
- What-If Scenarios: Model scenarios: 'What if we increase marketing spend by 20%?' or 'What if we add 10 more seats in Grade 1?'
- Accuracy Tracking: Weekly comparison of forecast vs actuals. Model self-improves as more data comes in.
- Conversion Probability: Each pipeline lead gets a probability score of converting to enrollment based on current engagement.
- Capacity Alerts: Automatic alerts when forecasted demand exceeds available seats for any grade.
Get Started in 4 Simple Steps
- Historical Data Import: System ingests 3+ years of admission data to establish baseline patterns.
- Real-Time Analysis: AI continuously analyzes current pipeline, conversion rates, and seasonal patterns.
- Generate Forecasts: Weekly updated forecasts per grade with confidence intervals.
- Plan & Act: Use forecasts to plan sections, allocate marketing budgets, and set admission targets.
Frequently Asked Questions
How accurate are the forecasts?
After 2+ years of historical data, forecasts are typically 85-90% accurate 4 weeks before admission deadline. Accuracy improves as the deadline approaches.
What data does the AI use?
Historical enrollment by grade, current pipeline lead count and stages, conversion rates by source, seasonal enquiry patterns, and year-over-year growth trends.
Can I model different scenarios?
Yes. The What-If module lets you adjust variables like marketing spend, seat count, or conversion targets to see projected impact on enrollment.
Do I need 3 years of data?
The AI works with as little as 1 year of data but accuracy improves significantly with 3+ years. During the first year, it uses industry benchmarks as a baseline.
How often are forecasts updated?
Forecasts update weekly by default, but you can trigger a refresh anytime as pipeline data changes.