Automations
Analytics and the risk zone
Find school reports, distinguish payments from earned revenue, and read student-risk factors and confidence.
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Open Analytics and choose the report for your question: CRM, finances, payments, schedule, teachers, retention, risk, forecasts or marketing. Reports have separate permissions; general analytics access does not automatically reveal financial figures.
Check the period and scope
Check the reporting period and selected branch before comparing numbers. Receiving a payment and earning revenue by delivering lessons are separate events. The explanation next to a metric shows its definition and calculation. A missing denominator appears as “—”, rather than zero.
Observed LTV and estimated lifetime
The retention summary shows average LTV as mean lifetime lesson-charge revenue in UAH. This is revenue already recorded, not predicted future payments. Old foreign-currency balances are not added to UAH revenue.
Average lifetime in months is a separate churn-based estimate. It does not replace observed LTV or guarantee future revenue.
Thirty-day churn uses the active/paused student base at the start of the window. Twelve-month retention follows its opening base through the year: later arrivals are excluded, and repeat archives count once. Without an opening base, the result is “—”.
Marketing: spend to first payment
CAC divides marketing spend by attributed students whose first successful invoice-backed payment falls in the selected period. A student may have arrived earlier; leads, conversions and payments use their own event dates.
ROMI compares net successful payment revenue with marketing spend. Payback uses CAC and average monthly realised revenue. Marketing data can be cached for five minutes.
Read more in leads and funnel and marketing analytics.
Read risk together with its evidence
Open Analytics → Student risk. Read the health score, risk level, factors and confidence together. Sparse evidence lowers confidence; it is not a certain prediction that a student will leave.
A first calculation or model update is not presented as a change in student behaviour. High and critical risk totals use the latest student-health levels across the selected scope, not just rows on the current page.
Use the reasons to decide what to check: attendance, upcoming lessons, homework or payment context. Speak with the student before drawing a conclusion. Configure automatic notifications separately in automations.
See the student churn-risk overview.