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FeaturesSaaS FactoryUpdated February 19, 2026

Churn Prediction & Automated Upsell Automation

Churn Prediction & Automated Upsell Automation

Available from: v1.0.3

SaaS Factory includes a fully autonomous revenue protection and expansion stack. This covers two tightly integrated capabilities: churn prediction (identifying customers at risk of leaving) and upsell automation (identifying customers ready to expand and acting on that signal without human intervention).

Both capabilities run continuously with no human required at any step.


Churn Prediction

How It Works

Churn risk is computed per customer using a rolling ML/AI scoring pipeline that ingests behavioural usage signals:

  • Login frequency — declining session activity relative to the customer's own baseline
  • Feature adoption — breadth and depth of feature usage over time
  • API call volume — drops in programmatic usage
  • Support ticket sentiment — negative sentiment trends in support interactions

These signals are combined into a single churn risk score (0–100) and bucketed into a churn risk tier:

TierScore RangeMeaning
low0–24Healthy, no action needed
medium25–49Early warning, monitor closely
high50–74At-risk, automated intervention triggered
critical75–100Imminent churn, escalated win-back sequence

Score Recalculation

Scores are recalculated:

  • On a scheduled cadence (rolling window, daily minimum)
  • On-demand when a significant usage drop event is detected (e.g. API call volume falls >50% week-over-week)

Customer Schema Fields

The following fields are available on the customer record:

churn_risk_score   Integer (0–100)
churn_risk_tier    Enum: low | medium | high | critical

Dashboard Visibility

Churn risk scores and tier trends are surfaced in the Customer Management section of the platform. Each customer record displays:

  • Current score and tier
  • Score trend over the last 30 days
  • The primary contributing signals

Automated Upsell Automation

Upsell Opportunity Detection

The upsell engine continuously monitors customers for expansion signals:

  • Plan limit proximity — customers approaching seat, API call, or storage limits
  • Usage velocity — customers whose usage is growing fast relative to their current plan ceiling

When an opportunity is detected, the customer is flagged as expansion-ready and an upsell sequence is initiated automatically.

Trigger Rules Engine

The rules engine dispatches upsell actions without human input:

  • In-app prompts — contextual upgrade nudges served within the product at relevant moments
  • Email campaigns — automated outreach tied to the specific limit or feature driving the opportunity

All upsell events are logged to the deal pipeline for full revenue attribution and reporting.


Dunning-to-Win-Back Workflow

The billing engine's dunning flow extends beyond basic past_due invoice retries. Customers who churn through non-payment enter an automated win-back sequence:

  1. Re-engagement email cadence — timed series of emails with account recovery messaging
  2. Discount offer generation — automated generation of personalised discount offers where appropriate
  3. Outcome tracking — reactivated or lost outcomes are recorded and fed back into the churn model as training signal, improving future predictions

Dunning vs. Win-Back

StageTriggerAction
DunningInvoice past_duePayment retry + notification emails
Win-BackSubscription churned via non-paymentRe-engagement cadence + discount offer

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