Analytics · Predictive
Customer Churn Prediction and Predictive Satisfaction Scoring (CSAT/NPS)
Predict customer satisfaction before the survey comes back. Predictive Satisfaction Score scores every customer from behavioral and operational signals, so you catch dissatisfaction while you can still act.
What it does
Forecast satisfaction from behavioral signals.
- Predict satisfaction without waiting for surveys
- Detect at-risk customers earlier
- Extend visibility beyond survey respondents
- Enable proactive outreach and intervention
How it works
A clear path from start to result
Unify
Bring survey, behavioral, operational, and interaction signals into one customer dataset.
Model
Train a model on your history to predict satisfaction and NPS for every customer.
Score
Refresh predictions continuously, covering the customers who never answer a survey.
Explain
Surface the drivers behind each score and flag who is turning at-risk.
Intervene
Route at-risk customers into outreach, then confirm the predicted score recovered.
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Run it continuously, on web and mobile
- Predicted satisfaction and NPS scored continuously across your whole base
- Behavioral, operational, and survey signals unified into one model
- Driver-level explanation and at-risk alerts pushed to CRM and workflows
What you get
Deliverables you can act on
Predictions
Predicted satisfaction and NPS across the full base, with model accuracy.
Satisfaction Drivers
What moves satisfaction, ranked by impact, with sensitivity analysis.
At-Risk Customers
Per-customer predicted risk, prioritized for proactive outreach.
Risk Distribution
High, medium, and low predicted risk across your whole base.
Methodology
A survey score tells you where you were, not where you’re going
A raw satisfaction score reports how customers felt last period, after the fact. We fit a model to your survey drivers, forecast each customer’s next-period score and six-month trajectory, and surface who is trending down, so you act on where satisfaction is heading, not just where it has been.
A static survey score
- Reports the score after the period has closed
- A lagging indicator of how customers already felt
- No view of where the score is heading
- Reacts after satisfaction has already dropped
Intellimark predictive satisfaction
- Predicts a satisfaction score for every customer in your data
- Forecasts the next-period score and six-month trajectory per customer
- Weights the survey drivers that move the score most, via regression
- Flags customers trending down early, while you can still act
Grounded in the research on survey nonresponse and behavioral prediction: Non-response bias in satisfaction surveys (peer-reviewed, PMC) · Leveraging non-respondent data in satisfaction modeling (Journal of Business Research) · Predictive NPS and CSAT (QuestionPro)
Market reality
Why this matters now
10-30%
is the range for a good survey response rate, so most customers never tell you how they feel
SurveyMonkey37%
of organizations feel well-prepared to act on real-time customer feedback, so most respond too late
CRM Magazine, citing ForresterCommon
questions
What is a Predictive Satisfaction Score? +
A model that predicts how satisfied each customer is, and their churn risk, from behavioral, operational, and survey signals, so you see sentiment without waiting for a response.
How is it different from CSAT or NPS surveys? +
Surveys measure the customers who answer, after the fact. Prediction scores every customer continuously, including the silent majority, and flags risk early enough to act.
How accurate is it? +
Models are trained and validated on your own history, and we report predicted-versus-actual accuracy so you can trust the score before acting on it.
Who uses it? +
Customer success, retention, and CX teams who need to intervene with at-risk customers before a renewal slips or a relationship sours.