Customer health-score tracking
We set up a customer health-score: a composite 'health' indicator from usage, activity and engagement signals — to see who is at risk and who is growing, and react in time. Honestly upfront: a health-score is a HEURISTIC/proxy assembled from chosen signals and weights, not exact truth (bad input data or weights = a misleading score); it probabilistically points to risk, it does not predict precisely; it needs data; and the score itself changes nothing without actions on it. We build an honest indicator for prioritizing attention, not a 'thermometer that cures'.
Customer health-score tracking — overview
A customer health-score is a composite indicator of a customer's state aggregating signals: frequency and depth of product use, activity, achievement of key actions, support requests, engagement, payments. From these, by a chosen model/weights, a 'health score' is computed, flagging customers as healthy, at-risk or growing. The goal is to notice churn risk and growth opportunities earlier. Honestly about 'a heuristic, not truth', this is key: a health-score is a devised model of chosen signals and weights, not objective truth about the customer. Its quality wholly depends on which signals are taken and how they are weighted: wrong weights or 'noisy'/incomplete data give a nice but misleading score (garbage in — garbage out). A health-score is only as good as its input data and logic. We honestly design it for your reality and revise it rather than pass off an arbitrary formula as truth. Honestly about probabilism: a health-score POINTS to likely risk or growth but does not predict precisely. A customer healthy by score may leave, and an 'at-risk' one may stay. It is a tool for prioritizing attention, not a verdict. Honestly about data: a meaningful score needs sufficient and quality behavior data. On scarce data the score will be random. Honestly about 'score ≠ action', this is key: the indicator itself improves nothing. The value is in ACTIONS: which of the 'at-risk' to focus attention on (CSM 1011, interventions), what to offer the growing. A health-score without a reaction process is just a nice dashboard. Honestly about calibration: the model must be checked against real outcomes (do the 'at-risk' actually leave) and adjusted. It is a living process. Honestly about the effect: with good data and a reaction process it helps react earlier and prioritize, but it is not a retention guarantee. Honestly about access: behavior/activity data, a reaction resource are needed. An important boundary: this is a health-score (an indicator); churn-prediction (ML forecast) — 1000; the CSM role (reaction) — 1011; NPS/CSAT metrics — 1014/1015. Picture this: instead of 'we learn about a customer's problem after the fact' — an early honest risk/growth indicator with actions on it. The base price starts from 50,000 ₽ (depends on data and integration).
Problems we solve
- We learn about churn risk or customer problems too late.
- No unified view of customer 'health' and dynamics.
- Attention is distributed blindly, not by risk/opportunity.
- A past 'score' was arbitrary and misleading.
What's included in the Customer health-score tracking service
- Designing a health-score for your real signals and weights
- Assessing input-data quality and sufficiency
- Customer segmentation: healthy / at-risk / growing
- A reaction process for the score (prioritization, CSM 1011, interventions)
- Model calibration against real outcomes (a living process)
- Honest boundaries (a heuristic not truth; probabilistic; score ≠ action; no guarantee)
- A link with churn-prediction (1000) and CSM (1011)
- Handover and review with you
What you get
- An early indicator of at-risk and growing customers
- Prioritizing attention by risk/opportunity (not blindly)
- An honest score for your reality (not an arbitrary formula)
- Honest boundaries (a heuristic; probabilistic; actions needed; no guarantee)
How the work goes: steps
- We determine the signals and logic of the health-score for your product
- We assess data, set up the score and segmentation
- We build a reaction process and calibration, honestly set boundaries with you
Why PDV Expert
- Fixed price and timeline — no surprises on the invoice.
- Report and recommendations in plain language — clear without a technical background.
- In touch at every step and answering questions about the result.
FAQ
Will a health-score accurately show who will leave?
No, honestly: a health-score is a heuristic of chosen signals and weights, not exact truth. It POINTS to likely risk or growth but does not predict precisely — a customer healthy by score may leave, and an 'at-risk' one may stay. It is a tool for prioritizing attention, not a verdict. Plus the score's quality wholly depends on data and weights. We honestly build an indicator, not an oracle (for a probabilistic forecast see churn-prediction 1000).
Can a health-score be made without good data?
No, honestly: the score's quality wholly depends on input data and logic — garbage in gives garbage out. On scarce or 'noisy' data the score will be random, and wrong weights give a nice but misleading indicator. Sufficient and quality behavior data are needed. We will honestly assess them, design the model for your reality and calibrate it rather than pass off an arbitrary formula as truth.
Set up a health-score — and retention will grow?
The score itself changes nothing, honestly: this is key. The value is in ACTIONS on it: which of the 'at-risk' to focus attention on (CSM 1011, interventions), what to offer the growing. A health-score without a reaction process is just a nice dashboard. Retention grows from actions, not from the presence of an indicator. We build exactly the reaction process, not just a number on the screen.
About the provider
The «Customer health-score tracking» service is provided by PDV Expert — a team specialising in «Customer retention». We work under contract and deliver a written report with recommendations.