Not last year's cohort average. The future value of each customer, and what drives it.

Matr lets your CRM, growth, and finance teams build, interrogate, and pilot the lifetime-value logic that drives your acquisition budgets, your retention priorities, and your customer experience.

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LE PROBLÈME AUJOURD'HUI

LTV is on every dashboard. It changes almost nothing.

01

A number everywhere

Your BI tool reports LTV. Your subscription platform shows customer value. Your finance team recomputes it every quarter. Most deliver a number you can't act on.

02

An average of the past

The LTV on your dashboard is a cohort average, built from what already happened. It tells you what last year's customers were worth, not what this one will be, or why.

03

Too late to matter

By the time the quarterly figure lands, the acquisition budget is spent and the high-value customer you could have protected has quietly churned.

LES DONNÉES NÉCESSAIRES
Recommendation isn't a silo.

Ce que c'est

LTV × Churn

Protect the high-value customers most at risk, first

LTV × Recommendation

Adapt what you suggest to customer value, not just behavior

LTV × Segmentation

Build value-based segments, not just behavioral ones

Votre horizon

Valeur à un an, trois ans, sur toute la relation. MatR le fixe avec vous pendant le cadrage.

test
Ask a question. Get a model in production.
01
Describe your goal
02
Train automatically
03
Deploy in one click
04
Automate & monitor
Tell Matr what you want to predict,in plain language.
Matr identifies the right datasets and starts working.
Every step is visible and explainable. No black box.
Matr selects features, tests algorithms, and trains the model.
The model goes live, no setup.
Predictions refresh with your data, via dashboard, API, or direct integration.
Set it once. No MLOps team required.
Matr monitors performance and flags when retraining is needed.
The ML runs in production.
What a day with Matr actually looks like for a CRM team.

Detection

« Quelle est la valeur moyenne sur trois ans des clients venus par chaque canal ? »

You get the list, ranked by probability, with the signals that drove each prediction (drop in usage frequency, unopened recent emails, unsubscribe page visits).

Understanding

"Why is the Premium segment churning faster this quarter?"

Matr analyzes, cross-references variables, returns the main factors. Not a spreadsheet. An explanation, structured, actionable.

Action

"Which at-risk customers are most likely to respond to a 15% retention offer?"

You get the sub-segment to activate first, with projected response rate. The campaign builds itself from there.

Measurement

"What was the impact of last month's campaign on actual churn for the targeted customers?"

The model returns the gap between predicted churn and observed churn, with interpretation. You know what worked. You iterate.

VOS BRIQUES MATR
Why this isn't just
another query tool.
Who can use it

Everyone

Natural language

Speed to answer

Seconds

Valeur client passée et prédite.

Data volume

Unlimited

Envoi vers le CRM et l'outil marketing.

Les questions qu'on nous pose.

  • Faut-il un data scientist ?

    Non. MatR construit et met à jour le calcul. Vous posez la question en français.

  • Valeur en chiffre d'affaires ou en marge ?

    Les deux, si vos marges sont disponibles.

  • Et pour un nouveau client sans historique ?

    MatR estime sa valeur à partir des clients qui lui ressemblent, et l'affine au fil des achats.

  • Combien de temps pour avoir les premières valeurs ?

    Quelques semaines après le cadrage, selon vos sources.