En Voiture Simone
Online driving school
How En Voiture Simone arbitrates its media mix on contribution
A Marketing Mix Model that integrates paid channels, organic channels, and market context to estimate what actually contributes to license sales — and to redeploy budget when the environment shifts.
of continuous modeling
of the mix integrated, paid and organic
exogenous factors modeled
Model reading
Base & brand — 34% of modeled contribution to license sales
Illustrative split. Modeled contribution, all channels combined.
Large budgets, an app, and a market that moves on its own
En Voiture Simone sells driving licenses online, with a mobile app that captures signups and delivers the theory test. Acquisition runs across every paid channel, with substantial budgets. But when it comes to arbitrating, two unknowns resist classic reporting: the app's real share of license sales, and the effect of regulatory shocks on demand.
App
Signups, theory test
Web
License sales, content
The app blurs attribution
Signups land on the app, licenses also sell through the web. Last click cannot say which journey actually sells.
A series of exogenous shocks
CPF reform, paid activation, examiner shortage: demand moves for reasons that have nothing to do with marketing.
A rare skill to keep in-house
Contribution modeling requires sharp statistical expertise, hard to justify internally for a periodic need.
A contribution model, not an oracle
Every channel, one model
The MMM integrates paid channels, organic channels, and exogenous factors to estimate each lever's contribution to license sales.
DecisionApp vs web, finally settled
The model separates what the app actually brings to sales from what flows through the web — the question no reporting could answer.
AttributionA regularly refreshed model
The market changes, so does the model: refreshed regularly over two years, it checks after every shock whether the mix still holds.
SteeringContribution, not last click
The MMM estimates each lever's share of sales, including what last click never sees: brand, organic, the app. It then serves to test reallocation scenarios before committing budget.
Illustrative split of the modeled contribution to license sales. The model's actual values remain confidential.
Exogenous factors integrated
The model isolates what belongs to marketing from what belongs to context. When regulation or exam supply shifts, the reading of the mix stays true.
Two years of modeling, continuously
of continuous MMM
A living model, refreshed regularly — not a one-off study
of the mix modeled
Paid channels, organic channels, and brand base
finally comparable
Each journey's contribution to license sales
exogenous factors integrated
CPF, examiners, seasonality, economic context
Scope and usage indicators: they describe what the model covers and makes possible. The model's quantified outputs remain confidential.
Reallocating without betting
Over two years, the model served as a decision aid: recutting investment, redirecting part of the budgets toward the channels estimated most profitable, and running successive experiments to validate every move.
Above all, it settled questions classic reporting left open: the app's share of license sales, and the mix's resilience to exogenous shocks — CPF reform, examiner shortage. What these factors changed in demand was no longer a matter of opinion, but a variable in the model.
The model is refreshed regularly: every market shift becomes a mix update, not a crisis.
What En Voiture Simone says
A review left on Trustfolio, a verified B2B review platform, by Maxime Morelli, CMO of En Voiture Simone, for the paid missions run by the Spark team, which designs and publishes Nanga.
« Spark participe pleinement à la croissance de notre activité et de notre acquisition de clients. »
Maxime Morelli
CMO, En Voiture Simone
Review left on November 5, 2020
Review collected and authenticated by Trustfolio, originally in French, covering online performance campaigns. This mission is distinct from the Marketing Mix Modeling presented on this page.