Choosing your program with real MonMaster and InserSup data

Choosing a master’s or a post-secondary program is often based on fuzzy criteria: a school’s reputation, an opinion found on a forum, the number of likes on a video. Yet public data exists, produced by the Ministry of Higher Education, that answers two far more useful questions: how many people applied to this specific program last year, and what became of its graduates. Here’s how to read it without scaring yourself or reassuring yourself wrongly.

MonMaster: what the dataset actually measures

The MonMaster dataset, published by the SIES (the statistical service of the Ministry of Higher Education), documents every program open to applications on the MonMaster platform (France’s national platform for master’s admissions): available places, the volume of applications received in the main and supplementary phases, and applicant profiles (all applicants, those who are ranked, those who are called, and those who ultimately accept an offer).

To give you a sense of scale: for the 2025 admissions cycle, the dataset covers 8,167 programs, 258,289 candidates who confirmed at least one application, and more than 2.6 million applications filed in the main phase. These figures show one essential thing: on average, an applicant applies to several dozen programs, which completely changes how you should read a raw applications-to-places ratio.

The trap to avoid: if a program shows “800 applications for 30 places,” that doesn’t mean an applicant has 30 chances out of 800 of getting in. Many of those 800 applications are “safety net” wishes filed by people who, if called, won’t accept the offer because they prefer a program elsewhere. That’s exactly why the dataset distinguishes ranked candidates, called candidates, and those who actually accept: this last figure — the conversion rate between being called and accepting — gives a much more accurate picture of a program’s real pressure than the simple applications-to-places ratio.

InserSup: what happens to graduates

InserSup is the ministry’s program for measuring the employment outcomes of higher-education graduates, by cross-referencing student administrative records with an extract of nominative social declarations (DSN, employer-reported wage and employment data) supplied by Dares and Insee, France’s labor statistics agencies. Unlike a survey-based approach where graduates respond (or don’t) to a questionnaire, InserSup relies on actual employment data.

The data covers professional bachelor’s degrees (licences professionnelles), master’s degrees, BUT degrees (a three-year technological bachelor’s), engineering degrees, and equivalent five-year-level programs, at universities, engineering schools, and business schools. It measures, at 6, 12, 18, 24, and 30 months after graduation:

• the rate of salaried and self-employed work in France;
• the type of contracts obtained (permanent, fixed-term, etc.);
• the distribution of net monthly full-time-equivalent salaries.

These indicators exist at several levels: for a specific degree at a given institution, for a type of degree across all institutions, and at the national level — which lets you compare a given master’s at a given university to the national average for the same field.

How to read these two datasets together, without scaring yourself

A single figure rarely tells you much on its own; it’s the comparisons that matter:

1. Compare a program’s pressure to similar programs, not to an abstract national average. A highly sought-after science master’s in a big city will mechanically get more applications than an equivalent master’s in a mid-sized town — that doesn’t mean the second one is worse.
2. Look at the employment rate at 18 or 30 months rather than at 6 months if you want a stable picture: some graduates take longer to find a position matching their training, especially in fields where entry into the job market is gradual.
3. A rejected application to a highly competitive program doesn’t measure your worth. A high applications ratio often reflects a city’s appeal, cost of living, or reputation, not solely the program’s academic quality.
4. Neither MonMaster nor InserSup predicts your own path. These datasets describe past cohorts or previous admission cycles: they give you a realistic order of magnitude, never an individual guarantee of admission or employment. A program with an excellent 18-month employment rate doesn’t mean that you, personally, will find a job within that time frame.

A practical use

Before finalizing your choices, it’s more useful to compare 3 to 5 similar programs on both angles at once — entry-level pressure (MonMaster) and actual outcomes (InserSup) — than to rely on a single indicator. A lesser-known program with a solid, stable 18-month employment rate can be a stronger choice than a highly sought-after program whose actual outcomes are more uncertain.

Key takeaways

• MonMaster (SIES, Ministry of Higher Education) gives, per program, the number of places, applications, and the profile of ranked, called, and accepting candidates.
• A raw applications-to-places ratio overstates the real difficulty: many applications are safety-net wishes that never turn into an acceptance.
• InserSup measures graduates’ actual employment (via DSN records, not a survey) at 6, 12, 18, 24, and 30 months, by degree and by institution.
• This data describes past cohorts: it informs a choice, it doesn’t guarantee an individual admission or job.
• Always compare several similar programs against each other rather than a single figure against a national average.

To check these official figures directly, program by program, without digging through the ministry’s raw files, the orientation connector queries these datasets live.