The online job search relies on a mechanism that is often misunderstood: before a recruiter reads your application, an automatic sorting software (ATS, or Applicant Tracking System) has already analyzed it. Understanding this filter and then adapting each step of your approach accordingly can radically change the response rate to submitted applications.
ATS Filtering and Keywords: What Blocks Applications Before Reading
An ATS scans the content of your resume to identify specific terms from the job description. If these terms are missing, the document is ranked at the bottom of the pile, sometimes without any human ever opening it.
The reflex to adopt: reread each targeted job offer and identify the skills, tools, and job titles that recur. Integrate them into your resume, not as a block, but within the description of your experiences. A section title like “Agile Project Management” carries more weight than a line lost in a “Miscellaneous” section.
Two common mistakes disable automatic detection. The first: using a complex graphic format (multiple columns, icons, nested text boxes) that the software cannot read. The second: writing a unique resume sent as-is to all job offers. Each targeted application deserves a vocabulary adjustment, including job synonyms that the recruiter uses in their ad.
Those looking to find a job on Job and Co have access to offers categorized by sector, making it easier to spot recurring terms in a specific field before adapting their resume.
Generative AI and Applications: Real Utility and Limits to Know
The use of generative artificial intelligence for job applications is progressing rapidly. According to a study by Apec published in May 2026, 31% of executives used generative AI to apply in 2025, up from 15% in 2024. This acceleration changes the game for both candidates and recruiters.
AI concretely assists with three repetitive tasks:
- Rephrasing work experiences to align with the vocabulary of a job offer, which improves passing ATS filters
- Generating a first draft of a cover letter based on the job description, which the candidate then personalizes
- Preparing for an interview by simulating questions related to the targeted position and industry
The trap is documented: according to the same source, the majority of recruiters find AI-generated cover letters too similar to differentiate profiles. Copy-pasting a text produced by ChatGPT without rewriting it amounts to sending a letter identical to that of dozens of other candidates. The tool serves as a draft, not a finished product.
Maintaining a Personal Voice Despite Automation
After using a prompt to structure your letter, read it aloud. Replace generic phrases with details that only your background can provide: a measurable result, a unique mission context, the name of a mastered tool. It is this layer of specificity that distinguishes your application from a pile of formatted applications.
LinkedIn Profile and Job Search: Important Settings
LinkedIn remains the dominant professional network in France for online job searching. The profile functions as a public and indexable resume, but several technical settings go unnoticed.
The first is the “Open to Work” setting visible only to recruiters. This option signals your availability to companies using LinkedIn Recruiter, without alerting your current employer. It can be found in the profile privacy settings, under “Job Search Preferences.”
The second lever concerns the summary (the “Info” section). Recruiters skim it. Two to three sentences are enough to state your profession, an area of expertise, and the type of position sought. Every word counts: the terms used here feed the profile suggestion algorithm.
Regular Activity and Algorithmic Visibility
Publishing or commenting on content related to your field increases the frequency with which your profile appears in recruiters’ search results. A well-reasoned comment on a job-related post is worth more than a simple “like.” The LinkedIn algorithm favors active profiles in suggestions, including for sponsored job offers.
Tracking Online Applications: A Method to Avoid Empty Follow-ups
Sending dozens of applications without tracking their status generates two problems: poorly targeted follow-ups and a loss of motivation due to a lack of benchmarks. A tracking table, even a rudimentary one, corrects both.
Three columns are sufficient: the date sent, the company and position, the status (sent, followed up, interview, rejected). This tracking allows you to identify offers that have gone unanswered after ten business days, a reasonable timeframe before a follow-up via email or LinkedIn.
- Follow up with a new element: a company update, a complementary skill, a confirmed availability
- Limit yourself to one follow-up per application, unless the recruiter has explicitly opened the dialogue
- Note the channel used (email, LinkedIn messaging, form) to avoid awkward duplicates
A structured follow-up reduces the number of applications needed by concentrating effort on active leads rather than mass sending.
The volume of applications sent does not predict the outcome. What makes the difference is the alignment between the vocabulary of your application and that of the offer, the visible personalization of each submission, and the regularity of the follow-up. Three well-adjusted applications per week yield more responses than thirty identical resumes scattered across all job boards.
