The majority of job-related websites share a common architecture, but few candidates or recruiters truly exploit the logic behind this architecture. Understanding the structure of a job site means saving time on sorting, refining searches, and spotting opportunities that default filters do not reveal.
Technical structure of a job site: reading the sitemap as a monitoring tool
An XML or HTML sitemap is not just a simple file for search engines. It is a functional map that reveals the hierarchy of content, the frequency of updates in sections, and the categories of job offers that are actually active.
We recommend consulting the sitemap even before using the internal search engine. On a site like Tous un Job, exploring the structure of the Tous un Job site allows for immediate identification of the covered sectors, targeted geographical areas, and pages for additional services (training, support, company).
A well-constructed sitemap segments URLs by content type: job listings, company pages, editorial resources, partner public services. This segmentation indicates the editorial priorities of the site and, by extension, the sectors where the volume of offers is densest.
- URLs structured as /emploi/secteur/ville/ signal an exploitable geographical network for targeted local searches.
- Pages indexed under /formation/ or /competences/ reveal whether the site offers a candidate journey beyond simple job listing consultations.
- The presence of pages /entreprise/nom/ indicates that recruiters have dedicated profiles, allowing for direct targeting of an employer.
Search filters and taxonomy: what faceted navigation does not show
Faceted navigation (filters by contract, location, salary, sector) relies on a taxonomy defined by the site. This taxonomy is never neutral. It reflects editorial choices that influence the results.
A job site that offers a “remote work” filter at the first level of navigation has chosen to prioritize this criterion. Another that relegates the type of contract to a secondary filter considers that the sector of activity takes precedence. Identifying these taxonomy choices helps understand which profiles the site aims to attract.
We frequently observe that candidates limit themselves to the displayed filters without questioning the underlying structure. By combining the reading of the sitemap with the analysis of the URL parameters generated by the filters, one can build advanced queries. For example, manually modifying the URL parameters to cross a sector and a location not offered together in the standard interface.
Exploiting URL parameters to refine a job search
When a filter generates a URL like /recherche?secteur=informatique&lieu=lyon&contrat=cdi, each parameter is modifiable. Replacing “lyon” with another city or adding a salary parameter (if the site supports it in the back-end without displaying it in the front) allows access to results that the interface does not directly offer.
This technique works on most job sites using standard frameworks. It requires checking that the server indeed returns results and not an error page, which confirms or denies the existence of the filter on the data side.
Salary transparency and job listing structure: a regulatory constraint reshaping job sites
The transposition of the European directive on pay transparency will profoundly change the structure of job sites in France. Employers will have to communicate the salary or a range before the first interview, either directly in the offer or in advance of the process.
This obligation also prohibits asking candidates for information about their current or past salary. Job titles and recruitment procedures must be designed in a non-discriminatory manner, with objective and gender-neutral salary criteria.
For job sites, this means a structural overhaul of job listings. Data fields must include a mandatory salary block. Salary search filters, previously optional on many platforms, become a component expected by candidates and by regulation.
Impact on the information architecture of job sites
Sites that anticipate this constraint are already restructuring their databases to standardize salary ranges. For candidates, a reliable salary filter becomes a quality criterion of the site itself. A job site without a relevant salary filter will lose attractiveness compared to those that display this data in a standardized manner.
Artificial intelligence and marking generated content on job sites
AI systems integrated into candidate journeys (recruitment chatbots, automated application sorting, prequalification) must now explicitly indicate that they are AI. Content generated by these tools, whether reformulated job listings or automated responses, must be marked as such.
This obligation changes the reading of a job site. Identifying content marked “generated by AI” allows for assessing the level of automation of the recruiter. A site that clearly displays these mentions demonstrates regulatory compliance, but also signals that the first selection filter is algorithmic.
- Checking for the presence of a badge or mention “content generated by AI” on job descriptions indicates the degree of human intervention in writing.
- Prequalification chatbots identified as AI allow candidates to adapt their response style (keywords, structure, conciseness).
- “Personalized” job recommendations marked AI signal a matching algorithm whose criteria deserve to be understood to optimize one’s profile.
Browsing a job site without considering these markings is akin to ignoring a crucial layer of information. The visible structure (menus, filters, pages) tells only part of the story. The invisible structure (taxonomy, URL parameters, regulatory obligations, AI marking) determines the actual quality of the candidate experience and the relevance of the results obtained.
