The selection of professional hair care products has long rested on two pillars: the hairdresser’s experience and the commercial relationship with the brand representative. The introduction of artificial intelligence into this process is structurally modifying both. Hairswiss analyzes what this change concretely implies for Swiss professionals, and how ingredient chemistry is becoming an increasingly central selection criterion in algorithmic recommendation systems.
How Does an AI System Select a Hair Care Product?
A recommendation engine applied to professional hair care products does not work on aesthetic preferences: it cross-references objective parameters. The key variables include INCI composition (presence and concentration of actives), declared cosmetic function (conditioner, surfactant, film-forming agent), compatibility with a defined hair type (porosity, chemical state, diameter), and the professional’s purchase history.
This type of processing requires that product data be structured at a high level of chemical granularity. A product whose INCI list is not correctly indexed — or whose active ingredients are not qualified by molecular function — will be systematically less visible in an AI-assisted catalog. This represents a significant shift from traditional distribution, where brand notoriety and commercial relationships outweighed composition.
The Three Questions AI Asks That Representatives Did Not
1. What is the functional concentration of the active? A shampoo labeled “with keratin” may contain between 0.1% and 5% hydrolyzed proteins depending on its price positioning. A recommendation system that cross-references INCI data with clinical results can theoretically discriminate these dosage levels where a sales conversation would not.
2. Are there chemical incompatibilities with other products in use? Combining an alkaline-pH shampoo with a cationic tannin-based treatment can be counterproductive. An algorithm trained on formulation data can flag these incompatibilities; a static catalog does not.
3. Does the formulation match the service protocol offered? A salon specializing in keratin smoothing treatments has different requirements for film-forming agents and chelating agents (EDTA, citric acid) than a color-focused salon. Protocol-based segmentation is difficult to achieve manually at scale, but accessible to a correctly parameterized AI system.
The Phenomenon in Switzerland: Professional Distribution and B2B Platforms
In Switzerland, this movement takes on a particular dimension in a highly linguistically segmented market where access to professional ranges has long been conditioned by exclusive distribution circuits. B2B platforms such as cliCHair.ch introduce an algorithmically assisted catalog approach that allows professionals to access product recommendations cross-referenced by hair type and INCI composition, independently of traditional distribution channels.
What Hairswiss observes in this phenomenon is not a change of brand or supplier, but a transformation of the decision criterion: from relational trust toward formulatory transparency. For professionals trained in reading INCI lists and the mechanisms of action of actives, this shift represents a direct competitive advantage.