Purpose:　This　paper　investigates　the　semantic　association　mechanisms　of　weak　demand　signals　that　facilitate　innovative　product　development　in　terms　of　conceptual　and　temporal　precedence,　despite　their　inherent　ambiguity　and　uncertainty.　Design/methodology/approach:　To　address　this　challenge,　a　domain　ontology　approach　is　proposed　to　construct　a　customer　demand　scenario-based　framework　that　eliminates　the　blind　spots　in　weak　demand　signal　identification.　The　framework　provides　a　basis　for　identifying　such　signals　and　introduces　evaluation　indices,　such　as　depth,　novelty　and　association,　which　are　integrated　to　propose　a　three-dimensional　weak　signal　recognition　model　based　on　domain　ontology　that　outperforms　existing　research.　Findings:　Empirical　analysis　is　carried　out　based　on　customer　comments　of　new　energy　vehicles　on　car　platform　such　as　“Auto　Home”　and　“Bitauto”.　Results　demonstrate　that　in　terms　of　recognition　quantity,　the　three-dimensional　weak　demand　signal　recognition　model,　based　on　domain　ontology,　can　accurately　identify　six　demand　weak　signals.　Conversely,　the　keyword　analysis　method　exhibits　a　recognition　quantity　of　four　weak　signals;　in　terms　of　recognition　quality,　the　three-dimensional　weak　demand　signal　recognition　model　based　on　domain　ontology　can　exclude　non-demand　signals　such　as　“charging　technology”,　while　keyword　analysis　methods　cannot.　Overall,　the　model　proposed　in　this　paper　has　higher　sensitivity.　Originality/value:　This　paper　proposes　a　novel　method　for　identifying　weak　demand　signals　that　considers　the　frequency　of　the　signal＇s　novelty,　depth　and　relevance　to　the　target　demand.　To　verify　its　effectiveness,　customer　review　data　for　new　energy　vehicles　is　used.　The　results　provide　a　theoretical　reference　for　formulating　government　policies　and　identifying　weak　demand　signals　for　businesses.　©　2023,　Emerald　Publishing　Limited.