{"id":"W7125172545","doi":"10.62517/jnme.202510405","title":"Market Segmentation and Tag Optimization in Customer Behavior Data Analysis: Current Status and Future Research Directions","year":2025,"lang":"","type":"article","venue":"Journal of new media and economics.","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Market segmentation; Key (lock); Segmentation; Market research; Consumer behaviour; Face (sociological concept); Current (fluid)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01296528,0.0009739654,0.001849545,0.003038173,0.0006442589,0.004719543,0.002532102,0.002539724,0.002461037],"category_scores_gemma":[0.01234303,0.0007009974,0.001259145,0.005684088,0.00262526,0.01057972,0.001438011,0.002193149,0.001115324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001425559,"about_ca_system_score_gemma":0.002531402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004932665,"about_ca_topic_score_gemma":0.003448068,"domain_scores_codex":[0.9964246,0.001614853,0.0002035996,0.0007965517,0.0007752753,0.0001850201],"domain_scores_gemma":[0.9718807,0.02305951,0.001014238,0.0008088233,0.002933033,0.0003036063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001182504,0.0003172137,0.005060135,0.002015048,0.000102916,0.00002734763,0.0003855706,0.01319717,0.0007529312,0.02911361,0.004173392,0.9447365],"study_design_scores_gemma":[0.0001146408,0.001043768,0.01711436,0.004963959,0.0004586323,0.0003908647,0.00660072,0.5140499,0.0062825,0.258117,0.1903676,0.0004959854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03532481,0.5770205,0.3508978,0.02282509,0.0006487457,0.0001703189,0.0002653783,0.001079871,0.01176753],"genre_scores_gemma":[0.2782676,0.3556727,0.3550347,0.003034901,0.003466716,0.0003032544,0.000700387,0.0003072566,0.003212512],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01296528,"threshold_uncertainty_score":0.06856775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06352882524906278,"score_gpt":0.3382986378740011,"score_spread":0.2747698126249383,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}