{"id":"W4383533106","doi":"10.1002/mar.21866","title":"Does (customer data) size matter? Generating valuable customer insights with less customer relationship risk","year":2023,"lang":"en","type":"article","venue":"Psychology and Marketing","topic":"Consumer Behavior in Brand Consumption and Identification","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"British Academy","keywords":"Customer intelligence; Customer to customer; Customer retention; Customer advocacy; Loyalty business model; Voice of the customer; Customer equity; Business; Computer science; Marketing; Customer relationship management; Service quality; Service (business)","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":[0.02163221,0.0003728509,0.0004637833,0.0010824,0.0006694726,0.005279568,0.0008934934,0.001035504,0.005228045],"category_scores_gemma":[0.1948066,0.0002695403,0.0005077227,0.00146191,0.001508747,0.008081978,0.001844032,0.001425152,0.0007874941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008728166,"about_ca_system_score_gemma":0.0009367597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256392,"about_ca_topic_score_gemma":0.001404317,"domain_scores_codex":[0.9820393,0.01116506,0.001015745,0.001319133,0.003916512,0.0005442332],"domain_scores_gemma":[0.5789634,0.3698347,0.02089773,0.01529331,0.01104518,0.003965609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00262313,0.001208414,0.7251765,0.0005845713,0.0006105604,0.0002760665,0.002919,0.006390078,0.003895763,0.00866307,0.004903255,0.2427496],"study_design_scores_gemma":[0.0003757258,0.003524086,0.8354732,0.0007252927,0.00118726,0.001228534,0.009759201,0.07192961,0.01394026,0.04457173,0.01702731,0.0002576984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9632524,0.0008038727,0.01109794,0.008001044,0.0001079005,0.0002614631,0.0004999405,0.0001559855,0.01581937],"genre_scores_gemma":[0.9965718,0.0001279928,0.002402586,0.0003805486,0.00005151119,0.00003760188,0.0001033323,0.0000218886,0.0003028073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02163221,"threshold_uncertainty_score":0.1144034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05466477901955536,"score_gpt":0.3033289501992356,"score_spread":0.2486641711796803,"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."}}