{"id":"https://openalex.org/W2595177306","doi":"https://doi.org/10.1145/3097983.3098123","title":"Customer Lifetime Value Prediction Using Embeddings","display_name":"Customer Lifetime Value Prediction Using Embeddings","publication_year":2017,"publication_date":"2017-08-04","ids":{"openalex":"https://openalex.org/W2595177306","doi":"https://doi.org/10.1145/3097983.3098123","mag":"2595177306"},"language":"en","primary_location":{"id":"doi:10.1145/3097983.3098123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3097983.3098123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1703.02596","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043588307","display_name":"Benjamin Paul Chamberlain","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Benjamin Paul Chamberlain","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074687185","display_name":"\u00c2ngelo Cardoso","orcid":"https://orcid.org/0000-0003-4155-3827"},"institutions":[{"id":"https://openalex.org/I4210162282","display_name":"Atos (United Kingdom)","ror":"https://ror.org/05vjgy768","country_code":"GB","type":"company","lineage":["https://openalex.org/I170138621","https://openalex.org/I4210162282"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"\u00c2ngelo Cardoso","raw_affiliation_strings":["ASOS.com, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ASOS.com, London, United Kingdom","institution_ids":["https://openalex.org/I4210162282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110479415","display_name":"Chenhe Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162282","display_name":"Atos (United Kingdom)","ror":"https://ror.org/05vjgy768","country_code":"GB","type":"company","lineage":["https://openalex.org/I170138621","https://openalex.org/I4210162282"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"C.H. Bryan Liu","raw_affiliation_strings":["ASOS.com, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ASOS.com, London, United Kingdom","institution_ids":["https://openalex.org/I4210162282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088888665","display_name":"Roberto Pagliari","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162282","display_name":"Atos (United Kingdom)","ror":"https://ror.org/05vjgy768","country_code":"GB","type":"company","lineage":["https://openalex.org/I170138621","https://openalex.org/I4210162282"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Roberto Pagliari","raw_affiliation_strings":["ASOS.com, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ASOS.com, London, United Kingdom","institution_ids":["https://openalex.org/I4210162282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001763022","display_name":"Marc Peter Deisenroth","orcid":"https://orcid.org/0000-0003-1503-680X"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Marc Peter Deisenroth","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.2112,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.9847213,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1753","last_page":"1762"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11536","display_name":"Consumer Retail Behavior Studies","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7666592597961426},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5560980439186096},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5160862803459167},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5050230622291565},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.432860404253006},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42168810963630676},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4101911187171936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39783698320388794},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36306294798851013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7666592597961426},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5560980439186096},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5160862803459167},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5050230622291565},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.432860404253006},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42168810963630676},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4101911187171936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39783698320388794},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36306294798851013},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1145/3097983.3098123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3097983.3098123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1703.02596","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1703.02596","pdf_url":"https://arxiv.org/pdf/1703.02596","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10083569","is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10083569/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In: Matwin, S and Yu, S, (eds.) Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '17).  (pp. pp. 1753-1762).  ACM (Association for Computing Machinery): New York, NY, USA. (2017)     ","raw_type":"Proceedings paper"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/48587","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/48587","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"Conference Paper"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/51137","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/51137","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Knowledge Discovery and Data Mining","raw_type":"Conference Paper"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/77478","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/77478","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Knowledge Discovery and Data Mining","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1703.02596","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1703.02596","pdf_url":"https://arxiv.org/pdf/1703.02596","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320247","display_name":"Royal Commission for the Exhibition of 1851","ror":"https://ror.org/05fdb2817"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1598033630","https://openalex.org/W1714704734","https://openalex.org/W1966202460","https://openalex.org/W2013489087","https://openalex.org/W2025348367","https://openalex.org/W2025768430","https://openalex.org/W2053186076","https://openalex.org/W2073601450","https://openalex.org/W2074694452","https://openalex.org/W2107581815","https://openalex.org/W2152424459","https://openalex.org/W2155893237","https://openalex.org/W2156957852","https://openalex.org/W2162244340","https://openalex.org/W2271840356","https://openalex.org/W2298765043","https://openalex.org/W2335930829","https://openalex.org/W2475334473","https://openalex.org/W2510174253","https://openalex.org/W2512971201","https://openalex.org/W2913668833","https://openalex.org/W2919115771","https://openalex.org/W2964341035","https://openalex.org/W3104097132","https://openalex.org/W4297683816","https://openalex.org/W4300175872","https://openalex.org/W4301213493"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W2256933480","https://openalex.org/W2027854990","https://openalex.org/W2370081953","https://openalex.org/W2364428742","https://openalex.org/W2378290951"],"abstract_inverted_index":{"We":[0,124,150],"describe":[1],"the":[2,58,68,71,78,126,142,145,162,165],"Customer":[3],"LifeTime":[4],"Value":[5],"(CLTV)":[6],"prediction":[7,18],"system":[8,51,127],"deployed":[9,128],"at":[10,52,129],"ASOS.com,":[11],"a":[12,138,152,172],"global":[13],"online":[14],"fashion":[15],"retailer.":[16],"CLTV":[17,148],"is":[19,65,137],"an":[20,26,176],"important":[21],"problem":[22],"in":[23,80,147],"e-commerce":[24],"where":[25],"accurate":[27],"estimate":[28],"of":[29,57,61,67,70,77,86,144,158,164,179],"future":[30,59],"value":[31,43,60],"allows":[32],"retailers":[33],"to":[34,48,92,141,155],"effectively":[35],"allocate":[36],"marketing":[37],"spend,":[38],"identify":[39],"and":[40,45,64,89,97,106,131,170],"nurture":[41],"high":[42],"customers":[44],"mitigate":[46],"exposure":[47],"losses.":[49],"The":[50,75],"ASOS":[53,130],"provides":[54],"daily":[55],"estimates":[56],"every":[62],"customer":[63,99],"one":[66],"cornerstones":[69],"personalised":[72],"shopping":[73],"experience.":[74],"state":[76,143],"art":[79,146],"this":[81],"domain":[82],"uses":[83],"large":[84],"numbers":[85],"handcrafted":[87,114,180],"features":[88,115,117],"ensemble":[90],"regressors":[91],"forecast":[93],"value,":[94],"predict":[95],"churn":[96],"evaluate":[98],"loyalty.":[100],"Recently,":[101],"domains":[102],"including":[103],"language,":[104],"vision":[105],"speech":[107],"have":[108],"shown":[109],"dramatic":[110],"advances":[111],"by":[112],"replacing":[113],"with":[116],"that":[118,133],"are":[119],"learned":[120],"automatically":[121],"from":[122],"data.":[123],"detail":[125],"show":[132],"learning":[134],"feature":[135],"representations":[136],"promising":[139],"extension":[140],"modelling.":[149],"propose":[151],"novel":[153],"way":[154],"generate":[156],"embeddings":[157],"customers,":[159],"which":[160],"addresses":[161],"issue":[163],"ever":[166],"changing":[167],"product":[168],"catalogue":[169],"obtain":[171],"significant":[173],"improvement":[174],"over":[175],"exhaustive":[177],"set":[178],"features.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}