SALESPERSON CLUSTERING SYSTEM AND PROGRAM
PROBLEM TO BE SOLVED: To provide a salesperson clustering system capable of generating cluster variables which eliminate arbitrariness and effectively capture characteristics of salespersons.SOLUTION: A salesperson clustering system 10 comprises: salesperson data storage means 30 for storing the amo...
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| description | PROBLEM TO BE SOLVED: To provide a salesperson clustering system capable of generating cluster variables which eliminate arbitrariness and effectively capture characteristics of salespersons.SOLUTION: A salesperson clustering system 10 comprises: salesperson data storage means 30 for storing the amount of profit of each customer for each salesperson in association with salesperson identification information and customer identification information; feature vector creating means 22 for calculating respectively the amount of profit at a plurality of quantiles in profit distribution for each salesperson using stored data on the amount of profit, and creating feature vectors for each salesperson which includes each of the calculated amount of profit as constituent elements, where the cluster variables for a vertical axis of the profit distribution is the number of customers, the cluster variables for a horizontal axis of profit distribution is the amount of the profit from one customer; and cluster analyzing means 23 for classifying the plurality of salespersons according to cluster analysis using the created feature vectors for each salesperson as input.SELECTED DRAWING: Figure 1
【課題】恣意性を排除し、かつ、営業員の特徴を効果的に捉えたクラスタ用変数を作成することができる営業員クラスタリングシステムを提供する。【解決手段】営業員毎で、かつ、顧客毎の収益金額を、営業員識別情報および顧客識別情報と関連付けて記憶する営業員データ記憶手段３０と、ここに記憶された収益金額のデータを用いて、クラスタ用変数として、縦軸を顧客数とし、横軸を１人の顧客から上げた収益金額とする営業員毎の収益分布における複数の分位点の各収益金額を求め、求めた各収益金額を構成要素とする特徴ベクトルを営業員毎に作成する特徴ベクトル作成手段２２と、作成した営業員毎の特徴ベクトルを入力としてクラスタ分析により複数の営業員を分類するクラスタ分析手段２３とを設け、営業員クラスタリングシステム１０を構成した。【選択図】図１ |
| format | Patent |
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【課題】恣意性を排除し、かつ、営業員の特徴を効果的に捉えたクラスタ用変数を作成することができる営業員クラスタリングシステムを提供する。【解決手段】営業員毎で、かつ、顧客毎の収益金額を、営業員識別情報および顧客識別情報と関連付けて記憶する営業員データ記憶手段３０と、ここに記憶された収益金額のデータを用いて、クラスタ用変数として、縦軸を顧客数とし、横軸を１人の顧客から上げた収益金額とする営業員毎の収益分布における複数の分位点の各収益金額を求め、求めた各収益金額を構成要素とする特徴ベクトルを営業員毎に作成する特徴ベクトル作成手段２２と、作成した営業員毎の特徴ベクトルを入力としてクラスタ分析により複数の営業員を分類するクラスタ分析手段２３とを設け、営業員クラスタリングシステム１０を構成した。【選択図】図１</description><language>eng ; jpn</language><subject>CALCULATING ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2018</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180426&DB=EPODOC&CC=JP&NR=2018067112A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180426&DB=EPODOC&CC=JP&NR=2018067112A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>KATO ATSUO</creatorcontrib><title>SALESPERSON CLUSTERING SYSTEM AND PROGRAM</title><description>PROBLEM TO BE SOLVED: To provide a salesperson clustering system capable of generating cluster variables which eliminate arbitrariness and effectively capture characteristics of salespersons.SOLUTION: A salesperson clustering system 10 comprises: salesperson data storage means 30 for storing the amount of profit of each customer for each salesperson in association with salesperson identification information and customer identification information; feature vector creating means 22 for calculating respectively the amount of profit at a plurality of quantiles in profit distribution for each salesperson using stored data on the amount of profit, and creating feature vectors for each salesperson which includes each of the calculated amount of profit as constituent elements, where the cluster variables for a vertical axis of the profit distribution is the number of customers, the cluster variables for a horizontal axis of profit distribution is the amount of the profit from one customer; and cluster analyzing means 23 for classifying the plurality of salespersons according to cluster analysis using the created feature vectors for each salesperson as input.SELECTED DRAWING: Figure 1
【課題】恣意性を排除し、かつ、営業員の特徴を効果的に捉えたクラスタ用変数を作成することができる営業員クラスタリングシステムを提供する。【解決手段】営業員毎で、かつ、顧客毎の収益金額を、営業員識別情報および顧客識別情報と関連付けて記憶する営業員データ記憶手段３０と、ここに記憶された収益金額のデータを用いて、クラスタ用変数として、縦軸を顧客数とし、横軸を１人の顧客から上げた収益金額とする営業員毎の収益分布における複数の分位点の各収益金額を求め、求めた各収益金額を構成要素とする特徴ベクトルを営業員毎に作成する特徴ベクトル作成手段２２と、作成した営業員毎の特徴ベクトルを入力としてクラスタ分析により複数の営業員を分類するクラスタ分析手段２３とを設け、営業員クラスタリングシステム１０を構成した。【選択図】図１</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2018</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZNAMdvRxDQ5wDQr291Nw9gkNDnEN8vRzVwiOBLJ8FRz9XBQCgvzdgxx9eRhY0xJzilN5oTQ3g5Kba4izh25qQX58anFBYnJqXmpJvFeAkYGhhYGZuaGhkaMxUYoAm2AlGw</recordid><startdate>20180426</startdate><enddate>20180426</enddate><creator>KATO ATSUO</creator><scope>EVB</scope></search><sort><creationdate>20180426</creationdate><title>SALESPERSON CLUSTERING SYSTEM AND PROGRAM</title><author>KATO ATSUO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_JP2018067112A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; jpn</language><creationdate>2018</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>KATO ATSUO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>KATO ATSUO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>SALESPERSON CLUSTERING SYSTEM AND PROGRAM</title><date>2018-04-26</date><risdate>2018</risdate><abstract>PROBLEM TO BE SOLVED: To provide a salesperson clustering system capable of generating cluster variables which eliminate arbitrariness and effectively capture characteristics of salespersons.SOLUTION: A salesperson clustering system 10 comprises: salesperson data storage means 30 for storing the amount of profit of each customer for each salesperson in association with salesperson identification information and customer identification information; feature vector creating means 22 for calculating respectively the amount of profit at a plurality of quantiles in profit distribution for each salesperson using stored data on the amount of profit, and creating feature vectors for each salesperson which includes each of the calculated amount of profit as constituent elements, where the cluster variables for a vertical axis of the profit distribution is the number of customers, the cluster variables for a horizontal axis of profit distribution is the amount of the profit from one customer; and cluster analyzing means 23 for classifying the plurality of salespersons according to cluster analysis using the created feature vectors for each salesperson as input.SELECTED DRAWING: Figure 1
【課題】恣意性を排除し、かつ、営業員の特徴を効果的に捉えたクラスタ用変数を作成することができる営業員クラスタリングシステムを提供する。【解決手段】営業員毎で、かつ、顧客毎の収益金額を、営業員識別情報および顧客識別情報と関連付けて記憶する営業員データ記憶手段３０と、ここに記憶された収益金額のデータを用いて、クラスタ用変数として、縦軸を顧客数とし、横軸を１人の顧客から上げた収益金額とする営業員毎の収益分布における複数の分位点の各収益金額を求め、求めた各収益金額を構成要素とする特徴ベクトルを営業員毎に作成する特徴ベクトル作成手段２２と、作成した営業員毎の特徴ベクトルを入力としてクラスタ分析により複数の営業員を分類するクラスタ分析手段２３とを設け、営業員クラスタリングシステム１０を構成した。【選択図】図１</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | SALESPERSON CLUSTERING SYSTEM AND PROGRAM |
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