JP3794895B2 - Sales support system and sales support method - Google Patents

Description

【００６７】
（商品ＤＢ２０１の内容）
この商品ＤＢ２０１においては、上記カテゴリ項目は、その商品がどのカテゴリの顧客を対象にしたものかを示したものである（ただし、ドントケアは商品ＤＢ２０１のカテゴリには含まれない）。
【００６８】
この商品ＤＢ２０１の内容としては、以下のようなものがある。
【００６９】
１．商品基礎情報
この商品基礎情報には、商品コード、商品名称、登録日、カテゴリ等が含まれている。
【００７０】
２．価格情報
この価格情報には、仕入れ価格、通常販売価格、値引き販売価格、損益分岐販売価格等が含まれている。
【００７１】
３．販売履歴情報
この販売履歴情報には、今までの販売履歴情報等が含まれている。
【００７２】
４．売り方情報
この売り方情報には、売価タイプ情報（正価販売専用、正価販売後値引き可、値引き販売専用）、展示方法情報（高級感ある展示、通常展示、ワゴン展示、他商品に付随して展示）、接客情報（説明販売対象、説明不要、他商品も勧める等）等が含まれている。
【００７３】
（顧客ＤＢ２０２の内容）
この顧客ＤＢ２０２においては、顧客を所定の区分に分類したものである。
【００７４】
顧客ＤＢ２０２の内容としては、各顧客毎に以下の４つの大分類で情報を持っている。
【００７５】
１．顧客基礎情報
この顧客基礎情報には、顧客コード、氏名、年齢、カテゴリ、住所、電話番号、職業、購読雑誌、購読新聞等の属人情報等が含まれている。
【００７６】
２．購買履歴情報
この購買履歴情報には、今までの購買履歴情報等が含まれている。
【００７７】
３．アプローチ情報
このアプローチ情報には、顧客自身の希望、基礎情報、購買履歴を参酌して決定される、各顧客に適したアプローチ方法情報（ダイレクトメール、雑誌広告、新聞チラシ、駅貼りポスター、電子メール等）等が含まれている。
【００７８】
４．クレーム情報
このクレーム情報には、各顧客より寄せられた意見・クレーム及びその顛末の情報等が含まれている。
【００７９】
（商品層別ＤＢ２０３の内容）
商品層別ＤＢ２０３の内容としては、商品を所定の基準で層別した結果を保持している。
【００８０】
この層別の内容を以下の表２に基づいて説明する。
【００８１】
なお、ここでは、販売履歴又は商品の属性で層別している。
【００８２】
【表２】

【００８３】
すなわち、表２の基準で層別した結果は、その層別項目として１．販売額累計（商品の過去１年の販売額累計で層別・累計が（５００万円以上、５００〜５０万円、５０万円以下）、２．粗利額累計（商品の過去１年の粗利額累計で層別・累計が（２００万円以上、２００〜３０万円、３０万円以下））、３．商品グレード（商品のグレードで層別・グレードは（高級、通常、普及品））、４．値引き率（商品の値引き可能性で層別・販売価格は（定価、３割まで値引き可、３割以上値引き可））、５．販売額変動（通年商品のみ）（販売額が過去３週でどのように変動しているか・販売額が（増加、ほぼ一定、減少））、６．適時度（季節品のみ）（季節商品が、旬の商品か・季節商品が（旬、旬の前後、季節外れ））、７．新商品度（発売開始からの期間・発売開始から（１ケ月以内、１〜６ケ月、６ケ月以上））、８．ブランド力度（ブランド力で層別・ブランド力が（強い、中程度、弱い））等が含まれている。
【００８４】
ここで、層別に際しては、各基準で分類できるだけのデータをもつ商品のみを層別対象にしている。
【００８５】
もちろん、一つの商品を複数の基準で重複して層別してよいものとする。
【００８６】
ここでは、層別は３つとし、その内容は表２において括弧の中に記載されているようなものである。
【００８７】
そして、各層は括弧の左よりＡ，Ｂ，Ｃの記号で指し示される。
【００８８】
例えば、「商品グレードか高級」の層を指し占めす記号は、「商品グレード」の項目番号が３であり、「高級」の層がＡに該当するので「３Ａ」で指し示される。
【００８９】
実際の商品層別ＤＢ２０３のフォーマットは、以下の表３に示されるようになっている。
【００９０】
【表３】

【００９１】
すなわち、これらの層別結果のフォーマット例としては、表３に示されているように、商品コード１０００１、１０００２、１０００３、１０００４について、それぞれ１〜８欄にわけてＡＡＡＢＢＣＡ（ただし、６欄はブランク）、ＣＢＡＡＡＡＢＡ、ＡＣＣＣＡＣＣＣ、ＢＢＢＢＢＢＢ（ただし、６欄はブランク）のようになされる。
【００９２】
ここで、該当しない場合や、データが不足して分類不能のところはブランクである。
【００９３】
そして、この表３に示されているフォーマット例では、例えば、商品コード１０００１の場合、３欄がＡなので、層別項目の番号３の「商品グレード」において、層別がＡの「高級」に該当することが判る。
【００９４】
（顧客層別ＤＢ２０４）
顧客層別ＤＢ２０４の内容は、顧客を所定の基準で層別した結果を保持している。
【００９５】
この層別の内容を以下の表４に基づいて説明する。
【００９６】
なお、ここでは、購買履歴を用いて層別している。
【００９７】
【表４】

【００９８】
すなわち、表４の基準で層別した結果は、その層別項目として１．ブランド忠実度（ブランドに対する忠実度に従い層別・忠実度が（大、中、小））、２．季節品購入時期（季節商品を購入する時期で層別・購入時期が季節品販売期間の（始め、中、後半））、３．新商品購入時期（新商品購入する時期で層別・発表の（直後、半年以内、それ以降））、４．購入価格（商品を購入する時の価格で層別・購入価格が（定価、３割以内値引き、３割以上値引き））、５．商品グレード（購入商品のグレードで層別・商品グレードが（高級、通常、普及品））、６．購入頻度（購入頻度で層別・購入頻度が年（５回以上、１〜４回、１回以下））、７．購入額（購入額で層別・購入額が年（７万円以上、７〜３万円、３万以下））、８．顧客度変化（購入額の変化で層別・購入額が（増加、不変、減少））、９．セール反応度（セールでの購買割合で層別・セールでの購買額が（５割以上、５〜３割、３割以下））等が含まれている。
【００９９】
ここで、層別に際しては各基準で分類できるだけのデータをもつ顧客のみを層別対象にしている。
【０１００】
もちろん、一つの顧客を複数の基準で重複して層別してよいものとする。
【０１０１】
層別は３つとし、その内容は表４において括弧の中に記載されている。
【０１０２】
そして、各層は括弧の左よりＡ，Ｂ，Ｃの記号で指し示される。
【０１０３】
実際の顧客層別ＤＢ２０４のフォーマットは、以下の表５に示されるようになっている。
【０１０４】
【表５】

【０１０５】
すなわち、これらの層別結果のフォーマット例としては、表５に示されているように、顧客コードＡ０００１、Ａ０００２、Ａ０００３、Ａ０００４について、それぞれ１〜９欄にわけてＣＡＡＡＡＡＡＢＣ、ＣＣＣＣＣＢＣＢＡ、ＡＡＢＢＢＣ（ただし、７〜９欄はブランク）、ＢＢＣＡＡＡＡＣＢのようになされている。
【０１０６】
ここで、該当しない場合や、データが不足して分類不能のところはブランクである。
【０１０７】
そして、この表５に示されているフォーマット例では、例えば、顧客コードＡ０００１の場合、３欄がＡなので、層別項目の番号３の「新商品購入時期」において、層別がＡの発表の「直後」に該当することが判る。
【０１０８】
（知識ベース）
以下の表６に知識ベース２０５の内容例を示す。
【０１０９】
すなわち、知識ベース２０５の例としては、以下の表６の基準で販売目的に対して抽出した結果を保持している。
【０１１０】
【表６】

【０１１１】
すなわち、表６の基準で抽出した結果は、販売目的に対する商品層別ＤＢの抽出条件と顧客層別ＤＢ抽出条件との欄にわけて、それぞれ、１．売上げ確保１Ａ＋１Ｂ＋３Ｃ＋６Ａ、６Ａ＋７Ａ、２．利益確保２Ａ＋３Ａ＋４Ａ、４Ａ＋５Ａ、３．季節遅れ在庫処分６Ｃ、２Ｃ、４．新商品販売促進７Ａ＋７Ｂ、３Ａ＋３Ｂ、５．ブランド販売促進８Ａ、１Ａ＋１Ｂ等が含まれている。
【０１１２】
例えば、表６において、「利益確保」の販売目的においては、商品は「粗利累計が２００万円以上（２Ａ）、又は、商品グレードが高級（３Ａ）、又は、販売価格が定価（４Ａ）」の条件で抽出され、顧客は「購入価格が定価（４Ａ）、又は、購入商品のグレードが高級（３Ａ）」で抽出される。
【０１１３】
この場合、知識ベースの抽出条件は、一応デフォルトで入っているが、その場で所望の設定に更新することができるようになつている。
【０１１４】
次に、以上のように構成される販売支援システムの処理フローの詳細を説明する前に、本販売支援システムによる処理の流れの各フェーズの概略について説明する。
【０１１５】
１．目的決定フェーズ
店長が、「販売履歴出力プログラム」を利用して過去の販売履歴に基づき、各ＭＤ週毎に販売目的を決定する。
【０１１６】
販売目的はリストに示される複数の候補より、抽出するようにしてある。
【０１１７】
ここで、ＭＤ週とは、年間を５２週に区切ったものである。
【０１１８】
２．販促商品および顧客抽出フェーズ
上記販売目的に合致した商品が、知識ベースのルールに従って、商品層別ＤＢ２０３より抽出される。
【０１１９】
この商品層別ＤＢ２０３より抽出される結果については、手作業で修正可能である。
【０１２０】
上記販売目的に合致した顧客が、知識ベースのルールに従って、顧客層別ＤＢ２０４より抽出される。
【０１２１】
この顧客層別ＤＢ２０４より抽出される結果については、手作業で修正可能である。
【０１２２】
３．整合フェーズ
カテゴリ情報をもちいて、上記抽出された商品と顧客間のミスマッチ部分が削除される。
【０１２３】
上記ミスマッチ部分が削除された商品と顧客については、再度手作業で修正可能である。
【０１２４】
４．販売方法決定フェーズ
上記のようにして決定された顧客に対して、顧客ＤＢ２０２のアプローチ情報より、対象顧客に対するアプローチ方法が検索される。
【０１２５】
また、上記のようにして決定された商品に対して、商品ＤＢ２０１の売り方情報より、対象商品の売り方が決定される。
【０１２６】
上記顧客ＤＢ２０２のアプローチ方法と、商品ＤＢ２０１の売り方とは、それぞれ、手作業で修正可能である。
【０１２７】
以上１．〜４．のフェーズを経ることにより、販売目的に沿って、「顧客」と「商品（品揃え）」と「売り方」が決定される。
【０１２８】
次に、以上のように構成される販売支援システムの処理手順の詳細について説明する。
【０１２９】
まず、ＰＣ端末１０２で「販売履歴出力プログラム」を起動し、過去の販売履歴を検討する。
【０１３０】
次に、「販売戦術策定支援プログラム」を起動し、所望の販売戦術の策定作業に移る。
【０１３１】
以下、図３に示すフローチャートを参照して説明する。
【０１３２】
目標決定フェーズにおいては、まず、販売目的設定ウィンドウで複数の販売目的候補を含むリストを呈示する（ステップＳ１）。
【０１３３】
この販売目的のリストとしては、例えば「売上げ確保」、「利益確保」、「季節遅れ在庫処分」、「新商品販売促進」、「ブランド販売促進」等がある。
【０１３４】
この中から、操作者（主に店長）は過去の販売履歴に鑑みて、適切な販売目的を選択して入力し、販売支援システムはこの入力に基づいて販売目的を設定する（ステップＳ２）。
【０１３５】
この販売目的を入力する作業はＭＤ週単位に行われ、必要な数のＭＤ週について販売目的が設定される。
【０１３６】
次に、操作者は各ＭＤ週における販売目標（販売量又は販売金額）を適宜入力し、販売支援システムはこの入力された販売目標（販売量又は販売金額）を保持する（ステップＳ３）。
【０１３７】
以上で、目標決定フェーズが終了する。
【０１３８】
次に、商品及び顧客抽出フェーズでは、まず、上記ステップＳ２で設定された販売目的に対応する商品を抽出する。
【０１３９】
この商品抽出は、知識ベース２０５に格納された販売目的と商品層別ＤＢ抽出条件の一覧より、上記入力された販売目的に対応する商品層別ＤＢ２０３の抽出条件を得て、この抽出条件で商品層別ＤＢ２０３を検索して、条件に合致する商品を抽出することにより行う（ステップＳ４）。
【０１４０】
このとき、上記ステップＳ３で入力された販売目標が参酌され、販売目標が低い場合には、知識ベース２０５の抽出条件式でＯＲ（＋）で結ばれた各のうち、複数の条件を満足する商品のみ抽出するようにして絞り込みをしている。
【０１４１】
この抽出した商品一覧を表示し、操作者による手入力による修正を受け入れる（ステップＳ５）。
【０１４２】
次に、上記ステップＳ２で入力された販売目的に対応する顧客を抽出する。
【０１４３】
この顧客抽出は、知識ベース２０５に格納された販売目的と顧客層別ＤＢ抽出条件の一覧より、上記設定された販売目的に対応する顧客層別ＤＢ２０４の抽出条件を得て、この抽出条件で顧客層別ＤＢ２０４を検索して、条件に合致する顧客を抽出することにより行う（ステップＳ６）。
【０１４４】
このとき、上記ステップＳ３で入力された販売目標が参酌され、販売目標が低い場合には、知識ベース２０５の抽出条件式でＯＲ（＋）で結ばれた各条件のうち、複数の条件を満足する顧客のみ抽出するようにして絞り込みをしている。
【０１４５】
この抽出した顧客一覧を表示し、操作者による手入力による修正を受け入れる（ステップＳ７）。
【０１４６】
以上で販促商品および顧客抽出フェーズが終了する。
【０１４７】
次に、整合フェーズでは、上記抽出された商品と顧客に関して、それぞれ商品ＤＢ２０１および顧客ＤＢ２０２に保持されているカテゴリー情報を用いて、ミスマッチとなっている部分を削除する（ステップＳ８）。
【０１４８】
これは、抽出された各顧客のカテゴリーのうち「ドントケア」以外のカテゴリーと、抽出された全商品のカテゴリー全てを比較し、どちらか一方にしか含まれないカテゴリーがあれば、そのカテゴリーをもつ商品や顧客を抽出したリストから外すことによって行う。
【０１４９】
これによって、抽出された各商品のカテゴリーと、同じカテゴリーの顧客が抽出された各顧客の中に必ず含まれることになる。
【０１５０】
この整合した商品一覧と顧客一覧を表示し、操作者による手入力による修正を受け入れる（ステップＳ９）。
【０１５１】
以上で、販促商品と顧客が最終的に決定したので、次に、販売方法決定フェーズに移る。
【０１５２】
販売決定フェーズでは、まず、顧客ＤＢ２０２を検索して、抽出した各顧客に対するアプローチ方法を獲得する。
【０１５３】
そして、これによって一番獲得された数の多いアプローチ方法に決定する（ステップＳ１０）。
【０１５４】
上記決定したアプローチ方法と、獲得した他のアプローチ方法を表示し、操作者の手入力によるアプローチ方法の変更を受け入れる（ステップＳ１１）。
【０１５５】
これによって、採用するアプローチ方法が最終決定される。
【０１５６】
もちろん、複数のアプローチ方法を採用するように決定してもよい。
【０１５７】
さらに、商品ＤＢ２０１を検索して、抽出した各商品に対する売り方情報を獲得する。
【０１５８】
そして、これによって、獲得した数の一番多い、売り方に決定する（ステップＳ１２）。
【０１５９】
上記決定した売り方と、獲得した他の売り方情報を表示し、操作者の手入力による売り方の変更を受け入れる（ステップＳ１３）。
【０１６０】
これによって、採用する売り方が最終決定される。
【０１６１】
もちろん、複数の売り方を採用するように決定してもよい。
【０１６２】
以上で、販促対象の商品、顧客、アプローチ方法、売り方が決定されたことになる。
【０１６３】
この情報は、最終結果として出力されるとともに、実績と後日対比するために、該販売支援システム中に保存される。
【０１６４】
＜実施形態２＞
上述した実施形態１では、販売目的より知識ベース２０５のルールにもとづき、販売すべき商品と、販売すべき顧客が抽出され、両者のミスマッチをカテゴリー項目で除くようにしている。
【０１６５】
この実施形態２では、顧客層を特定して、この顧客層に適した商品を購買履歴情報より抽出し、この商品に対する売り方を決定してゆくものである。
【０１６６】
本実施の形態において用いられるＤＢ等の構成や内容は、上述した実施形態１のそれと同様であり、「販売戦術策定支援プログラム」の処理のみが上述した実施形態１と異なっている。
【０１６７】
このため、「販売戦術策定支援プログラム」の処理内容を図４のフローチャートを参照して詳細に説明する。
【０１６８】
まず、顧客層の特定をする。
【０１６９】
この場合、操作者は、過去の販売履歴に鑑みて、経営上販売促進活動を実施すべき顧客層を決定する作業を行う。
【０１７０】
具体的には、操作者が、表４に記載した顧客の層別条件を見て、自己の営業成績を向上させるにはどの顧客層に対して販売促進活動をするのが最適であるかを判断し、選択した顧客層を販売支援システムに入力する（ステップＳ２１）。
【０１７１】
ここで、入力は、例えば、７Ａのように指定する。
【０１７２】
もちろん、複数の顧客層を入力するようにしてもよい。
【０１７３】
次に、この入力された顧客層に含まれる顧客を特定する。
【０１７４】
上記入力された顧客層の条件より顧客層別ＤＢ２０４を検索して、この条件を満足する顧客番号を得る（ステップＳ２２）。
【０１７５】
そして、顧客ＤＢ２０２を検索して、上記得られた顧客番号の顧客の購買履歴情報より購入商品を調べる（ステップＳ２３）。
【０１７６】
さらに、これらの調べた購入商品を数量順、販売額順、利益額順の３つより操作者により選択された１つでソートして、リスト形式にして表示する（ステップＳ２４）。
【０１７７】
このリストのうち、例えば、１０件の商品をデフォルトで選択する（ステップＳ２５）。
【０１７８】
ただし、これは、操作者が適宜商品を選択するようにしてもよい。
【０１７９】
次に、この選択された商品について、商品層別ＤＢ２０３を調査し、これらの商品が属する商品層を得る（ステップＳ２６）。
【０１８０】
そして、この商品層を販促商品の対象とし（ステップＳ２７）、商品ＤＢ２０１よりこれらの商品の売り方を得る（ステップＳ２８）。
【０１８１】
これにより、販売促進対象の「顧客」と、その顧客に対する「商品（品揃え）」と売り方」が決定される。
【０１８２】
＜実施形態３＞
この実施形態３では、商品の属する層を特定して、この商品層に合致した顧客を販売履歴より抽出し、この顧客に対するアプローチ方法を決定してゆくものである。
【０１８３】
本実施の形態において用いられるＤＢ等の構成や内容は、上述した実施形態１のそれと同様であり、「販売戦術策定支援プログラム」の処理のみが上述した実施形態１と異なっている。
【０１８４】
このため、「販売戦術策定支援プログラム」の処理内容を図５のフローチャートを参照して詳細に説明する。
【０１８５】
まず、商品層の特定をする。
【０１８６】
この場合、操作者は、過去の販売履歴に鑑みて、経営上販売促進活動を実施すべき商品層を決定する作業を行う。
【０１８７】
具体的には、操作者が、表２に記載した商品の層別条件を見て、自己の営業成績を向上させるにはどの商品層に対して販売促進活動をするのが最適であるかを判断し、選択した商品層を販売支援システムに入力する（ステップＳ３１）。
【０１８８】
ここで、入力は、例えば、７Ａのように指定する。
【０１８９】
もちろん、複数の商品層を入力するようにしてもよい。
【０１９０】
次に、この入力された商品層に含まれる商品を特定する。
【０１９１】
上記入力された商品層の条件より商品層別ＤＢ２０３を検索して、この条件を満足する商品番号を得る（ステップＳ３２）。
【０１９２】
そして、商品ＤＢ２０１を検索して、上記得られた商品番号の商品の販売履歴情報より購入顧客を調べる（ステップＳ３３）。
【０１９３】
さらに、これらの調べた購入顧客を数量順、販売額順、利益額順の３つより操作者により選択された１つでソートして、リスト形式にして表示する（ステップＳ３４）。
【０１９４】
このリストのうち、例えば、１０件の商品に対する顧客をデフォルトで選択する（ステップＳ３５）。
【０１９５】
ただし、これは、操作者が適宜を選択するようにしてもよい。
【０１９６】
次に、この選択された顧客について、顧客層別ＤＢ２０４を調査し、上記選択された顧客が属する顧客層を得る（ステップＳ３６）。
【０１９７】
そして、この顧客層を販促顧客の対象とし（ステップＳ３７）、顧客ＤＢ２０２よりその顧客層に対するアプローチ方法を得る（ステップＳ３８）。
【０１９８】
これにより、販売促進対象の「商品（品揃え）」と、「顧客」と、その顧客に対する「アプローチ方法」が決定される。
【０１９９】
【発明の効果】
従って、以上説明したように、本発明によれば、販売計画の策定を有効に支援可能な販売支援システム及び販売支援方法を提供することができる。
【図面の簡単な説明】
【図１】図１は、本発明の実施形態１による販売支援システムのハード構成を示すブロックである。
【図２】図２は、本発明の実施形態１による販売支援システムのハード構成に用いられるＤＢ等の構成を示すブロックである。
【図３】図３は、本発明の実施形態１による販売支援システムの処理手順を説明するためのフローチャートである。
【図４】図４は、本発明の実施形態２による販売支援システムの処理手順を説明するためのフローチャートである。
【図５】図５は、本発明の実施形態３による販売支援システムの処理手順を説明するためのフローチャートである。
【符号の説明】
１０１…データベースサーバ（ＤＢ）、
１０２…ＰＯＳ端末、
１０３…ＰＣ端末、
１０４…ネットワークプリンタ、
１０５…ＬＡＮ回線、
２０１…商品ＤＢ、
２０２…顧客ＤＢ、
２０３…商品層別ＤＢ、
２０４…顧客層別ＤＢ、
２０５…知識ベース。[0001]
BACKGROUND OF THE INVENTION
The present invention is a sales support system.And sales support methodIn particular, sales support systems that support the development of sales plans using computersAnd sales support methodAbout.
[0002]
[Prior art]
A technique for storing information about a customer in a computer, analyzing the information, and utilizing it for customer service is widely known.
[0003]
For example, Japanese Patent Application Laid-Open No. 8-50617 discloses a technique for improving the efficiency of creating an estimate using customer information collected through a questionnaire or the like.
[0004]
In addition, a technique for analyzing customer purchase history and making effective sales promotion materials is also widely known.
[0005]
For example, in a technique called ABC analysis, customers are stratified by criteria such as purchase amount, and an important customer segment is extracted.
[0006]
Further, in a technique called RFM analysis, analysis is performed from the viewpoint of extracting customers who have purchased more recently.
[0007]
[Problems to be solved by the invention]
On the other hand, due to the individualization of consumers, the effects of conventional uniform sales methods are fading.
[0008]
Targeting a group of consumers who are said to be the thickest middle class, if the sales campaign has been expanded, the period of certain results will be over. If sales plans that are clearly conscious are not formulated, effective sales promotions compared to costs are becoming difficult to achieve.
[0009]
However, if you make a wrong choice at the starting point of “to which customer”, “what”, “when”, and “how to sell”, you can develop a good plan after that. However, it will not function as an effective plan.
[0010]
For this reason, it is important to first select an appropriate customer or product, and further, this selection itself needs to be changed flexibly according to various conditions faced by management.
[0011]
In addition, approach methods suitable for customers and sales method information suitable for products belong to the know-how of the seller, and many years of experience are required to determine appropriate approach methods and sales methods.
[0012]
The present invention is based on the above problems.SalesSales support system that can effectively support the development of sales plansAnd sales support methodThe purpose is to provide.
[0013]
[Means for Solving the Problems]
  According to the present invention, in order to solve the above problems,
  (1) By programmed computerComposed, A sales support system that supports the development of sales plans,
  A customer database that holds customer information about each customer, including the customer categories that categorize customers,
  A product database that holds product information about each product, including a category of a customer targeted for the product, consisting of some of the customer categories;
  A product stratification database that stores the product stratification results for each product categorized into multiple stratification items, corresponding to the product,
  A customer stratification database that stores customer stratification results in which each customer is stratified into multiple stratification items, in correspondence with the customer,
  Corresponding to a plurality of sales purposes, the conditions for extracting products from the product stratification database using the product stratification results and the conditions for extracting customers from the customer stratification database using the customer stratification results are as follows: A knowledge base to hold,
  A sales purpose setting means for setting a sales purpose;
  According to the sales purpose set by the sales purpose setting means, based on the content of the knowledge base, customer extraction means for extracting customers from the customer stratification database;
  Product extraction means for extracting products from the product stratification database based on the contents of the knowledge base according to the sales purpose set by the sales purpose setting means;
  For all of the customers extracted by the customer extraction means, the customer category is extracted from the customer database, and for all of the products extracted by the product extraction means, the customer category targeted for the product is the product database. Compared with all categories extracted from the product database, and all categories other than the category that is not used as the product information among the categories extracted from the customer database,If there is a category that is included in only one of the categories, the product and customer with that category are excluded from the extraction results, thereby matching the extraction results of the customer extraction means and the extraction results of the product extraction means.YouMatching means,
  A sales support system is provided.
[0014]
In other words, in this sales support system,By inputting the sales date according to various conditions faced by the management body, a “product” and a “customer” suitable for the sales purpose are proposed and sales are supported.
[0015]
  Further, according to the present invention, in order to solve the above problems,
  (2)The above product informationIncludes how-to information for each productOnly,
  The product extracted by the product information extraction unit and matched by the matching unit, and the productThe databaseBased on the seller information held in the output, the seller outputs the seller information for the extracted and matched products.Step,
  The sales support system according to (1) is further provided.
[0016]
That is, in this sales support system, the sales plan that supports the formulation is made more practical by outputting even the “sales information” of the extracted and matched products.
[0017]
  Further, according to the present invention, in order to solve the above problems,
  (3)The customer information above isIncludes approach information for each customerOnly,
  The customer extracted by the customer information extracting means and matched by the matching means, and the customerThe databaseBased on the approach information held in theStep,
  The sales support system according to (1) is further provided.
[0018]
That is, in this sales support system, the sales plan for supporting the formulation is made more practical by outputting the “approach information” for the extracted and matched customers.
[0019]
  Further, according to the present invention, in order to solve the above problems,
  (4) By programmed computerExecuted, A way to help formulate sales plans,
  The computer
  A customer database that holds customer information about each customer, including the customer categories that categorize customers,
  A product database that holds product information about each product, including a category of a customer targeted for the product, consisting of some of the customer categories;
  The product stratification results obtained by stratifying each product into multiple stratification items are associated with that product.HoldProduct stratification databaseWhen,
  The customer stratification results obtained by stratifying each customer into multiple stratification items are associated with that customer.HoldCustomer stratification databaseWhen,
  Corresponding to a plurality of sales purposes, the conditions for extracting products from the product stratification database using the product stratification results and the conditions for extracting customers from the customer stratification database using the customer stratification results are as follows:HoldKnowledge baseAnd
  Purpose of salesAccept settings forSteps,
  SettingA customer extraction step of extracting customers from the customer stratification database based on the content of the knowledge base according to the set sales purpose;
  SettingA product extraction step of extracting a product from the product stratification database based on the content of the knowledge base according to a set sales purpose;
  For all the customers extracted in the customer extraction step, the category of the customer is extracted from the customer database, and for all the products extracted in the product extraction step, the category of the customer targeted for the product is Compared with all categories extracted from the product database, extracted from the product database, all categories other than the category not used as the product information among the categories extracted from the customer database,If there is a category that is included in only one of the categories, a matching step for matching the extraction result of the customer extraction step and the extraction result of the product extraction step by excluding the product and customer having the category from the extraction result; ,
  TheExecutionA sales support method is provided.
[0020]
That is, this sales supportMethodInBy inputting the sales date according to various conditions faced by the management body, a “product” and a “customer” suitable for the sales purpose are proposed and sales are supported.
[0031]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to the drawings.
[0032]
<Embodiment 1>
The sales support system according to the first embodiment is a sales support system using a database (DB) in which “customer”, “product (assortment)”, and “how to sell” are determined according to the sales purpose.
[0033]
In this embodiment, apparel sales are assumed.
[0034]
Next, an outline of the first embodiment will be described.
[0035]
In the sales support system according to the first embodiment, the product information and customer information obtained from the sales history and external information are held in the product DB and the customer DB, and further, the product layer in which the products are stratified according to a unique standard. Separate DBs and customers are stored in a customer stratification DB that is stratified according to its own standards.
[0036]
When the sales purpose is input, based on the knowledge base rules, the products targeted for sales promotion are extracted and presented using the data in the product base DB, and further, the data in the customer base DB based on the knowledge base rules. A customer to be promoted is extracted and presented.
[0037]
Then, after removing the mismatch between the presented product and the customer, the approach method suitable for the customer and the selling method information suitable for the product are presented.
[0038]
That is, the sales support system according to the first embodiment proposes to whom and what to sell according to the sales purpose.
[0039]
Hereinafter, details of the first embodiment will be described.
[0040]
FIG. 1 is a diagram showing a hardware configuration of a sales support system according to Embodiment 1 of the present invention.
[0041]
As shown in FIG. 1, the sales support system according to the present invention includes one database server (DB) 101, a plurality of POS terminals 102, a plurality of PC terminals 103, a plurality of network printers 104, and a LAN. Line 105.
[0042]
Here, the PC terminal 102 is a personal computer equipped with an emulator.
[0043]
The DB server 101 is connected to the head office computer of the sales support system via a communication line.
[0044]
Sales data collected by the POS terminal 102 is sent to the DB server 101 via the LAN line 105 and stored and managed as sales (purchase) history data.
[0045]
Various databases and operable programs are prepared on the DB server 101, and these are operated by the PC terminal 103.
[0046]
The processing results in the DB server 101 are transmitted to the head office computer via a communication line, and products and customer information are sent to the DB server 101 from the head office computer. .
[0047]
On the DB server 101, there are a sales tactic formulation support program, a sales history output program, a sales history acquisition program, and a DB maintenance program as main programs.
[0048]
Here, the sales tactics formulation support program supports the formulation of a sales plan, and this embodiment will be described in detail below.
[0049]
The sales history output program outputs past sales history data by ABC analysis, RFM analysis or the like.
[0050]
The sales history acquisition program collects a sales history from a POS terminal provided in each store.
[0051]
The DB maintenance program creates each DB from sales history data and maintenance data.
[0052]
FIG. 2 is a diagram showing a configuration of main DBs and the like used in the hardware configuration of the sales support system according to the first embodiment of the present invention.
[0053]
Details of each DB and the like will be described later, but here, an overview will be introduced using FIG.
[0054]
The sales (purchase) history data D1 is collected by the sales history acquisition program.
[0055]
The DB maintenance data D2 includes product data update information and customer data update information.
[0056]
The product DB 201 is for daily addition / deletion / change / update of product information based on the sales history data D1 and the DB maintenance data D2.
[0057]
In the customer DB 202, customer information is added / deleted / changed / updated on a daily basis based on sales history data D1 including purchase history and complaint history and DB maintenance data D2.
[0058]
The product stratification DB 203 is a weekly addition / deletion / change / update of product stratification information with reference to information in the customer DB 201 and the product DB 202 from the sales history data D1 including the sales history.
[0059]
The customer stratification DB 204 is a weekly addition / deletion / change / update of customer stratification information with reference to the information in the customer DB 201 and the product DB 202 from the sales history data D1 including the purchase history.
[0060]
The knowledge base 205 is changed and updated as needed in the sales strategy development support program.
[0061]
As shown in FIG. 2, the contents of the database other than the knowledge base are processed using the contents of the sales (purchase) history data D1 and the DB maintenance data D2.
[0062]
The DB maintenance program performs batch processing for updating various DBs at a predetermined timing from the sales history data D1 and DB maintenance data D2 (preliminarily input from the PC terminal).
[0063]
Hereinafter, the contents of each DB will be described in detail.
[0064]
First, “category” that is data included in the product DB 201 and the customer DB 202 will be described.
[0065]
The categories in the customer DB 202 and the product DB 201 are as shown in Table 1 below: teens (young teens), young adults (single in the early 20s), conservatives (major who prefer conservative style), and advance (progressive) Age), aged (elderly), don't care (all ages who are not so impressed with clothes).
[0066]
[Table 1]

[0067]
(Contents of the product DB 201)
In the product DB 201, the category item indicates to which category of customer the product is targeted (however, don't care is not included in the category of the product DB 201).
[0068]
The contents of the product DB 201 include the following.
[0069]
1. Product basic information
The product basic information includes a product code, a product name, a registration date, a category, and the like.
[0070]
2. Price information
This price information includes a purchase price, a normal sales price, a discount sales price, a break-even sales price, and the like.
[0071]
3. Sales history information
The sales history information includes sales history information and the like so far.
[0072]
4). How to sell
This sales information includes sales price type information (exclusive price sale, discount after discount sale, discount sale only), display method information (high-quality display, normal display, wagon display, display attached to other products), Customer service information (explanation sales target, explanation unnecessary, recommending other products, etc.) is included.
[0073]
(Contents of customer DB 202)
In this customer DB 202, customers are classified into predetermined categories.
[0074]
The contents of the customer DB 202 have information in the following four major categories for each customer.
[0075]
1. Customer basic information
The customer basic information includes customer code, name, age, category, address, telephone number, occupation, subscription magazine, personal information such as subscription newspaper, and the like.
[0076]
2. Purchase history information
This purchase history information includes purchase history information and the like so far.
[0077]
3. Approach information
In this approach information, approach method information suitable for each customer (direct mail, magazine advertisement, newspaper flyer, station poster, e-mail, etc.) determined in consideration of the customer's own wishes, basic information, and purchase history Etc. are included.
[0078]
4). Claim information
This complaint information includes opinions and complaints received from each customer and information on the end of the complaint.
[0079]
(Contents of product category DB 203)
As the contents of the product stratification DB 203, the result of categorizing products according to a predetermined standard is held.
[0080]
The contents of each layer will be described with reference to Table 2 below.
[0081]
Here, the sales history or product attributes are stratified.
[0082]
[Table 2]

[0083]
That is, the results of stratification according to the criteria in Table 2 are as follows. Cumulative sales amount (cumulative total of product sales over the past year (5 million yen or more, 500 to 500,000 yen, 500,000 yen or less), 2. Gross profit accumulation (product over the past year) Cumulative gross profit by stratification / cumulative (2 million yen or more, 200 to 300,000 yen, 300,000 yen or less), 3. Product grade (by product grade, stratification / grade is (high grade, normal, popular product) )) 4. Discount rate (by price discount possibility of products, stratified and selling price (list price, discount to 30%, discount by 30% or more)), 5. Sales amount fluctuation (only for year-round products) (sales amount) In the past 3 weeks ・ Sales amount (increase, almost constant, decrease), 6. Timeliness (seasonal products only) (whether seasonal products are seasonal products or seasonal products (seasonal products) , Before and after the season, out of season), 7. New product degree (period from the start of sales / from the start of sales (within 1 month, 1-6 months, 6 items) Above)), 8. Brand power level (stratified in brand power, brand power is (strong, moderate, are included weak)), and the like.
[0084]
Here, at the time of stratification, only products having data that can be classified by each standard are targeted for stratification.
[0085]
Of course, it is assumed that one product may be stratified by overlapping with a plurality of standards.
[0086]
Here, there are three stratifications, and the contents are as described in parentheses in Table 2.
[0087]
Each layer is indicated by the symbols A, B, and C from the left of the parenthesis.
[0088]
For example, the symbol indicating the “product grade or luxury” layer is indicated by “3A” because the item number “product grade” is 3, and the “high grade” layer corresponds to A.
[0089]
The actual format of the product layer DB 203 is as shown in Table 3 below.
[0090]
[Table 3]

[0091]
That is, as an example of the format of these stratified results, as shown in Table 3, the product codes 10001, 10001, 10003, and 10004 are divided into 1 to 8 columns and AAABCA (however, 6 columns are blank). ), CBAAAABA, ACCCACCC, BBBBBBBBB (however, the 6th column is blank).
[0092]
Here, when it is not applicable or the data cannot be classified due to lack of data, it is blank.
[0093]
In the format example shown in Table 3, for example, in the case of the product code 10001, the third column is A, and therefore, in the “product grade” of the item 3 of the stratification, the stratification is “high quality” of A. It turns out that it corresponds.
[0094]
(Customer segment DB 204)
The content of the customer stratification DB 204 holds the result of stratifying customers according to a predetermined standard.
[0095]
The contents of each layer will be described with reference to Table 4 below.
[0096]
Here, the purchase history is used for stratification.
[0097]
[Table 4]

[0098]
That is, the results of stratification according to the criteria in Table 4 are as follows. 1. Brand fidelity (strategy / fidelity (large, medium, small) according to brand fidelity) 2. Seasonal product purchase time (seasonal product purchase time and stratification / purchase time of the seasonal product sales period (first, middle, second half)) 3. New product purchase time (stratified and announced at the time of new product purchase (immediately, within half a year, thereafter)) Purchase price (Purchase price at the time of purchasing the product (Price: discount within 30%, discount over 30%)) Product grade (by grade of purchased product, stratified and product grade (high quality, normal, popular product)), 6. 6. Purchase frequency (by purchase frequency, stratified and purchase frequency is yearly (5 times or more, 1 to 4 times, 1 time or less)), Purchase amount (by purchase amount, stratified and purchase amount per year (70,000 yen or more, 70 to 30,000 yen, 30,000 or less)), 8. Customer degree change (by purchase price change, stratification / purchase amount (increase, unchanged, decrease)), 9. Sales response (the percentage of purchases in the sale is stratified and the purchase amount in the sale (50% or more, 50 to 30%, 30% or less)).
[0099]
Here, in stratification, only customers who have enough data to be classified according to each standard are targeted for stratification.
[0100]
Of course, it is assumed that one customer may be stratified by a plurality of criteria.
[0101]
There are three stratifications and the contents are listed in parentheses in Table 4.
[0102]
Each layer is indicated by the symbols A, B, and C from the left of the parenthesis.
[0103]
The actual format of the customer group-specific DB 204 is as shown in Table 5 below.
[0104]
[Table 5]

[0105]
That is, as shown in Table 5, as an example format of these stratified results,clientThe codes A0001, A0002, A0003, and A0004 are divided into columns 1 to 9, respectively, such as CAAAAAAABC, CCCCCBCBA, AABBBC (however, columns 7 to 9 are blank) and BBCAAAACB.
[0106]
Here, when it is not applicable or the data cannot be classified due to lack of data, it is blank.
[0107]
And this table5In the format example shown in FIG. 4, for example, in the case of the customer code A0001, the third column is A, so in the “new product purchase time” of the item 3 of the stratification, the stratification corresponds to “immediately after the announcement of A” I know that
[0108]
(Knowledge base)
Table 6 below shows an example of the contents of the knowledge base 205.
[0109]
That is, as an example of the knowledge base 205, the result extracted for the purpose of sales is stored according to the criteria shown in Table 6 below.
[0110]
[Table 6]

[0111]
In other words, the results extracted based on the criteria in Table 6 are divided into columns of the product stratification DB extraction condition and the customer stratification DB extraction condition for sales purposes. Secure sales 1A + 1B + 3C + 6A, 6A + 7A, 2. 2. Secure profit 2A + 3A + 4A, 4A + 5A Seasonal stock disposal 6C, 2C, 4. New product sales promotion 7A + 7B, 3A + 3B, 5. Brand sales promotion 8A, 1A + 1B, etc. are included.
[0112]
For example, in Table 6, for the purpose of “Securing profits”, the product is “cumulative gross profit of 2 million yen or more (2A); The customer is extracted with “Purchase price is fixed price (4A), or purchase product is high-grade (3A)”.
[0113]
In this case, the knowledge base extraction conditions are included as defaults, but can be updated to desired settings on the spot.
[0114]
Next, before describing the details of the processing flow of the sales support system configured as described above, an outline of each phase of the flow of processing by the sales support system will be described.
[0115]
1. Objective determination phase
The store manager uses the “sales history output program” to determine the sales purpose for each MD week based on the past sales history.
[0116]
The sales purpose is extracted from a plurality of candidates shown in the list.
[0117]
Here, the MD week is the year divided into 52 weeks.
[0118]
2. Promotional product and customer extraction phase
The products that match the sales purpose are extracted from the product stratification DB 203 according to the rules of the knowledge base.
[0119]
The result extracted from the product stratification DB 203 can be corrected manually.
[0120]
Customers that match the sales purpose are extracted from the customer stratification DB 204 according to the rules of the knowledge base.
[0121]
The results extracted from this customer stratification DB 204 can be corrected manually.
[0122]
3. Alignment phase
Using the category information, the mismatched portion between the extracted product and the customer is deleted.
[0123]
The product and customer from which the mismatch portion has been deleted can be manually corrected again.
[0124]
4). Sales method decision phase
For the customer determined as described above, the approach method for the target customer is searched from the approach information of the customer DB 202.
[0125]
Further, with respect to the product determined as described above, how to sell the target product is determined from the sales method information in the product DB 201.
[0126]
The approach method of the customer DB 202 and the selling method of the product DB 201 can be corrected manually.
[0127]
1 above. ~ 4. Through this phase, “customer”, “product (assortment)” and “how to sell” are determined according to the sales purpose.
[0128]
Next, the details of the processing procedure of the sales support system configured as described above will be described.
[0129]
First, the “sales history output program” is activated on the PC terminal 102 and the past sales history is examined.
[0130]
Next, the “sales tactics formulation support program” is started, and a desired sales tactics are formulated.
[0131]
This will be described below with reference to the flowchart shown in FIG.
[0132]
In the target determination phase, first, a list including a plurality of sales purpose candidates is presented in the sales purpose setting window (step S1).
[0133]
Examples of the sales purpose list include “sales securing”, “profit securing”, “seasonally delayed inventory disposal”, “new product sales promotion”, “brand sales promotion”, and the like.
[0134]
The operator (mainly the store manager) selects and inputs an appropriate sales purpose in view of the past sales history, and the sales support system sets the sales purpose based on this input (step S2).
[0135]
The operation of inputting the sales purpose is performed for each MD week, and the sales purpose is set for a necessary number of MD weeks.
[0136]
Next, the operator appropriately inputs a sales target (sales amount or sales amount) for each MD week, and the sales support system holds the input sales target (sales amount or sales amount) (step S3).
[0137]
This completes the target determination phase.
[0138]
Next, in the product and customer extraction phase, first, a product corresponding to the sales purpose set in step S2 is extracted.
[0139]
This product extraction obtains the extraction condition of the product stratification DB 203 corresponding to the input sales purpose from the list of sales purpose and product stratification DB extraction conditions stored in the knowledge base 205, and the product is extracted under this extraction condition. This is performed by searching the stratified DB 203 and extracting products that meet the conditions (step S4).
[0140]
At this time, if the sales target input in step S3 is taken into consideration and the sales target is low, a plurality of conditions among the conditions connected by OR (+) in the extraction condition expression of the knowledge base 205 are satisfied. Narrow down by extracting only products.
[0141]
The extracted product list is displayed, and correction by manual input by the operator is accepted (step S5).
[0142]
Next, the customer corresponding to the sales purpose input in step S2 is extracted.
[0143]
This customer extraction is performed by obtaining the extraction condition of the customer stratification DB 204 corresponding to the set sales purpose from the sales purpose and customer stratification DB extraction condition list stored in the knowledge base 205, and using this extraction condition as a customer. This is done by searching the stratified DB 204 and extracting customers that meet the conditions (step S6).
[0144]
At this time, when the sales target input in step S3 is taken into consideration and the sales target is low, a plurality of conditions among the conditions connected by OR (+) in the extraction condition expression of the knowledge base 205 are satisfied. Narrow down by extracting only the customers who do.
[0145]
The extracted customer list is displayed, and correction by manual input by the operator is accepted (step S7).
[0146]
This completes the sales promotion product and customer extraction phase.
[0147]
Next, in the matching phase, the mismatched portion is deleted using the category information held in the product DB 201 and the customer DB 202 for the extracted product and customer (step S8).
[0148]
This compares the categories of each extracted customer other than “Don't Care” with all the categories of all the extracted products, and if there is a category that is included in only one of them, the product that has that category Or by removing customers from the extracted list.
[0149]
As a result, the category of each extracted product and the customer of the same category are always included in each extracted customer.
[0150]
The matched product list and customer list are displayed, and correction by manual input by the operator is accepted (step S9).
[0151]
With the above, since the sales promotion product and the customer are finally determined, the process proceeds to the sales method determination phase.
[0152]
In the sales decision phase, first, the customer DB 202 is searched to acquire an approach method for each extracted customer.
[0153]
As a result, the approach method having the largest number of acquisitions is determined (step S10).
[0154]
The determined approach method and other acquired approach methods are displayed, and the change of the approach method by the operator's manual input is accepted (step S11).
[0155]
As a result, the approach method to be adopted is finally determined.
[0156]
Of course, you may decide to employ | adopt a some approach method.
[0157]
Further, the product DB 201 is searched to obtain information on how to sell each extracted product.
[0158]
As a result, the selling method having the largest number of acquired items is determined (step S12).
[0159]
The determined selling method and other acquired selling method information are displayed, and the change of the selling method manually input by the operator is accepted (step S13).
[0160]
As a result, the sales method to be adopted is finally determined.
[0161]
Of course, you may decide to employ a plurality of selling methods.
[0162]
With the above, the product, customer, approach method, and sales method to be promoted are determined.
[0163]
This information is output as a final result and stored in the sales support system for comparison with the actual results at a later date.
[0164]
<Embodiment 2>
In the first embodiment described above, based on the rules of the knowledge base 205 based on the sales purpose, the products to be sold and the customers to be sold are extracted, and mismatches between them are excluded by category items.
[0165]
In the second embodiment, a customer segment is specified, a product suitable for this customer segment is extracted from purchase history information, and a sales method for this product is determined.
[0166]
The configuration and contents of the DB and the like used in the present embodiment are the same as those of the first embodiment described above, and only the processing of the “sales tactics formulation support program” is different from the first embodiment described above.
[0167]
Therefore, the processing content of the “sales tactics formulation support program” will be described in detail with reference to the flowchart of FIG.
[0168]
First, identify customer segments.
[0169]
In this case, the operator performs an operation of determining a customer layer on which sales promotion activities are to be performed in view of the past sales history.
[0170]
Specifically, the operator should look at the customer stratification conditions listed in Table 4 to determine which customer segment is most suitable for promoting sales in order to improve their business performance. Judgment is made and the selected customer segment is input to the sales support system (step S21).
[0171]
Here, the input is designated as 7A, for example.
[0172]
Of course, a plurality of customer segments may be input.
[0173]
Next, a customer included in the input customer segment is specified.
[0174]
The customer segment DB 204 is searched from the input customer segment conditions, and a customer number satisfying these conditions is obtained (step S22).
[0175]
Then, the customer DB 202 is searched, and the purchased product is examined from the purchase history information of the customer of the obtained customer number (step S23).
[0176]
Further, these purchased purchased items are sorted by one selected by the operator from the order of quantity, sales amount, and profit amount, and displayed in a list format (step S24).
[0177]
From this list, for example, ten items are selected by default (step S25).
[0178]
However, the operator may select a product as appropriate.
[0179]
Next, the product layer DB 203 is examined for the selected product, and the product layer to which these products belong is obtained (step S26).
[0180]
Then, this product layer is targeted for the promotional product (step S27), and how to sell these products is obtained from the product DB 201 (step S28).
[0181]
As a result, the “customer” to be promoted and the “product (assortment)” and sales method for the customer are determined.
[0182]
<Embodiment 3>
In the third embodiment, a layer to which a product belongs is specified, a customer that matches the product layer is extracted from the sales history, and an approach method for the customer is determined.
[0183]
The configuration and contents of the DB and the like used in the present embodiment are the same as those of the first embodiment described above, and only the processing of the “sales tactics formulation support program” is different from the first embodiment described above.
[0184]
Therefore, the processing contents of the “sales tactics formulation support program” will be described in detail with reference to the flowchart of FIG.
[0185]
First, the product layer is specified.
[0186]
In this case, the operator performs an operation of determining a product layer on which the sales promotion activity is to be executed in view of the past sales history.
[0187]
Specifically, the operator should look at the product stratification conditions listed in Table 2 to determine which product layer is most suitable for promoting sales in order to improve their business performance. The determined product layer is input to the sales support system (step S31).
[0188]
Here, the input is designated as 7A, for example.
[0189]
Of course, a plurality of product layers may be input.
[0190]
Next, a product included in the input product layer is specified.
[0191]
The product layer-specific DB 203 is searched based on the input product layer condition, and a product number satisfying this condition is obtained (step S32).
[0192]
Then, the product DB 201 is searched, and the purchase customer is examined from the sales history information of the product having the obtained product number (step S33).
[0193]
Furthermore, these purchased customers that have been examined are sorted according to one selected by the operator from the order of quantity, sales amount, and profit amount, and are displayed in a list format (step S34).
[0194]
From this list, for example, customers for 10 items are selected by default (step S35).
[0195]
However, this may be appropriately selected by the operator.
[0196]
Next, for this selected customer, the customer group DB 204 is examined to obtain the customer group to which the selected customer belongs (step S36).
[0197]
Then, this customer segment is targeted for the sales promotion customer (step S37), and an approach method for the customer segment is obtained from the customer DB 202 (step S38).
[0198]
As a result, “product (assortment)” to be promoted, “customer”, and “approach method” for the customer are determined.
[0199]
【The invention's effect】
Therefore, as described above, according to the present invention, a sales support system that can effectively support the formulation of a sales plan.And sales support methodCan be provided.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a hardware configuration of a sales support system according to Embodiment 1 of the present invention.
FIG. 2 is a block diagram showing a configuration of a DB or the like used in the hardware configuration of the sales support system according to the first embodiment of the present invention.
FIG. 3 is a flowchart for explaining a processing procedure of the sales support system according to the first embodiment of the present invention.
FIG. 4 is a flowchart for explaining a processing procedure of the sales support system according to the second embodiment of the present invention.
FIG. 5 is a flowchart for explaining a processing procedure of the sales support system according to the third embodiment of the present invention.
[Explanation of symbols]
101 ... Database server (DB),
102 ... POS terminal,
103 ... PC terminal,
104 ... Network printer,
105 ... LAN line,
201 ... commodity DB,
202 ... customer DB,
203 ... Product segment DB,
204 ... DB by customer segment,
205 ... Knowledge base.

Claims (4)

A sales support system that consists of programmed computers and supports the development of sales plans.
A customer database that holds customer information about each customer, including the customer categories that categorize customers,
A product database that holds product information about each product, including a category of a customer targeted for the product, consisting of some of the customer categories;
A product stratification database that stores the product stratification results for each product categorized into multiple stratification items, corresponding to the product,
A customer stratification database that stores customer stratification results corresponding to each customer,
Corresponding to a plurality of sales purposes, the conditions for extracting products from the product stratification database using the product stratification results and the conditions for extracting customers from the customer stratification database using the customer stratification results are as follows: A knowledge base to hold,
A sales purpose setting means for setting a sales purpose;
According to the sales purpose set by the sales purpose setting means, based on the content of the knowledge base, customer extraction means for extracting customers from the customer stratification database;
Product extraction means for extracting products from the product stratification database based on the contents of the knowledge base according to the sales purpose set by the sales purpose setting means;
For all of the customers extracted by the customer extraction means, the customer category is extracted from the customer database, and for all of the products extracted by the product extraction means, the customer category targeted for the product is the product database. Compared with all categories extracted from the customer database, except for categories that are not used as product information, and all categories extracted from the product database, they are included in only one of the categories. If there is no category, a matching unit that matches the extraction result of the customer extraction unit and the extraction result of the product extraction unit by excluding the product and customer having the category from the extraction result;
A sales support system comprising: The above product information, viewing including the sales methods information for each product,
A product in which the alignment means is aligned with said product information extracting means extracts, on the basis of the sales methods information held by the commodity database, the output means to output the sales methods information for goods that are aligned is the extraction,
The sales support system according to claim 1, further comprising: The above customer information, only contains the approach information for each customer,
The customer information extracting means extracts the customers the matching means is matched, on the basis of the approach information held by the customer database, the output means to output the approach information to customers that are aligned is the extraction,
The sales support system according to claim 1, further comprising: A method that helps a sales plan be developed by a programmed computer,
The computer
A customer database that holds customer information about each customer, including the customer categories that categorize customers,
A product database that holds product information about each product, including a category of a customer targeted for the product, consisting of some of the customer categories;
The product stratification results stratified for each commodity plurality of layers by item, and product stratification database holding in correspondence with the product,
A customer stratification database that stores customer stratification results in which each customer is stratified into multiple stratification items, in correspondence with the customer,
Corresponding to a plurality of sales purposes, the conditions for extracting products from the product stratification database using the product stratification results and the conditions for extracting customers from the customer stratification database using the customer stratification results are as follows: With a knowledge base to hold ,
A step of accepting the setting of the sales purpose;
Depending on the set has been sales purposes, based on the contents of the knowledge base, and customer extracting a customer from the customer-specific database,
Depending on the set has been sale, and product extraction step based on the contents of the knowledge base, to extract the product from the product layer-specific database,
For all the customers extracted in the customer extraction step, the category of the customer is extracted from the customer database, and for all the products extracted in the product extraction step, the category of the customer targeted for the product is Compare all categories extracted from the product database and all categories extracted from the product database, with all categories extracted from the customer database other than the categories not used as the product information. If there is a category that is not included, the matching step for matching the extraction result of the customer extraction step and the extraction result of the product extraction step by excluding the product and customer having the category from the extraction result;
The sales support method characterized by performing .

Images