Ara\u015ft\u0131rmam\u0131z, g\u00fcn\u00fcm\u00fcz m\u00fc\u015fterisini anlaman\u0131n yaln\u0131zca memnuniyet skorlar\u0131yla de\u011fil; davran\u0131\u015fsal veriler, deneyim detaylar\u0131 ve yapay zek\u00e2 destekli analitikle m\u00fcmk\u00fcn oldu\u011funu ortaya koyuyor.<\/p>\n
\u201cArt\u0131k m\u00fc\u015fteri sadakati tek bir temas noktas\u0131na de\u011fil; b\u00fct\u00fcnsel deneyime ba\u011fl\u0131. Verinin g\u00fcc\u00fcn\u00fc sadece \u00f6l\u00e7\u00fcm i\u00e7in de\u011fil, m\u00fc\u015fteriyi hissetmek ve daha ak\u0131ll\u0131 aksiyonlar tasarlamak i\u00e7in<\/strong><\/p>\n kullanmak zorunday\u0131z. Bu ara\u015ft\u0131rma, akaryak\u0131t sekt\u00f6r\u00fcnde dahi deneyimin ne kadar katmanl\u0131 oldu\u011funu ve her bir detay\u0131n NPS \u00fczerinde nas\u0131l etkiler yaratt\u0131\u011f\u0131n\u0131 net bi\u00e7imde ortaya koyuyor.\u201d<\/strong><\/p>\n XSIGHTS K\u0131demli M\u00fc\u015fteri \u00c7\u00f6z\u00fcmleri Dan\u0131\u015fman\u0131<\/p>\n Yakup Peker<\/strong><\/p>\n T\u00fcrkiye genelinde\u00a03.600 ki\u015fiyle<\/strong>, CAWI y\u00f6ntemiyle ger\u00e7ekle\u015ftirdi\u011fimiz ara\u015ft\u0131rma; m\u00fc\u015fteri sadakatini ve NPS\u2019i etkileyen t\u00fcm fakt\u00f6rleri ayr\u0131\u015ft\u0131rarak\u00a0hiyerar\u015fik modellerle<\/strong>,\u00a0driver analizleriyle<\/strong>\u00a0ve<\/p>\n yapay zek\u00e2 destekli s\u0131n\u0131fland\u0131rmalarla<\/strong>\u00a0incelemi\u015ftir. Bulgular; segmentasyon bazl\u0131 yolculuklar\u0131, istasyon hizmetlerinden sadakat programlar\u0131na kadar uzanan geni\u015f bir deneyim alan\u0131n\u0131 kapsamaktad\u0131r.<\/p>\n XSIGHTS olarak, bu kapsaml\u0131 analiti\u011fin yaln\u0131zca akaryak\u0131t sekt\u00f6r\u00fcne de\u011fil; m\u00fc\u015fteri yolculu\u011funu modellemek isteyen t\u00fcm markalara yol g\u00f6sterici nitelikte oldu\u011funa inan\u0131yoruz.<\/p>\n Raporu indirmek i\u00e7in t\u0131klay\u0131n\u0131z.<\/a><\/p>\n