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있습니다.\u003C/p\u003E\r\n\u003Cp\u003E그 과제는 더욱 심화되고 있습니다. \u003Ca href=\"https://www.snowflake.com/ko/the-modern-marketing-data-stack-report/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E최신 마케팅 데이터 스택\u003C/a\u003E 보고서에서는 모든 비즈니스의 운영 방식, 나아가 Customer 360에 접근하는 방식까지 재편하는 세 가지 상호 연결된 요소를 추적합니다.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003EAI 의무:\u003C/b\u003E AI는 더 이상 부분적인 실험에 머무르지 않고, 비즈니스 전반의 효율성을 높이고 새로운 수익 기회를 창출하기 위한 최고 경영진의 필수 전략 과제이 되었습니다.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E데이터 중력 및 개방형 아키텍처로의 전환: \u003C/b\u003E단일 통합 데이터 플랫폼으로 향하고 있는 흐름은 거부할 수 없으며, 이는 사일로화된 ‘블랙박스’ 애플리케이션에서 더욱 개방적이고 투명한 아키텍처로의 전환을 가속화하고 있습니다.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E신뢰 의무: \u003C/b\u003E규제가 증대되는 시대에 고객 신뢰는 가장 중요한 비즈니스 자산 중 하나가 되었습니다. 이로 인해, 데이터 처리 방식에 있어 새로운 수준의 개인정보 보호, 보안 및 투명성이 필요합니다.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003E이 모든 변화는 '효율적인' C360을 정의하는 기준이 달라졌음을 시사합니다. 단순히 C360을 구축하는 과제를 넘어, 오늘날의 데이터 문제를 해결하고 AI 기반의 미래 상황에 대비할 수 있는 C360을 구축하도록 변화하는 것입니다. 그렇다면, 어디서부터 시작해야 할까요?\u003C/p\u003E\r\n\u003Ch3\u003E여정을 위한 프레임워크: C360 성숙도 모델\u003C/h3\u003E\r\n\u003Cp\u003E조직에서 Customer 360 성숙도 여정에서 현재 위치를 파악하고 다음 단계를 결정할 수 있도록, 데이터 자산으로서의 C360에 초점을 맞춘 4단계 성숙도 모델을 활용할 수 있습니다.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E스테이지 1 – 사일로화된 데이터: \u003C/b\u003E고객 데이터는 존재해도 개별 애플리케이션 내에 별도로 존재하는 단계입니다. 크로스 채널 뷰가 없으며 보고는 수동적이고 일관성이 부족합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E스테이지 2 – 부분적 C360: \u003C/b\u003E주요 정형 데이터 소스가 데이터 플랫폼에 중앙 집중화되어 있지만, 뷰는 여전히 불완전하고 일관성이 없는 단계입니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E스테이지 3 – 포괄형 C360:\u003C/b\u003E 모든 주요 정형 데이터 기반의 신뢰할 수 있는 단일 고객 뷰가 존재하며, 고객이 한 \u003Ci\u003E행동\u003C/i\u003E에 대해 명확하고 신뢰할 수 있는 과거 기록을 제공합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E스테이지 4 – 지능형 C360: \u003C/b\u003E포괄형 C360은 이제 이메일 및 통화 녹취록과 같은 비정형 데이터까지 활용하여 단순히 고객의 행동뿐만 아니라 그 이면에 있는 감정과 의도까지 완벽하게 파악이 가능합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003E다음 단계 모색: 가치에 이르는 경로\u003C/h3\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-2de4783236","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--92c74fb6-c9a4-4229-a29b-8deed7c4b10f/customer-360-1.jpg?quality=85&preferwebp=true","lazyEnabled":true,"alt":"360-1","height":"902","width":"1803",":type":"snowflake-site/components/image"},"blog_text_1407379112":{"id":"blog-text-c7681d2976","text":"\u003Cp\u003E\u003Csub\u003E자료 1: Customer 360 성숙도 여정 — 조직 내 현재 성숙도의 대략적인 분포.\u003C/sub\u003E\u003C/p\u003E\n\u003Cp\u003E \u003C/p\u003E\n\u003Cp\u003E고객이 여정의 어느 단계에 있든, 불필요한 교체 없이 확고한 기반 위에서 다음 스테이지로 이동하는 것이 목표입니다.\u003C/p\u003E\n\u003Cp\u003E초기 여정(스테이지 1 및 스테이지 2)에 있는 조직의 경우, 최우선 과제는 \u003Cb\u003E포괄형 C360\u003C/b\u003E을 올바른 방식으로 구축하는 것입니다. 수십 개의 도구 간에 데이터를 복사하던 기존 모델은 이미 무너졌습니다.  비용이 많이 들고, 지연 시간이 길며, 거버넌스 통제가 되지 않아 신뢰하기 어려운(사실상 불가능에 가까운) 생태계를 만들기 때문입니다. 고객의 목표는 데이터 사본을 없애고 단일 진실 공급원 역할을 하는 단일 거버넌스 플랫폼에 데이터를 중앙 집중화하는 것입니다. 이와 같은 집중화가 그 다음 모든 작업의 기반이 됩니다.\u003C/p\u003E\n\u003Cp\u003E이미 포괄형 C360(스테이지 3)을 갖춘 조직의 경우라면 정형 데이터 통합이라는 까다로운 작업은 마친 상태입니다. 하지만 이미 상당한 수준으로 정제된 데이터를 개선하는 데 지속적으로 노력을 투입하는 경우라면 한계 수익률이 점점 낮아지는 지점으로 근접하는 것일 수 있습니다. 고객이 한 행동은 알아도, 고객이 생각하고 느끼는 바는 알지 못하기 때문에 이탈 현상에는 여전히 당혹스러움을 느끼게 됩니다. \u003C/p\u003E\n\u003Cp\u003E다음 단계는 비정형 데이터를 연결하여 고객 행동 뒤에 있는 ‘이유’를 밝혀내는 \u003Cb\u003E지능형 C360\u003C/b\u003E로 발전하는 것입니다.\u003C/p\u003E\n\u003Ch3\u003EC360 성숙도가 갖는 가치: 포괄형에서 지능형으로\u003C/h3\u003E\n\u003Cp\u003E성숙도 여정을 따라 발전을 하게 되면 각 단계별로 혁신적인 비즈니스 가치를 창출합니다.  포괄형 C360의 강력한 기능을 통해, 정형 데이터에 대한 완전하고 신뢰할 수 있는 뷰를 확보할 수 있습니다.  이를 통해 '감'에 의존하는 의사 결정을 넘어, 데이터 중심 마케팅과 개선된 운영 효율성을 통해 실질적인 결과를 이끌어낼 수 있습니다. \u003C/p\u003E\n\u003Cp\u003E이들 기업의 여정 가운데 포괄형 C360 스테이지에 도달하여 성과를 보여주고 있는 두 기업의 실제 성공 사례를 살펴보겠습니다.\u003C/p\u003E\n\u003Cp\u003E캐나다 풋볼 리그(CFL)는 \u003Ca href=\"https://www.snowflake.com/en/customers/all-customers/case-study/cfl/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake로 포괄형 C360을 구축하여\u003C/a\u003E 팬 1인 당 120개가 넘는 데이터 포인트를 통합했습니다.  이러한 통합 뷰를 기반으로 개인화된 콘텐츠를 제공함으로써 리그 전환율은 9배 가량 증가하고 마케팅 대상 팬들의 유지율은 3배 더 높아졌습니다.\n \u003C/p\u003E\n\u003Cp\u003EAutodesk는 \u003Ca href=\"https://www.snowflake.com/en/customers/all-customers/case-study/autodesk/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake로 C360 분석 플랫폼을 재구축하여\u003C/a\u003E 이전 데이터 레이크의 부담을 극복한 경우입니다. 새로운 기반은 데이터 수집 속도를 10배 높이고 비즈니스 전반에 걸쳐 셀프 서비스 분석을 지원하여 플랫폼 지원에 필요한 인력을 3배 가량 낮추었습니다.\u003C/p\u003E\n\u003Cp\u003E최전선에 있는 기업들 입장에서 고객의 과거 기록 뷰만으로는 충분하지 않을 수 있습니다.  앞으로 필요한 경쟁 우위는 포괄형에서 지능형으로 성숙도를 높이는 것, 즉 비정형 데이터로 기반을 강화하여 고객 행동 이면의 ‘이유’를 이해하는 데서 나옵니다.\u003C/p\u003E\n\u003Cp\u003E단순한 위험 경감 이상으로, 지능형 C360은 기업 차원에서 숨은 확장 수익을 발견하고 낭비되는 광고 지출을 줄이는 데 도움이 되는 새로운 차원의 선제적이고 예측적인 역량을 제공합니다.  예를 들어, 고객이 별점 5점 리뷰(정형 데이터)를 남겼지만, 리뷰 텍스트(비정형 데이터)에서는 특정 부분에 대한 아쉬움을 언급했다고 가정해 보겠습니다. 지능형 C360을 통해 이 강력한 구매 신호를 포착하면, 영업팀이 고객이 스스로 설명한 정확한 니즈를 해결해 줄 프리미엄 모듈의 데모를 완벽한 타이밍에 후속 조치할 수 있습니다.\u003C/p\u003E\n\u003Cp\u003E광고 지출 측면을 살펴볼까요. 제품을 방금 구매한 고객이 다음 날 고객 지원팀에 불만을 제기하기 위해 전화한 경우를 생각해 보겠습니다. 지능형 C360은 통화 녹취록에서 부정적인 감정을 파악하고 고객을 광고 캠페인에서 자동으로 제외시켜, ROAS를 즉각적으로 개선하고 취약해진 고객과의 관계로 인한 추가 피해를 방지할 수 있습니다.\u003C/p\u003E\n\u003Cp\u003E이러한 사례들은 지능형 C360을 통해, 조직 차원에서 고객 경험이 의미하는 바를 재고하도록 그 방식을 근본적으로 바꾼 몇 가지 예시에 불과합니다.\u003C/p\u003E\n\u003Ch3\u003ESnowflake AI 데이터 클라우드를 통한 미래 구축\u003C/h3\u003E\n\u003Cp\u003E정형 데이터를 처음으로 통합해 보든, 비정형 소스로 해당 데이터를 보강하든, Snowflake AI 데이터 클라우드는 단일하고 유연한 기반을 제공하여 전체 여정을 지원합니다. Snowflake AI 데이터 클라우드의 특징은 다음과 같습니다.\n\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cb\u003E편의성: \u003C/b\u003E정형 및 비정형의 모든 데이터를 단일 플랫폼에서 처리하여 더 나은 고객 인사이트 및 고객 경험 개발을 가속화합니다.\n\u003C/li\u003E\n\u003Cli\u003E\u003Cb\u003E연결성: \u003C/b\u003E비정형 데이터를 있는 그대로 연결하여 기존 C360을 보강함으로써, 비용이 많이 드는 새로운 데이터 파이프라인과 데이터 이동이 필요하지 않습니다.\u003C/li\u003E\n\u003Cli\u003E\u003Cb\u003E신뢰성:\u003C/b\u003E CRM 기록부터 통화 녹취록에 이르기까지 모든 데이터에 단일 통합 거버넌스 및 보안 모델을 적용하고, 신뢰할 수 있는 AI를 프로덕션 환경에 안정적으로 배포합니다.\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1345452980":{"id":"image-36ffb494fe","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--82ffbe8c-7ce4-4fc3-ba80-007c454125b2/customer-360-2.jpg?quality=85&preferwebp=true","lazyEnabled":true,"alt":"360-2","height":"841","width":"1729",":type":"snowflake-site/components/image"},"blog_text_1689123046":{"id":"blog-text-c640588a85","text":"\u003Cp\u003E\u003Csub\u003E자료 2: Snowflake의 지능형 Customer 360\u003C/sub\u003E\u003C/p\u003E\n\u003Ch3\u003E \u003C/h3\u003E\n\u003Ch3\u003E다음 단계를 향한 여정\u003C/h3\u003E\n\u003Cp\u003EC360 성숙도 곡선의 어느 위치에 있든, 올바른 데이터 파운데이션에서 그 여정은 시작됩니다. 이 기반은 당면한 과제를 해결하는 동시에 AI 기반의 미래로 가는 직접적인 경로를 제시해 줄 것입니다.\u003C/p\u003E\n\u003Cp\u003E마케팅 데이터 스택을 현대화하고 마테크를 재편하는 세 가지 요소에 대해 자세히 알아보려면, Snowflake의 새 보고서 \u003Ca href=\"https://www.snowflake.com/ko/the-modern-marketing-data-stack-report/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E최신 마케팅 데이터 스택\u003C/a\u003E을 읽어보세요. \u003C/p\u003E\n\u003Cp\u003E \u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","image","blog_text_1407379112","image_1345452980","blog_text_1689123046"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"premium_content_bann":"aem-GridColumn 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방법","showImage":true,"image":{"id":"image","src":"https://www.snowflake.com/content/snowflake-site/global/ko/blog/customer-360-playbook-ai-era/_jcr_content/root/responsivegrid/container_main_content/flexible_column_container/flexible_column_content_container_1/responsivegrid_premium_content_banner/premium_content_bann/image.coreimg.png/1762969486899/modern-marketing-data-stack.png","lazyEnabled":true,"alt":"MMDS","height":"434","uuid":"bf6aa4eb-59e1-4a24-aa3e-382cac3fbd37","width":"642",":type":"snowflake-site/components/image"},"buttons_container":{"layout":"SIMPLE","id":"container-d480a568c1",":type":"snowflake-site/components/button/buttons-container",":items":{"button":{"id":"button-ee683c5943","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/ko/the-modern-marketing-data-stack-report/?utm_cta=website-blog-customer-360-playbook-mmds"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"지금 다운로드하기"}},":itemsOrder":["button"]},":type":"snowflake-site/components/premium-content-banner"}},":itemsOrder":["premium_content_bann"],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"author_chip":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-bbd21664bd",":type":"snowflake-site/components/container","appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{"author_chip":{"id":"author-chip-7601e23d58","title":{"id":"title","type":"heading2","lines":["Learn more about the authors"],":type":"snowflake-site/components/title-v2"},"authors":[{"authorImage":{"id":"image-80359b4fd2","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--e8914c33-ec1d-40bd-86c8-d2fe3c507add/florian-delval.jpg?quality=85&preferwebp=true","lazyEnabled":true,"alt":"Headshot style photo of Florian 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