Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea os usar\u00e1? \u2014 Teamcore Blog<\/title>\r\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Montserrat:ital,wght@0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,400;1,700&family=Raleway:wght@300;400;500;600;700;800&display=swap\" rel=\"stylesheet\">\r\n<style>\r\n*, *::before, *::after { margin: 0; padding: 0; box-sizing: border-box; }\r\n\r\n:root {\r\n --navy: #02193a;\r\n --blue: #003670;\r\n --teal: #72B699;\r\n --teal-dark: #4a9478;\r\n --sky: #5D92AF;\r\n --amber: #f8b475;\r\n --red: #e86363;\r\n --off: #f5f7fb;\r\n --ink: #1c2638;\r\n --muted: #5a6680;\r\n --border: #dde4ee;\r\n --white: #ffffff;\r\n --font-head: 'Montserrat', 'Raleway', 'Source Sans Pro', Helvetica, Arial, sans-serif;\r\n --font-body: 'Raleway', 'Montserrat', 'Source Sans Pro', Helvetica, Arial, sans-serif;\r\n}\r\n\r\nbody {\r\n font-family: var(--font-body);\r\n background: var(--off);\r\n color: var(--ink);\r\n line-height: 1.75;\r\n overflow-x: hidden;\r\n}\r\n\r\n.reveal {\r\n opacity: 0;\r\n transform: translateY(40px);\r\n transition: opacity 0.7s cubic-bezier(0.22,1,0.36,1), transform 0.7s cubic-bezier(0.22,1,0.36,1);\r\n}\r\n.reveal.from-left { transform: translateX(-44px); }\r\n.reveal.from-right { transform: translateX(44px); }\r\n.reveal.scale-up { transform: translateY(20px) scale(0.96); }\r\n.reveal.is-visible { opacity: 1 !important; transform: none !important; }\r\n\r\n.stagger-group > * {\r\n opacity: 0;\r\n transform: translateY(28px);\r\n transition: opacity 0.55s cubic-bezier(0.22,1,0.36,1), transform 0.55s cubic-bezier(0.22,1,0.36,1);\r\n}\r\n.stagger-group.is-visible > *:nth-child(1){ opacity:1; transform:none; transition-delay:0s; }\r\n.stagger-group.is-visible > *:nth-child(2){ opacity:1; transform:none; transition-delay:0.11s; }\r\n.stagger-group.is-visible > *:nth-child(3){ opacity:1; transform:none; transition-delay:0.22s; }\r\n.stagger-group.is-visible > *:nth-child(4){ opacity:1; transform:none; transition-delay:0.33s; }\r\n\r\n.hero {\r\n background: linear-gradient(145deg, #01112a 0%, #003670 54%, #0a4f6a 100%);\r\n position: relative;\r\n overflow: hidden;\r\n min-height: 680px;\r\n display: flex;\r\n flex-direction: column;\r\n justify-content: flex-end;\r\n}\r\n.hero-orb1 {\r\n position: absolute; top: -120px; right: -70px;\r\n width: 560px; height: 560px;\r\n border-radius: 50%;\r\n background: radial-gradient(circle, rgba(114,182,153,0.16) 0%, transparent 68%);\r\n pointer-events: none;\r\n}\r\n.hero-orb2 {\r\n position: absolute; bottom: -90px; left: 8%;\r\n width: 340px; height: 340px;\r\n border-radius: 50%;\r\n background: radial-gradient(circle, rgba(93,146,175,0.14) 0%, transparent 70%);\r\n pointer-events: none;\r\n}\r\n.hero-lines {\r\n position: absolute; inset: 0;\r\n background: repeating-linear-gradient(-45deg, transparent, transparent 42px, rgba(255,255,255,0.014) 42px, rgba(255,255,255,0.014) 43px);\r\n pointer-events: none;\r\n}\r\n.hero-grid {\r\n position: absolute;\r\n inset: 0;\r\n opacity: 0.18;\r\n background-image: linear-gradient(rgba(255,255,255,0.08) 1px, transparent 1px), linear-gradient(90deg, rgba(255,255,255,0.08) 1px, transparent 1px);\r\n background-size: 80px 80px;\r\n mask-image: radial-gradient(circle at 75% 25%, black 0%, transparent 58%);\r\n}\r\n.hero-inner {\r\n position: relative; z-index: 2;\r\n padding: 96px clamp(56px, 7vw, 112px) 84px;\r\n max-width: 1280px;\r\n width: 100%;\r\n}\r\n.hero-eyebrow { display: flex; align-items: center; gap: 12px; margin-bottom: 28px; flex-wrap: wrap; }\r\n.hero-tag {\r\n display: inline-block;\r\n background: rgba(114,182,153,0.18);\r\n border: 1px solid rgba(114,182,153,0.38);\r\n color: var(--teal);\r\n font-family: var(--font-head);\r\n font-size: 10px; font-weight: 700;\r\n letter-spacing: 2.5px; text-transform: uppercase;\r\n padding: 5px 14px; border-radius: 20px;\r\n}\r\n.hero-date { font-size: 12px; color: rgba(255,255,255,0.35); letter-spacing: 0.4px; }\r\n.hero h1 {\r\n font-family: var(--font-head);\r\n font-size: clamp(42px, 5.2vw, 84px);\r\n font-weight: 800;\r\n color: #fff;\r\n line-height: 1.08;\r\n margin-bottom: 28px;\r\n max-width: 980px;\r\n}\r\n.hero h1 em { font-style: italic; color: var(--teal); font-weight: 700; }\r\n.hero-deck {\r\n font-size: clamp(19px, 1.45vw, 24px); font-weight: 300;\r\n color: rgba(255,255,255,0.68);\r\n max-width: 760px; line-height: 1.68;\r\n margin-bottom: 40px;\r\n}\r\n.hero-meta {\r\n display: flex; align-items: center; gap: 26px; flex-wrap: wrap;\r\n border-top: 1px solid rgba(255,255,255,0.09);\r\n padding-top: 24px;\r\n}\r\n.meta-pill { font-size: 12px; color: rgba(255,255,255,0.42); display: flex; align-items: center; gap: 7px; }\r\n.meta-dot { width: 4px; height: 4px; border-radius: 50%; background: var(--teal); }\r\n\r\n.hero-visual {\r\n position: absolute;\r\n right: clamp(48px, 7vw, 130px);\r\n bottom: 86px;\r\n width: min(460px, 32vw);\r\n opacity: 0.92;\r\n z-index: 1;\r\n}\r\n.hero-visual svg { width: 100%; height: auto; display: block; }\r\n\r\n.article {\r\n max-width: 1680px;\r\n margin: 0 auto;\r\n padding: 88px clamp(48px, 4.2vw, 80px) 120px;\r\n}\r\n\r\np {\r\n font-size: clamp(18px, 1.1vw, 21px); font-weight: 400;\r\n color: #2d3a52; margin-bottom: 22px; line-height: 1.85;\r\n}\r\nh2 {\r\n font-family: var(--font-head);\r\n font-size: clamp(28px, 2.4vw, 38px);\r\n font-weight: 700; color: var(--navy);\r\n line-height: 1.25; margin: 68px 0 18px;\r\n display: flex; align-items: center; gap: 12px;\r\n}\r\nh2 .h-icon {\r\n width: 44px; height: 44px; flex-shrink: 0;\r\n background: linear-gradient(135deg, #e4f0fa 0%, #d9f0e8 100%);\r\n border-radius: 9px;\r\n display: flex; align-items: center; justify-content: center;\r\n}\r\nh2 .h-icon svg { width: 22px; height: 22px; }\r\nh2:first-of-type { margin-top: 0; }\r\n\r\nh3 {\r\n font-family: var(--font-head);\r\n font-size: 20px; font-weight: 700;\r\n color: var(--blue);\r\n margin: 40px 0 10px;\r\n display: flex; align-items: center; gap: 10px;\r\n}\r\nh3 .h3-icon {\r\n width: 28px; height: 28px; flex-shrink: 0;\r\n background: linear-gradient(135deg, #ddeeff 0%, #d4f0e6 100%);\r\n border-radius: 7px;\r\n display: flex; align-items: center; justify-content: center;\r\n}\r\nh3 .h3-icon svg { width: 14px; height: 14px; }\r\n\r\n.opener {\r\n font-family: var(--font-head);\r\n font-size: clamp(26px, 2.2vw, 34px);\r\n font-weight: 700; font-style: italic;\r\n color: var(--blue); line-height: 1.4;\r\n border-left: 4px solid var(--teal);\r\n padding-left: 28px; margin-bottom: 52px;\r\n}\r\n\r\n.src {\r\n font-family: var(--font-head);\r\n font-size: 10px; font-weight: 600;\r\n letter-spacing: 1px; text-transform: uppercase;\r\n color: var(--sky); opacity: 0.9;\r\n border: 1px solid rgba(93,146,175,0.3);\r\n border-radius: 4px; padding: 2px 7px;\r\n margin-left: 6px; vertical-align: middle;\r\n white-space: nowrap;\r\n}\r\n\r\n.data-hero {\r\n margin: 56px 0;\r\n background: linear-gradient(135deg, #ffffff 0%, #ecf5fb 100%);\r\n border: 1px solid var(--border);\r\n border-radius: 22px;\r\n min-height: 370px;\r\n overflow: hidden;\r\n position: relative;\r\n display: grid;\r\n grid-template-columns: 1fr 1fr;\r\n}\r\n.data-hero-copy { padding: 42px 42px 38px; display: flex; flex-direction: column; justify-content: center; }\r\n.data-hero-copy .label {\r\n font-family: var(--font-head); font-size: 10px; font-weight: 800; letter-spacing: 2px;\r\n text-transform: uppercase; color: var(--teal-dark); margin-bottom: 14px;\r\n}\r\n.data-hero-copy h2 { display: block; margin: 0 0 14px; }\r\n.data-hero-copy p { font-size: 18px; color: var(--muted); margin-bottom: 0; }\r\n.data-hero-graphic {\r\n background: linear-gradient(145deg, rgba(2,25,58,0.98), rgba(0,54,112,0.96));\r\n position: relative;\r\n display: flex; align-items: center; justify-content: center;\r\n padding: 28px;\r\n}\r\n.data-hero-graphic svg { width: 100%; max-width: 330px; }\r\n\r\n.scene {\r\n background: linear-gradient(135deg, #02193a 0%, #003670 100%);\r\n border-radius: 18px;\r\n padding: 44px 48px;\r\n margin: 52px 0;\r\n position: relative; overflow: hidden;\r\n}\r\n.scene::after {\r\n content: '';\r\n position: absolute; top: -50px; right: -50px;\r\n width: 220px; height: 220px;\r\n border: 42px solid rgba(114,182,153,0.08);\r\n border-radius: 50%;\r\n}\r\n.scene p {\r\n color: rgba(255,255,255,0.8);\r\n font-size: 20px; margin-bottom: 0;\r\n position: relative; z-index: 1;\r\n}\r\n.scene p + p { margin-top: 16px; }\r\n.scene strong { color: #fff; font-weight: 600; }\r\n\r\n.stat-grid {\r\n display: grid;\r\n grid-template-columns: repeat(3, 1fr);\r\n gap: 22px; margin: 60px 0;\r\n}\r\n.stat-card {\r\n background: linear-gradient(160deg, #ffffff 0%, #f4f8fd 100%);\r\n border: 1px solid var(--border);\r\n border-radius: 16px;\r\n padding: 34px 30px;\r\n position: relative; overflow: hidden;\r\n}\r\n.stat-card::after { content: ''; position: absolute; top: 0; left: 0; right: 0; height: 3px; }\r\n.stat-card.c-teal::after { background: linear-gradient(90deg, var(--teal), #4ebf9a); }\r\n.stat-card.c-sky::after { background: linear-gradient(90deg, var(--sky), #3a7fa0); }\r\n.stat-card.c-amber::after { background: linear-gradient(90deg, var(--amber), #e89a4a); }\r\n.stat-card.c-navy::after { background: linear-gradient(90deg, var(--navy), var(--blue)); }\r\n.stat-num {\r\n font-family: var(--font-head);\r\n font-size: 48px; font-weight: 800;\r\n color: var(--navy); line-height: 1; margin-bottom: 10px;\r\n}\r\n.stat-num.up { color: var(--teal-dark); }\r\n.stat-num.down { color: var(--red); }\r\n.stat-label { font-size: 15px; color: var(--muted); line-height: 1.55; }\r\n\r\n.pullquote {\r\n border-left: 4px solid var(--teal);\r\n padding: 6px 0 6px 30px;\r\n margin: 52px 0;\r\n}\r\n.pullquote p {\r\n font-family: var(--font-head);\r\n font-size: 24px; font-weight: 600;\r\n font-style: italic; color: var(--blue);\r\n margin-bottom: 10px; line-height: 1.55;\r\n}\r\n.pullquote cite {\r\n font-family: var(--font-head); font-size: 12px; color: var(--teal-dark);\r\n font-style: normal; font-weight: 700; letter-spacing: 0.3px;\r\n}\r\n\r\n.divider {\r\n height: 1px;\r\n background: linear-gradient(90deg, transparent, var(--border), transparent);\r\n margin: 64px 0;\r\n}\r\n\r\n.module-grid {\r\n display: grid;\r\n grid-template-columns: 1fr 1fr;\r\n gap: 24px;\r\n margin: 46px 0;\r\n}\r\n.module-card {\r\n background: #fff;\r\n border: 1px solid var(--border);\r\n border-radius: 16px;\r\n padding: 34px;\r\n position: relative;\r\n overflow: hidden;\r\n}\r\n.module-card::before {\r\n content: '';\r\n position: absolute;\r\n width: 120px; height: 120px;\r\n right: -62px; top: -62px;\r\n border-radius: 50%;\r\n background: rgba(114,182,153,0.10);\r\n}\r\n.module-kicker {\r\n font-family: var(--font-head); font-size: 10px; font-weight: 800; letter-spacing: 1.8px;\r\n text-transform: uppercase; color: var(--teal-dark); margin-bottom: 10px;\r\n}\r\n.module-card h4 {\r\n font-family: var(--font-head); font-size: 22px; color: var(--navy); line-height: 1.3; margin-bottom: 10px;\r\n}\r\n.module-card p { font-size: 17px; color: var(--muted); line-height: 1.72; margin-bottom: 0; }\r\n\r\n.process {\r\n margin: 48px 0;\r\n border: 1px solid var(--border);\r\n border-radius: 18px;\r\n overflow: hidden;\r\n background: #fff;\r\n}\r\n.process-step {\r\n display: grid;\r\n grid-template-columns: 84px 1fr;\r\n gap: 22px;\r\n padding: 28px 30px;\r\n border-bottom: 1px solid var(--border);\r\n}\r\n.process-step:last-child { border-bottom: none; }\r\n.process-num {\r\n width: 52px; height: 52px;\r\n border-radius: 15px;\r\n background: linear-gradient(135deg, #02193a, #003670);\r\n color: var(--teal);\r\n font-family: var(--font-head);\r\n font-weight: 900;\r\n font-size: 22px;\r\n display: flex; align-items: center; justify-content: center;\r\n}\r\n.process-copy h4 {\r\n font-family: var(--font-head); color: var(--navy); font-size: 21px; margin-bottom: 6px;\r\n}\r\n.process-copy p { font-size: 17px; color: var(--muted); margin: 0; line-height: 1.72; }\r\n\r\n.comparison {\r\n display: grid;\r\n grid-template-columns: 1fr 1fr;\r\n gap: 24px;\r\n margin: 48px 0 26px;\r\n}\r\n.compare-card {\r\n border-radius: 18px;\r\n padding: 32px 30px;\r\n border: 1px solid var(--border);\r\n background: #fff;\r\n}\r\n.compare-card.dark {\r\n background: linear-gradient(135deg, #02193a 0%, #003670 100%);\r\n border-color: rgba(255,255,255,0.08);\r\n}\r\n.compare-label {\r\n font-family: var(--font-head); font-size: 10px; font-weight: 800; letter-spacing: 1.8px;\r\n text-transform: uppercase; color: var(--muted); margin-bottom: 12px;\r\n}\r\n.compare-card.dark .compare-label { color: var(--teal); }\r\n.compare-number {\r\n font-family: var(--font-head); font-size: 56px; line-height: 1; font-weight: 900; color: var(--red); margin-bottom: 10px;\r\n}\r\n.compare-card.dark .compare-number { color: var(--teal); }\r\n.compare-card p { font-size: 17px; color: var(--muted); margin: 0; line-height: 1.68; }\r\n.compare-card.dark p { color: rgba(255,255,255,0.72); }\r\n\r\n.big-number {\r\n display: flex; align-items: baseline; gap: 18px;\r\n background: linear-gradient(135deg, #02193a 0%, #003670 100%);\r\n border-radius: 16px;\r\n padding: 34px 40px; margin: 44px 0;\r\n}\r\n.big-n {\r\n font-family: var(--font-head); font-size: 86px; font-weight: 900;\r\n color: var(--teal); line-height: 1; flex-shrink: 0;\r\n}\r\n.big-n-text { font-size: 19px; color: rgba(255,255,255,0.74); line-height: 1.65; }\r\n.big-n-text strong { color: #fff; font-weight: 600; }\r\n\r\n.impact-grid {\r\n display: grid;\r\n grid-template-columns: repeat(4, 1fr);\r\n gap: 20px;\r\n margin: 48px 0;\r\n}\r\n.impact-card {\r\n background: linear-gradient(160deg, #ffffff 0%, #f4f8fd 100%);\r\n border: 1px solid var(--border);\r\n border-radius: 16px;\r\n padding: 24px 18px;\r\n}\r\n.impact-number {\r\n font-family: var(--font-head);\r\n font-size: 42px;\r\n font-weight: 900;\r\n color: var(--teal-dark);\r\n line-height: 1;\r\n margin-bottom: 12px;\r\n}\r\n.impact-card p { font-size: 15px; line-height: 1.5; color: var(--muted); margin: 0; }\r\n\r\n.insight {\r\n background: linear-gradient(135deg, #e6f2ff 0%, #ddf0ea 100%);\r\n border: 1px solid #bcd8f5;\r\n border-radius: 16px;\r\n padding: 36px 40px; margin: 48px 0;\r\n}\r\n.insight-label {\r\n font-family: var(--font-head);\r\n font-size: 10px; font-weight: 700;\r\n letter-spacing: 2px; text-transform: uppercase;\r\n color: var(--teal-dark); margin-bottom: 12px;\r\n display: flex; align-items: center; gap: 6px;\r\n}\r\n.insight p { font-size: 19px; color: #1b3050; margin-bottom: 0; }\r\n\r\n.cta-block {\r\n background: linear-gradient(145deg, #01112a 0%, #003670 55%, #0a4f6a 100%);\r\n border-radius: 22px;\r\n padding: 68px 54px;\r\n text-align: center; margin-top: 76px;\r\n position: relative; overflow: hidden;\r\n}\r\n.cta-block::before {\r\n content: ''; position: absolute; bottom: -60px; right: -60px;\r\n width: 300px; height: 300px;\r\n border: 52px solid rgba(114,182,153,0.07); border-radius: 50%;\r\n}\r\n.cta-block::after {\r\n content: ''; position: absolute; top: -40px; left: -40px;\r\n width: 190px; height: 190px;\r\n border: 36px solid rgba(93,146,175,0.06); border-radius: 50%;\r\n}\r\n.cta-block h2 {\r\n color: #fff; margin-top: 0; font-size: clamp(20px, 3vw, 30px);\r\n position: relative; z-index: 1; display: block;\r\n}\r\n.cta-block p {\r\n color: rgba(255,255,255,0.62);\r\n max-width: 500px; margin: 0 auto 32px;\r\n font-size: 18px; position: relative; z-index: 1;\r\n}\r\n.cta-btn {\r\n display: inline-block;\r\n background: linear-gradient(135deg, #72B699 0%, #4a9478 100%);\r\n color: var(--navy);\r\n font-family: var(--font-head);\r\n font-size: 15px; font-weight: 700;\r\n padding: 16px 46px; border-radius: 40px;\r\n text-decoration: none; letter-spacing: 0.3px;\r\n position: relative; z-index: 1;\r\n transition: transform 0.18s, box-shadow 0.18s;\r\n box-shadow: 0 6px 24px rgba(72,180,150,0.3);\r\n}\r\n.cta-btn:hover { transform: translateY(-3px); box-shadow: 0 10px 32px rgba(72,180,150,0.4); }\r\n\r\n\r\n@media (min-width: 1180px) {\r\n .hero { min-height: 760px; }\r\n\r\n \/* Desktop amplio: el hero se mantiene, pero el cuerpo usa mucho m\u00e1s ancho \u00fatil. *\/\r\n .article {\r\n max-width: 1680px;\r\n padding-left: clamp(56px, 4vw, 88px);\r\n padding-right: clamp(56px, 4vw, 88px);\r\n }\r\n\r\n .article > p,\r\n .article > h2,\r\n .article > h3,\r\n .article > .opener,\r\n .article > .pullquote,\r\n .article > .scene,\r\n .article > .insight {\r\n max-width: 1320px;\r\n }\r\n\r\n .article > p {\r\n font-size: clamp(20px, 1.15vw, 23px);\r\n line-height: 1.82;\r\n }\r\n\r\n .article > .opener {\r\n max-width: 1400px;\r\n }\r\n\r\n .article > .stat-grid,\r\n .article > .data-hero,\r\n .article > .module-grid,\r\n .article > .process,\r\n .article > .comparison,\r\n .article > .big-number,\r\n .article > .impact-grid,\r\n .article > .cta-block,\r\n .article > .divider {\r\n width: 100%;\r\n max-width: none;\r\n }\r\n\r\n .data-hero {\r\n grid-template-columns: 1.18fr 0.82fr;\r\n min-height: 430px;\r\n }\r\n .data-hero-copy { padding: 56px 64px; }\r\n .data-hero-copy p { font-size: 20px; line-height: 1.75; }\r\n .process-step { grid-template-columns: 104px 1fr; padding: 34px 44px; }\r\n .process-step p { font-size: 18px; }\r\n .process-num { width: 62px; height: 62px; font-size: 26px; }\r\n}\r\n\r\n@media (min-width: 1600px) {\r\n .article {\r\n max-width: 1780px;\r\n padding-left: 64px;\r\n padding-right: 64px;\r\n }\r\n\r\n .article > p,\r\n .article > h2,\r\n .article > h3,\r\n .article > .opener,\r\n .article > .pullquote,\r\n .article > .scene,\r\n .article > .insight {\r\n max-width: 1460px;\r\n }\r\n}\r\n\r\n@media (max-width: 860px) {\r\n .hero-visual { opacity: 0.25; right: -40px; width: 420px; }\r\n .impact-grid { grid-template-columns: 1fr 1fr; }\r\n}\r\n@media (max-width: 680px) {\r\n .hero h1 { font-size: clamp(34px, 11vw, 46px); }\r\n .hero-deck { font-size: 17px; }\r\n p { font-size: 17px; }\r\n h2 { font-size: clamp(22px, 7vw, 29px); }\r\n .hero-inner { padding: 60px 24px 50px; }\r\n .article { max-width: 100%; padding: 44px 20px 72px; }\r\n .stat-grid, .module-grid, .comparison, .data-hero { grid-template-columns: 1fr; }\r\n .impact-grid { grid-template-columns: 1fr 1fr; }\r\n .scene { padding: 30px 28px; }\r\n .cta-block { padding: 44px 28px; }\r\n .big-number { flex-direction: column; gap: 4px; }\r\n .big-n { font-size: 50px; }\r\n .process-step { grid-template-columns: 1fr; gap: 12px; padding: 24px; }\r\n .data-hero-graphic { min-height: 230px; }\r\n}\r\n@media (max-width: 430px) {\r\n .impact-grid { grid-template-columns: 1fr; }\r\n}\r\n<\/style>\r\n<\/head>\r\n<body>\r\n\r\n<header class=\"hero\">\r\n <div class=\"hero-orb1\"><\/div>\r\n <div class=\"hero-orb2\"><\/div>\r\n <div class=\"hero-lines\"><\/div>\r\n <div class=\"hero-grid\"><\/div>\r\n <div class=\"hero-visual\" aria-hidden=\"true\">\r\n <svg viewbox=\"0 0 420 420\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\r\n <rect x=\"62\" y=\"80\" width=\"296\" height=\"230\" rx=\"24\" fill=\"rgba(255,255,255,0.08)\" stroke=\"rgba(255,255,255,0.22)\"\/>\r\n <rect x=\"94\" y=\"118\" width=\"90\" height=\"12\" rx=\"6\" fill=\"#72B699\"\/>\r\n <rect x=\"94\" y=\"152\" width=\"230\" height=\"10\" rx=\"5\" fill=\"rgba(255,255,255,0.34)\"\/>\r\n <rect x=\"94\" y=\"180\" width=\"178\" height=\"10\" rx=\"5\" fill=\"rgba(255,255,255,0.24)\"\/>\r\n <rect x=\"94\" y=\"224\" width=\"48\" height=\"48\" rx=\"12\" fill=\"rgba(114,182,153,0.20)\"\/>\r\n <rect x=\"158\" y=\"224\" width=\"48\" height=\"48\" rx=\"12\" fill=\"rgba(93,146,175,0.22)\"\/>\r\n <rect x=\"222\" y=\"224\" width=\"48\" height=\"48\" rx=\"12\" fill=\"rgba(248,180,117,0.20)\"\/>\r\n <path d=\"M118 248h128\" stroke=\"#72B699\" stroke-width=\"4\" stroke-linecap=\"round\"\/>\r\n <circle cx=\"300\" cy=\"78\" r=\"34\" fill=\"rgba(114,182,153,0.22)\"\/>\r\n <path d=\"M286 78l10 10 20-22\" stroke=\"#72B699\" stroke-width=\"7\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\r\n <circle cx=\"82\" cy=\"318\" r=\"30\" fill=\"rgba(93,146,175,0.22)\"\/>\r\n <path d=\"M70 318h24M82 306v24\" stroke=\"#5D92AF\" stroke-width=\"6\" stroke-linecap=\"round\"\/>\r\n <\/svg>\r\n <\/div>\r\n <div class=\"hero-inner\">\r\n <div class=\"hero-eyebrow\">\r\n <span class=\"hero-tag\">Execu\u00e7\u00e3o no Varejo \u00b7 Extra\u00e7\u00e3o de Dados<\/span>\r\n <span class=\"hero-date\">Teamcore Editorial \u00b7 Consumo massivo<\/span>\r\n <\/div>\r\n <h1>Seus dados de campo j\u00e1 est\u00e3o prontos.<br><em>Quando voc\u00ea os usar\u00e1?<\/em><\/h1>\r\n <p class=\"hero-deck\">A execu\u00e7\u00e3o no ponto de venda gera dados todos os dias. O problema \u00e9 que muitas opera\u00e7\u00f5es ainda os recebem tarde, incompletos ou desorganizados demais para transform\u00e1-los em decis\u00f5es.<\/p>\r\n <div class=\"hero-meta\">\r\n <span class=\"meta-pill\"><span class=\"meta-dot\"><\/span>7 min de leitura<\/span>\r\n <span class=\"meta-pill\"><span class=\"meta-dot\"><\/span>Dados e execu\u00e7\u00e3o comercial<\/span>\r\n <span class=\"meta-pill\"><span class=\"meta-dot\"><\/span>CPG \u00b7 Equipes de Campo \u00b7 Varejo<\/span>\r\n <\/div>\r\n <\/div>\r\n<\/header>\r\n\r\n<article class=\"article\">\r\n\r\n <div class=\"data-hero reveal scale-up\">\r\n <div class=\"data-hero-copy\">\r\n <div class=\"label\">O problema n\u00e3o \u00e9 falta de dados<\/div>\r\n <h2>\u00c9 a velocidade com que chegam a quem deve decidir.<\/h2>\r\n <p>Apenas o 12% dos varejistas transforma dados em a\u00e7\u00f5es preventivas. O restante, 88%, continua operando com visibilidade parcial: identifica o problema quando a venda j\u00e1 foi perdida.<\/p>\r\n <\/div>\r\n <div class=\"data-hero-graphic\" aria-hidden=\"true\">\r\n <svg viewbox=\"0 0 360 260\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\r\n <rect x=\"24\" y=\"30\" width=\"312\" height=\"198\" rx=\"18\" fill=\"rgba(255,255,255,0.08)\" stroke=\"rgba(255,255,255,0.18)\"\/>\r\n <rect x=\"52\" y=\"58\" width=\"102\" height=\"12\" rx=\"6\" fill=\"#72B699\"\/>\r\n <rect x=\"52\" y=\"92\" width=\"256\" height=\"8\" rx=\"4\" fill=\"rgba(255,255,255,0.32)\"\/>\r\n <rect x=\"52\" y=\"114\" width=\"218\" height=\"8\" rx=\"4\" fill=\"rgba(255,255,255,0.22)\"\/>\r\n <rect x=\"52\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(114,182,153,0.20)\"\/>\r\n <rect x=\"112\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(93,146,175,0.22)\"\/>\r\n <rect x=\"172\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(248,180,117,0.20)\"\/>\r\n <rect x=\"232\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(255,255,255,0.12)\"\/>\r\n <path d=\"M68 172l10 10 20-26\" stroke=\"#72B699\" stroke-width=\"5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\r\n <circle cx=\"135\" cy=\"173\" r=\"11\" stroke=\"#5D92AF\" stroke-width=\"5\"\/>\r\n <path d=\"M190 162v22M179 173h22\" stroke=\"#F8B475\" stroke-width=\"5\" stroke-linecap=\"round\"\/>\r\n <path d=\"M240 162l24 24M264 162l-24 24\" stroke=\"rgba(255,255,255,0.55)\" stroke-width=\"4\" stroke-linecap=\"round\"\/>\r\n <\/svg>\r\n <\/div>\r\n <\/div>\r\n\r\n <p class=\"opener reveal\">Suas equipes j\u00e1 est\u00e3o gerando a informa\u00e7\u00e3o. O que falta \u00e9 convert\u00ea-la em a\u00e7\u00e3o antes que o ponto de venda pague a fatura.<\/p>\r\n\r\n <div class=\"stat-grid stagger-group\">\r\n <div class=\"stat-card c-teal\">\r\n <div class=\"stat-num\">12%<\/div>\r\n <div class=\"stat-label\">dos varejistas transforma dados em a\u00e7\u00f5es preventivas.<\/div>\r\n <\/div>\r\n <div class=\"stat-card c-sky\">\r\n <div class=\"stat-num down\">7h+<\/div>\r\n <div class=\"stat-label\">se perdem por cadeia cada semana gerenciando, limpando e homologando dados.<\/div>\r\n <\/div>\r\n <div class=\"stat-card c-amber\">\r\n <div class=\"stat-num up\">10x<\/div>\r\n <div class=\"stat-label\">ROI m\u00e9dio quando o gargalo operacional \u00e9 eliminado.<\/div>\r\n <\/div>\r\n <\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M10.29 3.86L1.82 18a2 2 0 001.71 3h16.94a2 2 0 001.71-3L13.71 3.86a2 2 0 00-3.42 0z\"\/><line x1=\"12\" y1=\"9\" x2=\"12\" y2=\"13\"\/><line x1=\"12\" y1=\"17\" x2=\"12.01\" y2=\"17\"\/><\/svg>\r\n <\/span>\r\n O problema silencioso que destr\u00f3i resultados\r\n <\/h2>\r\n\r\n <div class=\"scene reveal\">\r\n <p>S\u00e3o 8h00. Seu produto principal esgotou ontem em 15 pontos de venda fundamentais. Suas equipes est\u00e3o revisando rotas, a concorr\u00eancia est\u00e1 repostando seus espa\u00e7os e os consumidores est\u00e3o escolhendo outras marcas.<\/p>\r\n <p><strong>Para quando voc\u00ea souber, j\u00e1 \u00e9 tarde demais.<\/strong><\/p>\r\n <\/div>\r\n\r\n <p class=\"reveal\">Esta cena n\u00e3o \u00e9 uma exce\u00e7\u00e3o: \u00e9 parte do dia a dia em muitas opera\u00e7\u00f5es de bens de consumo. As informa\u00e7\u00f5es sobre o que acontece na g\u00f4ndola chegam fragmentadas, tarde e com ru\u00eddo demais para agir. As equipes comerciais passam horas baixando arquivos, limpando bases, cruzando formatos e homologando dados antes de chegar \u00e0 primeira an\u00e1lise real.<\/p>\r\n\r\n <p class=\"reveal\">O custo n\u00e3o est\u00e1 apenas no tempo perdido. Est\u00e1 nos esgotados que s\u00e3o detectados tarde, nas promo\u00e7\u00f5es que ningu\u00e9m corrige a tempo, nas exibi\u00e7\u00f5es que s\u00e3o auditadas quando a campanha j\u00e1 terminou e nos espa\u00e7os que a concorr\u00eancia ocupa enquanto a equipe ainda tenta organizar a informa\u00e7\u00e3o.<\/p>\r\n\r\n <div class=\"pullquote reveal from-left\">\r\n <p>\u201cA diferen\u00e7a n\u00e3o foi que os problemas desapareceram. Foi que a equipe os viu a tempo de fazer algo a respeito.\u201d<\/p>\r\n <cite>\u2014 Caso de sucesso Teamcore \u00b7 Higiene & Beleza \u00b7 Peru 2025<\/cite>\r\n <\/div>\r\n\r\n <p class=\"reveal\">O gargalo n\u00e3o est\u00e1 na qualidade dos seus equipamentos. Est\u00e1 na dist\u00e2ncia entre os dados gerados em campo e as pessoas que precisam agir sobre eles. O Teamcore Data Extraction existe para eliminar essa dist\u00e2ncia.<\/p>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M21 16V8a2 2 0 00-1-1.73l-7-4a2 2 0 00-2 0l-7 4A2 2 0 003 8v8a2 2 0 001 1.73l7 4a2 2 0 002 0l7-4A2 2 0 0021 16z\"\/><polyline points=\"3.27 6.96 12 12.01 20.73 6.96\"\/><line x1=\"12\" y1=\"22.08\" x2=\"12\" y2=\"12\"\/><\/svg>\r\n <\/span>\r\n O que \u00e9 o Teamcore Data Extraction\r\n <\/h2>\r\n\r\n <p class=\"reveal\">Data Extraction \u00e9 a camada de intelig\u00eancia operacional da plataforma Teamcore que transforma tudo o que acontece no ponto de venda \u2014 visitas, tarefas de execu\u00e7\u00e3o, evid\u00eancias fotogr\u00e1ficas, respostas de campo \u2014 em dados estruturados, baixadores e acion\u00e1veis em tempo real.<\/p>\r\n\r\n <p class=\"reveal\">N\u00e3o \u00e9 um simples exportador de relat\u00f3rios. Funciona como um motor de convers\u00e3o: ele pega a execu\u00e7\u00e3o dispersa de milhares de promotores e supervisores, e a transforma em uma planilha de dados padronizada, filtr\u00e1vel e pronta para a an\u00e1lise estrat\u00e9gica.<\/p>\r\n\r\n <div class=\"module-grid stagger-group\">\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">M\u00f3dulo atual<\/div>\r\n <h4>Baixador Standard de KPIs<\/h4>\r\n <p>Sell-out, estoques e m\u00e9tricas de disponibilidade historizados. At\u00e9 2 anos de dados mais o per\u00edodo atual em uma \u00fanica consulta parametrizada.<\/p>\r\n <\/div>\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">M\u00f3dulo atual<\/div>\r\n <h4>Descarregador de Execu\u00e7\u00e3o<\/h4>\r\n <p>Planilha completa de respostas de campo: tipo de tarefa, usu\u00e1rio, loja, produto at\u00e9 o n\u00edvel SKU, intervalo de tempo e links para evid\u00eancias fotogr\u00e1ficas.<\/p>\r\n <\/div>\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">M\u00f3dulo atual<\/div>\r\n <h4>Baixador de Fotografias<\/h4>\r\n <p>Download em PDF com filtros avan\u00e7ados. Auditoria visual do estado real da g\u00f4ndola sem depender de relat\u00f3rios manuais.<\/p>\r\n <\/div>\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">Em desenvolvimento<\/div>\r\n <h4>Smart Downloader<\/h4>\r\n <p>A pr\u00f3xima evolu\u00e7\u00e3o: KPIs inteligentes com IA incorporada para priorizar automaticamente os alertas com maior impacto nas vendas.<\/p>\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><polyline points=\"22 12 18 12 15 21 9 3 6 12 2 12\"\/><\/svg>\r\n <\/span>\r\n Como funciona: do campo \u00e0 decis\u00e3o\r\n <\/h2>\r\n\r\n <p class=\"reveal\">A promessa \u00e9 simples: que o analista comece a gerar insights desde o minuto um, e n\u00e3o a partir da hora sete.<\/p>\r\n\r\n <div class=\"process reveal scale-up\">\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">1<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Execu\u00e7\u00e3o em App Mobile<\/h4>\r\n <p>As equipes de campo concluem tarefas de *facing*, exposi\u00e7\u00e3o e promo\u00e7\u00e3o pelo aplicativo. Cada resposta \u00e9 sincronizada automaticamente ao fazer *check-out*, incluindo evid\u00eancias fotogr\u00e1ficas georreferenciadas.<\/p>\r\n <\/div>\r\n <\/div>\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">2<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Processamento no Datapipe<\/h4>\r\n <p>O motor de dados da Teamcore normaliza, enriquece e estrutura a informa\u00e7\u00e3o em tempo real, cruzando dados de execu\u00e7\u00e3o com sell-out, estoques e metas comerciais.<\/p>\r\n <\/div>\r\n <\/div>\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">3<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Parametriza\u00e7\u00e3o da consulta<\/h4>\r\n <p>A partir da plataforma web, o analista configura o seu download: tipo de tarefa, atributos de usu\u00e1rio, atributos de loja, produto at\u00e9 o n\u00edvel SKU e intervalo de tempo exato.<\/p>\r\n <\/div>\r\n <\/div>\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">4<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Download pronto para an\u00e1lise<\/h4>\r\n <p>A planilha de dados chega limpa, homologada e estruturada. Zero trabalho de prepara\u00e7\u00e3o. A equipe pode passar direto da evid\u00eancia \u00e0 a\u00e7\u00e3o.<\/p>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><polyline points=\"12 6 12 12 16 14\"\/><\/svg>\r\n <\/span>\r\n O custo real de n\u00e3o ter esses dados a tempo\r\n <\/h2>\r\n\r\n <p class=\"reveal\">Uma redu\u00e7\u00e3o de 1% na disponibilidade nas prateleiras pode representar milh\u00f5es em receita perdida por ano. Mas o preju\u00edzo n\u00e3o \u00e9 apenas econ\u00f4mico: cada dia sem visibilidade leva a equipe a agir de forma reativa, em vez de preventiva.<\/p>\r\n\r\n <div class=\"comparison reveal\">\r\n <div class=\"compare-card\">\r\n <div class=\"compare-label\">Sem automa\u00e7\u00e3o<\/div>\r\n <div class=\"compare-number\">7h 10m<\/div>\r\n <p>por semana apenas em gerenciamento, limpeza e homologa\u00e7\u00e3o de dados.<\/p>\r\n <\/div>\r\n <div class=\"compare-card dark\">\r\n <div class=\"compare-label\">Com a Teamcore<\/div>\r\n <div class=\"compare-number\">26m<\/div>\r\n <p>por cadeia toda semana. A diferen\u00e7a n\u00e3o est\u00e1 em fazer mais relat\u00f3rios; est\u00e1 em recuperar tempo para decidir.<\/p>\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"big-number reveal scale-up\">\r\n <div class=\"big-n\">93%<\/div>\r\n <div class=\"big-n-text\">\r\n <strong>de redu\u00e7\u00e3o no tempo de gest\u00e3o de dados.<\/strong> Em uma opera\u00e7\u00e3o com 9 redes, isso equivale a 3.150 horas recuperadas por ano para an\u00e1lise, prioriza\u00e7\u00e3o e a\u00e7\u00e3o no ponto de venda.\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"insight reveal\">\r\n <div class=\"insight-label\">\r\n <svg width=\"14\" height=\"14\" viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.2\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><line x1=\"12\" y1=\"8\" x2=\"12\" y2=\"12\"\/><line x1=\"12\" y1=\"16\" x2=\"12.01\" y2=\"16\"\/><\/svg>\r\n O sinal de fundo\r\n <\/div>\r\n <p>Quando a informa\u00e7\u00e3o chega limpa e a tempo, muda a conversa: a equipe deixa de perguntar \u201co que aconteceu\u201d e come\u00e7a a decidir \u201co que fazemos agora\u201d. Essa diferen\u00e7a separa as opera\u00e7\u00f5es que reagem daquelas que previnem.<\/p>\r\n <\/div>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><line x1=\"18\" y1=\"20\" x2=\"18\" y2=\"10\"\/><line x1=\"12\" y1=\"20\" x2=\"12\" y2=\"4\"\/><line x1=\"6\" y1=\"20\" x2=\"6\" y2=\"14\"\/><\/svg>\r\n <\/span>\r\n O impacto global da Teamcore em n\u00fameros\r\n <\/h2>\r\n\r\n <p class=\"reveal\">A visibilidade operativa n\u00e3o apenas organiza a informa\u00e7\u00e3o. Ela tamb\u00e9m melhora a capacidade de recuperar vendas, sustentar a disponibilidade e resolver incid\u00eancias antes que escalem.<\/p>\r\n\r\n <div class=\"impact-grid stagger-group\">\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">+75%<\/div>\r\n <p>m\u00e9dia em vendas recuperadas com visibilidade operacional em tempo real.<\/p>\r\n <\/div>\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">6\u20139%<\/div>\r\n <p>de melhoria na disponibilidade de produtos na g\u00f4ndola.<\/p>\r\n <\/div>\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">\u221211,51 TP3T<\/div>\r\n <p>no tempo de resolu\u00e7\u00e3o de incidentes no ponto de venda.<\/p>\r\n <\/div>\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">+23%<\/div>\r\n <p>de otimiza\u00e7\u00e3o do tempo da equipe no ponto de venda.<\/p>\r\n <\/div>\r\n <\/div>\r\n\r\n <p class=\"reveal\">Para uma opera\u00e7\u00e3o comercial, esses n\u00fameros significam menos tempo perdido em tarefas repetitivas e mais capacidade para agir onde a venda acontece: o ponto de venda, a g\u00f4ndola, a exposi\u00e7\u00e3o, o invent\u00e1rio e a visita da equipe de campo.<\/p>\r\n\r\n <p class=\"reveal\">Os dados j\u00e1 est\u00e3o a\u00ed. Est\u00e3o em cada visita, cada fotografia, cada tarefa conclu\u00edda, cada check-out, cada SKU com ruptura, cada evid\u00eancia que a equipe levanta em campo. A diferen\u00e7a est\u00e1 em quanto tempo demoram para se transformar em uma decis\u00e3o.<\/p>\r\n\r\n <div class=\"cta-block reveal scale-up\">\r\n <h2>Pronto para usar seus dados de campo a tempo?<\/h2>\r\n <p>Saiba como o Teamcore Data Extraction transforma a execu\u00e7\u00e3o em dados limpos, estruturados e acion\u00e1veis para as suas equipes comerciais.<\/p>\r\n <a href=\"https:\/\/teamcore.com\/pt\/contato\/\" class=\"cta-btn\">Falar com um especialista \u2192<\/a>\r\n <\/div>\r\n\r\n<\/article>\r\n\r\n<script>\r\n(function(){\r\n var io = new IntersectionObserver(function(entries){\r\n entries.forEach(function(e){\r\n if(e.isIntersecting){\r\n e.target.classList.add('is-visible');\r\n io.unobserve(e.target);\r\n }\r\n });\r\n },{threshold:0.1, rootMargin:'0px 0px -40px 0px'});\r\n document.querySelectorAll('.reveal,.stagger-group').forEach(function(el){ io.observe(el); });\r\n})();\r\n<\/script>\r\n\r\n<\/body>\r\n<\/html>\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div 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class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/el-torneo-empieza-tu-gondola-tambien-esta-jugando\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/friends-toasting-with-beer-watching-soccer-match-i-2026-03-24-12-58-09-utc-768x512.jpg\" alt=\"Jovem grupo de amigos assistindo esporte na televis\u00e3o\" width=\"768\" height=\"512\" title=\"Jovem grupo de amigos assistindo esporte na televis\u00e3o\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/el-torneo-empieza-tu-gondola-tambien-esta-jugando\/\"> <div class=\"uc_post_title\">O torneio come\u00e7ou. A sua g\u00f4ndola tamb\u00e9m est\u00e1 jogando.<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 25\/06\/2026<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >Temporada de futebol e a sua g\u00f4ndola \u2014 Teamcore Blog\n\n\n\n\n\n\n\n Retail & CPG \u00b7 Tend\u00eancias...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/el-torneo-empieza-tu-gondola-tambien-esta-jugando\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n<div class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-768x511.jpg\" alt=\"Cliente abrindo a porta da geladeira no supermercado, escolhendo mantimentos, comida saud\u00e1vel, conceito de compras\" width=\"768\" height=\"511\" title=\"Cliente abrindo a porta da geladeira no supermercado, escolhendo mantimentos, comida saud\u00e1vel, conceito de compras\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/\"> <div class=\"uc_post_title\">Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea os usar\u00e1?<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 08\/06\/2026<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea os usar\u00e1? \u2014 Teamcore Blog...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n<div class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/como-el-mundial-2026-esta-cambiando-la-ejecucion-en-retail-en-latam\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/04\/3-claves-para-entender-el-comportamiento-de-compra-del-consumidor-en-el-Canal-Tradicional-1-768x512.webp\" alt=\"3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional (1)\" width=\"768\" height=\"512\" title=\"3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional (1)\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/como-el-mundial-2026-esta-cambiando-la-ejecucion-en-retail-en-latam\/\"> <div class=\"uc_post_title\">Como o Torneo 2026 est\u00e1 mudando a execu\u00e7\u00e3o no varejo na Am\u00e9rica Latina<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 24\/04\/2026<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >Como o Grande Torneio de 2026 est\u00e1 mudando a execu\u00e7\u00e3o no varejo na Am\u00e9rica Latina\n \n Inscreva-se\n\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\nabril...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/como-el-mundial-2026-esta-cambiando-la-ejecucion-en-retail-en-latam\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n<div class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/insights-propios-vs-estudios-externos-dos-fuentes-una-sola-decision\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/04\/Insights-propios-vs-estudios-externos-768x512.webp\" alt=\"Insights pr\u00f3prios vs. estudos externos\" width=\"768\" height=\"512\" title=\"Insights pr\u00f3prios vs. estudos externos\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div 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<\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/3-claves-para-entender-el-comportamiento-de-compra-del-consumidor-en-el-canal-tradicional\/\"> <div class=\"uc_post_title\">3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 14\/03\/2025<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional\nA companhia...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/3-claves-para-entender-el-comportamiento-de-compra-del-consumidor-en-el-canal-tradicional\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n\n <\/div>\t\n<\/div>\n\n\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea vai us\u00e1-los? \u2014 Blog da Teamcore: Execu\u00e7\u00e3o no Varejo \u00b7 Extra\u00e7\u00e3o de Dados \u00b7 Editorial da Teamcore \u00b7 Consumo de massa Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea vai us\u00e1-los? A execu\u00e7\u00e3o no ponto de venda gera dados todos os dias. O problema \u00e9 que muitas opera\u00e7\u00f5es ainda os recebem tarde, incompletos ou desorganizados demais para serem transformados em decis\u00f5es. 7 min de leitura Dados e execu\u00e7\u00e3o comercial CPG \u00b7 Equipes de campo \u00b7 Varejo O problema n\u00e3o \u00e9 a falta de dados. \u00c9 a velocidade com que eles chegam at\u00e9 quem deve decidir. Apenas 12% dos varejistas transformam dados em a\u00e7\u00f5es preventivas. Os 88% restantes continuam operando com visibilidade parcial: identificam o problema quando a venda j\u00e1 foi perdida. Suas equipes j\u00e1 est\u00e3o gerando as informa\u00e7\u00f5es. O que falta \u00e9 transform\u00e1-la em a\u00e7\u00e3o antes que o ponto de venda cobre a conta. 12% dos varejistas transformam dados em a\u00e7\u00f5es preventivas. Mais de 7h s\u00e3o perdidas por rede a cada semana gerenciando, limpando e padronizando dados. ROI m\u00e9dio 10x maior quando o gargalo operacional \u00e9 eliminado. O problema silencioso que destr\u00f3i resultados S\u00e3o 8h da manh\u00e3. Seu produto estrela esgotou ontem em 15 pontos de venda importantes. Suas equipes est\u00e3o revisando rotas, a concorr\u00eancia est\u00e1 reabastecendo suas prateleiras e os consumidores est\u00e3o escolhendo outras marcas. Quando voc\u00ea descobre, j\u00e1 \u00e9 tarde demais. Essa cena n\u00e3o \u00e9 uma exce\u00e7\u00e3o: faz parte do dia a dia em muitas opera\u00e7\u00f5es de consumo de massa. As informa\u00e7\u00f5es sobre o que ocorre nas prateleiras chegam fragmentadas, atrasadas e com ru\u00eddo demais para que se possa agir. As equipes comerciais passam horas baixando arquivos, limpando bancos de dados, cruzando formatos e padronizando dados antes de chegar \u00e0 primeira an\u00e1lise real. O custo n\u00e3o est\u00e1 apenas no tempo perdido. Est\u00e1 nos produtos esgotados que s\u00e3o detectados tarde demais, nas promo\u00e7\u00f5es que ningu\u00e9m corrige a tempo, nas exposi\u00e7\u00f5es que s\u00e3o auditadas quando a campanha j\u00e1 terminou e nos espa\u00e7os que a concorr\u00eancia ocupa enquanto a equipe ainda tenta organizar as informa\u00e7\u00f5es. \u201cA diferen\u00e7a n\u00e3o foi que os problemas desapareceram. Foi que a equipe os identificou a tempo de fazer algo a respeito.\u201d \u2014 Caso de sucesso Teamcore \u00b7 Higiene e Beleza \u00b7 Peru 2025 O gargalo n\u00e3o est\u00e1 na qualidade de suas equipes. Est\u00e1 na dist\u00e2ncia entre os dados gerados em campo e as pessoas que precisam agir com base neles. O Teamcore Data Extraction existe para eliminar essa dist\u00e2ncia. O que \u00e9 o Teamcore Data Extraction O Data Extraction \u00e9 a camada de intelig\u00eancia operacional da plataforma Teamcore que transforma tudo o que acontece no ponto de venda \u2014 visitas, tarefas de execu\u00e7\u00e3o, evid\u00eancias fotogr\u00e1ficas, respostas de campo \u2014 em dados estruturados, baix\u00e1veis e acion\u00e1veis em tempo real. N\u00e3o \u00e9 um simples exportador de relat\u00f3rios. Funciona como um mecanismo de convers\u00e3o: pega a execu\u00e7\u00e3o dispersa de milhares de profissionais de merchandising e supervisores e a transforma em uma planilha de dados padronizada, filtr\u00e1vel e pronta para an\u00e1lise estrat\u00e9gica. M\u00f3dulo atual: Downloader Padr\u00e3o de KPIs de sell-out, estoques e m\u00e9tricas de disponibilidade hist\u00f3ricas. At\u00e9 2 anos de dados mais o per\u00edodo atual em uma \u00fanica consulta parametrizada. M\u00f3dulo atual: Downloader de Execu\u00e7\u00e3o. Planilha completa de respostas de campo: tipo de tarefa, usu\u00e1rio, loja, produto at\u00e9 o n\u00edvel de SKU, intervalo de tempo e links para evid\u00eancias fotogr\u00e1ficas. M\u00f3dulo atual: Downloader de Fotos \u2013 Download em PDF com filtros avan\u00e7ados. Auditoria visual do estado real da prateleira, sem depender de relat\u00f3rios manuais. Em desenvolvimento: Downloader Smart \u2013 A pr\u00f3xima evolu\u00e7\u00e3o: KPIs inteligentes com IA incorporada para priorizar automaticamente os alertas com maior impacto nas vendas. Como funciona: do campo \u00e0 decis\u00e3o A promessa \u00e9 simples: que o analista comece a gerar insights desde o primeiro minuto, n\u00e3o s\u00f3 a partir da s\u00e9tima hora. 1 Execu\u00e7\u00e3o no aplicativo m\u00f3vel As equipes de campo realizam tarefas de facing, exposi\u00e7\u00e3o e promo\u00e7\u00e3o diretamente pelo aplicativo. Cada resposta \u00e9 sincronizada automaticamente ao fazer o check-out, incluindo evid\u00eancias fotogr\u00e1ficas georreferenciadas. 2 Processamento no Datapipe O mecanismo de dados da Teamcore normaliza, enriquece e estrutura as informa\u00e7\u00f5es em tempo real, cruzando dados de execu\u00e7\u00e3o com vendas, estoques e metas comerciais. 3 Configura\u00e7\u00e3o da consulta A partir da plataforma web, o analista configura seu download: tipo de tarefa, atributos do usu\u00e1rio, atributos da loja, produto at\u00e9 o n\u00edvel de SKU e intervalo temporal exato. 4 Download pronto para an\u00e1lise A planilha de dados chega limpa, homologada e estruturada. Sem trabalho de prepara\u00e7\u00e3o. A equipe pode passar diretamente das evid\u00eancias para a a\u00e7\u00e3o. O custo real de n\u00e3o ter esses dados em tempo h\u00e1bil: uma redu\u00e7\u00e3o de 1% na disponibilidade nas prateleiras pode representar milh\u00f5es em receitas perdidas por ano. Mas o preju\u00edzo n\u00e3o \u00e9 apenas econ\u00f4mico: cada dia sem visibilidade leva a equipe a reagir, em vez de prevenir. Sem automa\u00e7\u00e3o: 7h 10m por rede por semana apenas em gerenciamento, limpeza e homologa\u00e7\u00e3o de dados. Com o Teamcore: 26m por rede por semana. A diferen\u00e7a n\u00e3o est\u00e1 em produzir mais relat\u00f3rios; est\u00e1 em recuperar tempo para decidir. Redu\u00e7\u00e3o de 93% no tempo de gerenciamento de dados. Em uma opera\u00e7\u00e3o com 9 linhas de produ\u00e7\u00e3o, isso equivale a 3.150 horas recuperadas por ano para an\u00e1lise, prioriza\u00e7\u00e3o e a\u00e7\u00e3o no ponto de venda. O recado fundamental: quando as informa\u00e7\u00f5es chegam organizadas e na hora certa, a conversa muda: a equipe deixa de perguntar \u201co que aconteceu\u201d e come\u00e7a a decidir \u201co que faremos agora\u201d. Essa diferen\u00e7a separa as opera\u00e7\u00f5es que reagem daquelas que previnem. O impacto global do Teamcore em n\u00fameros A visibilidade operacional n\u00e3o apenas organiza as informa\u00e7\u00f5es. Ela tamb\u00e9m melhora a capacidade de recuperar vendas, manter a disponibilidade e resolver incidentes antes que eles se agravem. +75%, em m\u00e9dia, em vendas recuperadas com visibilidade operacional em tempo real. 6\u20139% de melhoria na disponibilidade de produtos nas prateleiras. \u221211,5% no tempo de resolu\u00e7\u00e3o de incidentes no ponto de venda. +23% de otimiza\u00e7\u00e3o do tempo da equipe no ponto de venda. Para uma opera\u00e7\u00e3o comercial, esses n\u00fameros significam menos tempo perdido em tarefas repetitivas e mais capacidade de agir onde a venda realmente acontece: o ponto de venda,<\/p>","protected":false},"author":2,"featured_media":5708,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[8],"tags":[],"class_list":["post-5706","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"\n<title>Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? - Teamcore<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? - Teamcore\" \/>\n<meta property=\"og:description\" content=\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? \u2014 Teamcore Blog Retail Execution \u00b7 Data Extraction Teamcore Editorial \u00b7 Consumo masivo Tus datos de campo ya est\u00e1n listos.\u00bfCu\u00e1ndo los usar\u00e1s? La ejecuci\u00f3n en punto de venta genera datos todos los d\u00edas. El problema es que muchas operaciones todav\u00eda los reciben tarde, incompletos o demasiado desordenados para convertirlos en decisiones. 7 min de lectura Data & ejecuci\u00f3n comercial CPG \u00b7 Field Teams \u00b7 Retail El problema no es falta de datos Es la velocidad con la que llegan a quien debe decidir. Solo el 12% de los retailers convierte datos en acciones preventivas. El 88% restante sigue operando con visibilidad parcial: encuentra el problema cuando la venta ya se perdi\u00f3. Tus equipos ya est\u00e1n generando la informaci\u00f3n. Lo que falta es convertirla en acci\u00f3n antes de que el punto de venta cobre la factura. 12% de los retailers convierte datos en acciones preventivas. 7h+ se pierden por cadena cada semana gestionando, limpiando y homologando datos. 10x ROI promedio cuando se elimina el cuello de botella operativo. El problema silencioso que destruye resultados Son las 8:00 AM. Tu producto estrella se agot\u00f3 ayer en 15 puntos de venta clave. Tus equipos est\u00e1n revisando rutas, la competencia est\u00e1 reponiendo sus espacios, y los consumidores est\u00e1n eligiendo otras marcas. Para cuando te enteres, ya es demasiado tarde. Esta escena no es una excepci\u00f3n: es parte del d\u00eda a d\u00eda en muchas operaciones de consumo masivo. La informaci\u00f3n sobre lo que ocurre en la g\u00f3ndola llega fragmentada, tarde, y con demasiado ruido para actuar. Los equipos comerciales pasan horas descargando archivos, limpiando bases, cruzando formatos y homologando datos antes de llegar al primer an\u00e1lisis real. El costo no est\u00e1 solo en el tiempo perdido. Est\u00e1 en los agotados que se detectan tarde, en las promociones que nadie corrige a tiempo, en las exhibiciones que se auditan cuando ya termin\u00f3 la campa\u00f1a y en los espacios que la competencia ocupa mientras el equipo todav\u00eda intenta ordenar la informaci\u00f3n. \u201cLa diferencia no fue que los problemas desaparecieran. Fue que el equipo los vio a tiempo para hacer algo al respecto.\u201d \u2014 Caso de \u00e9xito Teamcore \u00b7 Higiene & Belleza \u00b7 Per\u00fa 2025 El cuello de botella no est\u00e1 en la calidad de tus equipos. Est\u00e1 en la distancia entre los datos que se generan en terreno y las personas que necesitan actuar sobre ellos. Teamcore Data Extraction existe para eliminar esa distancia. Qu\u00e9 es Teamcore Data Extraction Data Extraction es la capa de inteligencia operativa de la plataforma Teamcore que transforma todo lo que sucede en el punto de venta \u2014visitas, tareas de ejecuci\u00f3n, evidencias fotogr\u00e1ficas, respuestas de campo\u2014 en datos estructurados, descargables y accionables en tiempo real. No es un simple exportador de reportes. Funciona como un motor de conversi\u00f3n: toma la ejecuci\u00f3n dispersa de miles de mercaderistas y supervisores, y la transforma en una s\u00e1bana de datos homologada, filtrable y lista para el an\u00e1lisis estrat\u00e9gico. M\u00f3dulo actual Descargador Standard de KPIs Sell-out, inventarios y m\u00e9tricas de disponibilidad historizados. Hasta 2 a\u00f1os de datos m\u00e1s el per\u00edodo actual en una sola consulta parametrizada. M\u00f3dulo actual Descargador de Ejecuci\u00f3n S\u00e1bana completa de respuestas de campo: tipo de tarea, usuario, tienda, producto hasta nivel SKU, rango de tiempo y links a evidencias fotogr\u00e1ficas. M\u00f3dulo actual Descargador de Fotograf\u00edas Descarga en PDF con filtros avanzados. Auditor\u00eda visual del estado real de la g\u00f3ndola sin depender de reportes manuales. En desarrollo Descargador Smart La pr\u00f3xima evoluci\u00f3n: KPIs inteligentes con IA incorporada para priorizar autom\u00e1ticamente las alertas con mayor impacto en ventas. C\u00f3mo funciona: del campo a la decisi\u00f3n La promesa es simple: que el analista empiece a generar insights desde el minuto uno, no desde la hora siete. 1 Ejecuci\u00f3n en App Mobile Los equipos de campo completan tareas de facing, exhibici\u00f3n y promoci\u00f3n desde la app. Cada respuesta se sincroniza autom\u00e1ticamente al hacer check-out, incluyendo evidencias fotogr\u00e1ficas georreferenciadas. 2 Procesamiento en Datapipe El motor de datos de Teamcore normaliza, enriquece y estructura la informaci\u00f3n en tiempo real, cruzando datos de ejecuci\u00f3n con sell-out, inventarios y metas comerciales. 3 Parametrizaci\u00f3n de la consulta Desde la plataforma web, el analista configura su descarga: tipo de tarea, atributos de usuario, atributos de tienda, producto hasta nivel SKU y rango temporal exacto. 4 Descarga lista para el an\u00e1lisis La s\u00e1bana de datos llega limpia, homologada y estructurada. Cero trabajo de preparaci\u00f3n. El equipo puede pasar directo de la evidencia a la acci\u00f3n. El costo real de no tener estos datos a tiempo Un 1% menos de disponibilidad en g\u00f3ndola puede representar millones en ingresos perdidos al a\u00f1o. Pero el da\u00f1o no es solo econ\u00f3mico: cada d\u00eda sin visibilidad empuja al equipo hacia la reacci\u00f3n en lugar de la prevenci\u00f3n. Sin automatizaci\u00f3n 7h 10m por cadena cada semana solo en gesti\u00f3n, limpieza y homologaci\u00f3n de datos. Con Teamcore 26m por cadena cada semana. La diferencia no est\u00e1 en hacer m\u00e1s reportes; est\u00e1 en recuperar tiempo para decidir. 93% de reducci\u00f3n en tiempo de gesti\u00f3n de datos. En una operaci\u00f3n con 9 cadenas, eso equivale a 3.150 horas recuperadas al a\u00f1o para an\u00e1lisis, priorizaci\u00f3n y acci\u00f3n en punto de venta. La se\u00f1al de fondo Cuando la informaci\u00f3n llega limpia y a tiempo, cambia la conversaci\u00f3n: el equipo deja de preguntar \u201cqu\u00e9 pas\u00f3\u201d y empieza a decidir \u201cqu\u00e9 hacemos ahora\u201d. Esa diferencia separa a las operaciones que reaccionan de las que previenen. El impacto global de Teamcore en n\u00fameros La visibilidad operativa no solo ordena la informaci\u00f3n. Tambi\u00e9n mejora la capacidad de recuperar venta, sostener disponibilidad y resolver incidencias antes de que escalen. +75% promedio en venta recuperada con visibilidad operativa en tiempo real. 6\u20139% de mejora en disponibilidad de productos en g\u00f3ndola. \u221211.5% en tiempo de resoluci\u00f3n de incidencias en punto de venta. +23% de optimizaci\u00f3n del tiempo del equipo en el punto de venta. Para una operaci\u00f3n comercial, estos n\u00fameros significan menos tiempo perdido en tareas repetitivas y m\u00e1s capacidad para actuar donde se juega la venta: el punto de venta,\" \/>\n<meta property=\"og:url\" content=\"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/\" \/>\n<meta property=\"og:site_name\" content=\"Teamcore\" \/>\n<meta property=\"article:published_time\" content=\"2026-06-08T20:39:56+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-06-11T16:20:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1703\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Contacto\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Contacto\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\"},\"author\":{\"name\":\"Contacto\",\"@id\":\"https:\\\/\\\/teamcore.com\\\/#\\\/schema\\\/person\\\/9a2c803c1b62f1939d4d7b59c3eb7825\"},\"headline\":\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s?\",\"datePublished\":\"2026-06-08T20:39:56+00:00\",\"dateModified\":\"2026-06-11T16:20:03+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\"},\"wordCount\":1181,\"image\":{\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/teamcore.com\\\/wp-content\\\/uploads\\\/2026\\\/06\\\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg\",\"articleSection\":[\"Blog\"],\"inLanguage\":\"pt-BR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\",\"url\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\",\"name\":\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? 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Quando voc\u00ea os usar\u00e1? - Teamcore","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/","og_locale":"pt_BR","og_type":"article","og_title":"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? - Teamcore","og_description":"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? \u2014 Teamcore Blog Retail Execution \u00b7 Data Extraction Teamcore Editorial \u00b7 Consumo masivo Tus datos de campo ya est\u00e1n listos.\u00bfCu\u00e1ndo los usar\u00e1s? La ejecuci\u00f3n en punto de venta genera datos todos los d\u00edas. El problema es que muchas operaciones todav\u00eda los reciben tarde, incompletos o demasiado desordenados para convertirlos en decisiones. 7 min de lectura Data & ejecuci\u00f3n comercial CPG \u00b7 Field Teams \u00b7 Retail El problema no es falta de datos Es la velocidad con la que llegan a quien debe decidir. Solo el 12% de los retailers convierte datos en acciones preventivas. El 88% restante sigue operando con visibilidad parcial: encuentra el problema cuando la venta ya se perdi\u00f3. Tus equipos ya est\u00e1n generando la informaci\u00f3n. Lo que falta es convertirla en acci\u00f3n antes de que el punto de venta cobre la factura. 12% de los retailers convierte datos en acciones preventivas. 7h+ se pierden por cadena cada semana gestionando, limpiando y homologando datos. 10x ROI promedio cuando se elimina el cuello de botella operativo. El problema silencioso que destruye resultados Son las 8:00 AM. Tu producto estrella se agot\u00f3 ayer en 15 puntos de venta clave. Tus equipos est\u00e1n revisando rutas, la competencia est\u00e1 reponiendo sus espacios, y los consumidores est\u00e1n eligiendo otras marcas. Para cuando te enteres, ya es demasiado tarde. Esta escena no es una excepci\u00f3n: es parte del d\u00eda a d\u00eda en muchas operaciones de consumo masivo. La informaci\u00f3n sobre lo que ocurre en la g\u00f3ndola llega fragmentada, tarde, y con demasiado ruido para actuar. Los equipos comerciales pasan horas descargando archivos, limpiando bases, cruzando formatos y homologando datos antes de llegar al primer an\u00e1lisis real. El costo no est\u00e1 solo en el tiempo perdido. Est\u00e1 en los agotados que se detectan tarde, en las promociones que nadie corrige a tiempo, en las exhibiciones que se auditan cuando ya termin\u00f3 la campa\u00f1a y en los espacios que la competencia ocupa mientras el equipo todav\u00eda intenta ordenar la informaci\u00f3n. \u201cLa diferencia no fue que los problemas desaparecieran. Fue que el equipo los vio a tiempo para hacer algo al respecto.\u201d \u2014 Caso de \u00e9xito Teamcore \u00b7 Higiene & Belleza \u00b7 Per\u00fa 2025 El cuello de botella no est\u00e1 en la calidad de tus equipos. Est\u00e1 en la distancia entre los datos que se generan en terreno y las personas que necesitan actuar sobre ellos. Teamcore Data Extraction existe para eliminar esa distancia. Qu\u00e9 es Teamcore Data Extraction Data Extraction es la capa de inteligencia operativa de la plataforma Teamcore que transforma todo lo que sucede en el punto de venta \u2014visitas, tareas de ejecuci\u00f3n, evidencias fotogr\u00e1ficas, respuestas de campo\u2014 en datos estructurados, descargables y accionables en tiempo real. No es un simple exportador de reportes. Funciona como un motor de conversi\u00f3n: toma la ejecuci\u00f3n dispersa de miles de mercaderistas y supervisores, y la transforma en una s\u00e1bana de datos homologada, filtrable y lista para el an\u00e1lisis estrat\u00e9gico. M\u00f3dulo actual Descargador Standard de KPIs Sell-out, inventarios y m\u00e9tricas de disponibilidad historizados. Hasta 2 a\u00f1os de datos m\u00e1s el per\u00edodo actual en una sola consulta parametrizada. M\u00f3dulo actual Descargador de Ejecuci\u00f3n S\u00e1bana completa de respuestas de campo: tipo de tarea, usuario, tienda, producto hasta nivel SKU, rango de tiempo y links a evidencias fotogr\u00e1ficas. M\u00f3dulo actual Descargador de Fotograf\u00edas Descarga en PDF con filtros avanzados. Auditor\u00eda visual del estado real de la g\u00f3ndola sin depender de reportes manuales. En desarrollo Descargador Smart La pr\u00f3xima evoluci\u00f3n: KPIs inteligentes con IA incorporada para priorizar autom\u00e1ticamente las alertas con mayor impacto en ventas. C\u00f3mo funciona: del campo a la decisi\u00f3n La promesa es simple: que el analista empiece a generar insights desde el minuto uno, no desde la hora siete. 1 Ejecuci\u00f3n en App Mobile Los equipos de campo completan tareas de facing, exhibici\u00f3n y promoci\u00f3n desde la app. Cada respuesta se sincroniza autom\u00e1ticamente al hacer check-out, incluyendo evidencias fotogr\u00e1ficas georreferenciadas. 2 Procesamiento en Datapipe El motor de datos de Teamcore normaliza, enriquece y estructura la informaci\u00f3n en tiempo real, cruzando datos de ejecuci\u00f3n con sell-out, inventarios y metas comerciales. 3 Parametrizaci\u00f3n de la consulta Desde la plataforma web, el analista configura su descarga: tipo de tarea, atributos de usuario, atributos de tienda, producto hasta nivel SKU y rango temporal exacto. 4 Descarga lista para el an\u00e1lisis La s\u00e1bana de datos llega limpia, homologada y estructurada. Cero trabajo de preparaci\u00f3n. El equipo puede pasar directo de la evidencia a la acci\u00f3n. El costo real de no tener estos datos a tiempo Un 1% menos de disponibilidad en g\u00f3ndola puede representar millones en ingresos perdidos al a\u00f1o. Pero el da\u00f1o no es solo econ\u00f3mico: cada d\u00eda sin visibilidad empuja al equipo hacia la reacci\u00f3n en lugar de la prevenci\u00f3n. Sin automatizaci\u00f3n 7h 10m por cadena cada semana solo en gesti\u00f3n, limpieza y homologaci\u00f3n de datos. Con Teamcore 26m por cadena cada semana. La diferencia no est\u00e1 en hacer m\u00e1s reportes; est\u00e1 en recuperar tiempo para decidir. 93% de reducci\u00f3n en tiempo de gesti\u00f3n de datos. En una operaci\u00f3n con 9 cadenas, eso equivale a 3.150 horas recuperadas al a\u00f1o para an\u00e1lisis, priorizaci\u00f3n y acci\u00f3n en punto de venta. La se\u00f1al de fondo Cuando la informaci\u00f3n llega limpia y a tiempo, cambia la conversaci\u00f3n: el equipo deja de preguntar \u201cqu\u00e9 pas\u00f3\u201d y empieza a decidir \u201cqu\u00e9 hacemos ahora\u201d. Esa diferencia separa a las operaciones que reaccionan de las que previenen. El impacto global de Teamcore en n\u00fameros La visibilidad operativa no solo ordena la informaci\u00f3n. Tambi\u00e9n mejora la capacidad de recuperar venta, sostener disponibilidad y resolver incidencias antes de que escalen. +75% promedio en venta recuperada con visibilidad operativa en tiempo real. 6\u20139% de mejora en disponibilidad de productos en g\u00f3ndola. \u221211.5% en tiempo de resoluci\u00f3n de incidencias en punto de venta. +23% de optimizaci\u00f3n del tiempo del equipo en el punto de venta. Para una operaci\u00f3n comercial, estos n\u00fameros significan menos tiempo perdido en tareas repetitivas y m\u00e1s capacidad para actuar donde se juega la venta: el punto de venta,","og_url":"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/","og_site_name":"Teamcore","article_published_time":"2026-06-08T20:39:56+00:00","article_modified_time":"2026-06-11T16:20:03+00:00","og_image":[{"width":2560,"height":1703,"url":"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg","type":"image\/jpeg"}],"author":"Contacto","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Contacto","Est. reading time":"6 minutos"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/#article","isPartOf":{"@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/"},"author":{"name":"Contacto","@id":"https:\/\/teamcore.com\/#\/schema\/person\/9a2c803c1b62f1939d4d7b59c3eb7825"},"headline":"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s?","datePublished":"2026-06-08T20:39:56+00:00","dateModified":"2026-06-11T16:20:03+00:00","mainEntityOfPage":{"@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/"},"wordCount":1181,"image":{"@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/#primaryimage"},"thumbnailUrl":"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg","articleSection":["Blog"],"inLanguage":"pt-BR"},{"@type":"WebPage","@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/","url":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/","name":"Seus dados de campo j\u00e1 est\u00e3o prontos. 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\n\t\t\t\t\t\r\n\r\n\r\n\r\n\r\nSeus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea os usar\u00e1? \u2014 Teamcore Blog<\/title>\r\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Montserrat:ital,wght@0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,400;1,700&family=Raleway:wght@300;400;500;600;700;800&display=swap\" rel=\"stylesheet\">\r\n<style>\r\n*, *::before, *::after { margin: 0; padding: 0; box-sizing: border-box; }\r\n\r\n:root {\r\n --navy: #02193a;\r\n --blue: #003670;\r\n --teal: #72B699;\r\n --teal-dark: #4a9478;\r\n --sky: #5D92AF;\r\n --amber: #f8b475;\r\n --red: #e86363;\r\n --off: #f5f7fb;\r\n --ink: #1c2638;\r\n --muted: #5a6680;\r\n --border: #dde4ee;\r\n --white: #ffffff;\r\n --font-head: 'Montserrat', 'Raleway', 'Source Sans Pro', Helvetica, Arial, sans-serif;\r\n --font-body: 'Raleway', 'Montserrat', 'Source Sans Pro', Helvetica, Arial, sans-serif;\r\n}\r\n\r\nbody {\r\n font-family: var(--font-body);\r\n background: var(--off);\r\n color: var(--ink);\r\n line-height: 1.75;\r\n overflow-x: hidden;\r\n}\r\n\r\n.reveal {\r\n opacity: 0;\r\n transform: translateY(40px);\r\n transition: opacity 0.7s cubic-bezier(0.22,1,0.36,1), transform 0.7s cubic-bezier(0.22,1,0.36,1);\r\n}\r\n.reveal.from-left { transform: translateX(-44px); }\r\n.reveal.from-right { transform: translateX(44px); }\r\n.reveal.scale-up { transform: translateY(20px) scale(0.96); }\r\n.reveal.is-visible { opacity: 1 !important; transform: none !important; }\r\n\r\n.stagger-group > * {\r\n opacity: 0;\r\n transform: translateY(28px);\r\n transition: opacity 0.55s cubic-bezier(0.22,1,0.36,1), transform 0.55s cubic-bezier(0.22,1,0.36,1);\r\n}\r\n.stagger-group.is-visible > *:nth-child(1){ opacity:1; transform:none; transition-delay:0s; }\r\n.stagger-group.is-visible > *:nth-child(2){ opacity:1; transform:none; transition-delay:0.11s; }\r\n.stagger-group.is-visible > *:nth-child(3){ opacity:1; transform:none; transition-delay:0.22s; }\r\n.stagger-group.is-visible > *:nth-child(4){ opacity:1; transform:none; transition-delay:0.33s; }\r\n\r\n.hero {\r\n background: linear-gradient(145deg, #01112a 0%, #003670 54%, #0a4f6a 100%);\r\n position: relative;\r\n overflow: hidden;\r\n min-height: 680px;\r\n display: flex;\r\n flex-direction: column;\r\n justify-content: flex-end;\r\n}\r\n.hero-orb1 {\r\n position: absolute; top: -120px; right: -70px;\r\n width: 560px; height: 560px;\r\n border-radius: 50%;\r\n background: radial-gradient(circle, rgba(114,182,153,0.16) 0%, transparent 68%);\r\n pointer-events: none;\r\n}\r\n.hero-orb2 {\r\n position: absolute; bottom: -90px; left: 8%;\r\n width: 340px; height: 340px;\r\n border-radius: 50%;\r\n background: radial-gradient(circle, rgba(93,146,175,0.14) 0%, transparent 70%);\r\n pointer-events: none;\r\n}\r\n.hero-lines {\r\n position: absolute; inset: 0;\r\n background: repeating-linear-gradient(-45deg, transparent, transparent 42px, rgba(255,255,255,0.014) 42px, rgba(255,255,255,0.014) 43px);\r\n pointer-events: none;\r\n}\r\n.hero-grid {\r\n position: absolute;\r\n inset: 0;\r\n opacity: 0.18;\r\n background-image: linear-gradient(rgba(255,255,255,0.08) 1px, transparent 1px), linear-gradient(90deg, rgba(255,255,255,0.08) 1px, transparent 1px);\r\n background-size: 80px 80px;\r\n mask-image: radial-gradient(circle at 75% 25%, black 0%, transparent 58%);\r\n}\r\n.hero-inner {\r\n position: relative; z-index: 2;\r\n padding: 96px clamp(56px, 7vw, 112px) 84px;\r\n max-width: 1280px;\r\n width: 100%;\r\n}\r\n.hero-eyebrow { display: flex; align-items: center; gap: 12px; margin-bottom: 28px; flex-wrap: wrap; }\r\n.hero-tag {\r\n display: inline-block;\r\n background: rgba(114,182,153,0.18);\r\n border: 1px solid rgba(114,182,153,0.38);\r\n color: var(--teal);\r\n font-family: var(--font-head);\r\n font-size: 10px; font-weight: 700;\r\n letter-spacing: 2.5px; text-transform: uppercase;\r\n padding: 5px 14px; border-radius: 20px;\r\n}\r\n.hero-date { font-size: 12px; color: rgba(255,255,255,0.35); letter-spacing: 0.4px; }\r\n.hero h1 {\r\n font-family: var(--font-head);\r\n font-size: clamp(42px, 5.2vw, 84px);\r\n font-weight: 800;\r\n color: #fff;\r\n line-height: 1.08;\r\n margin-bottom: 28px;\r\n max-width: 980px;\r\n}\r\n.hero h1 em { font-style: italic; color: var(--teal); font-weight: 700; }\r\n.hero-deck {\r\n font-size: clamp(19px, 1.45vw, 24px); font-weight: 300;\r\n color: rgba(255,255,255,0.68);\r\n max-width: 760px; line-height: 1.68;\r\n margin-bottom: 40px;\r\n}\r\n.hero-meta {\r\n display: flex; align-items: center; gap: 26px; flex-wrap: wrap;\r\n border-top: 1px solid rgba(255,255,255,0.09);\r\n padding-top: 24px;\r\n}\r\n.meta-pill { font-size: 12px; color: rgba(255,255,255,0.42); display: flex; align-items: center; gap: 7px; }\r\n.meta-dot { width: 4px; height: 4px; border-radius: 50%; background: var(--teal); }\r\n\r\n.hero-visual {\r\n position: absolute;\r\n right: clamp(48px, 7vw, 130px);\r\n bottom: 86px;\r\n width: min(460px, 32vw);\r\n opacity: 0.92;\r\n z-index: 1;\r\n}\r\n.hero-visual svg { width: 100%; height: auto; display: block; }\r\n\r\n.article {\r\n max-width: 1680px;\r\n margin: 0 auto;\r\n padding: 88px clamp(48px, 4.2vw, 80px) 120px;\r\n}\r\n\r\np {\r\n font-size: clamp(18px, 1.1vw, 21px); font-weight: 400;\r\n color: #2d3a52; margin-bottom: 22px; line-height: 1.85;\r\n}\r\nh2 {\r\n font-family: var(--font-head);\r\n font-size: clamp(28px, 2.4vw, 38px);\r\n font-weight: 700; color: var(--navy);\r\n line-height: 1.25; margin: 68px 0 18px;\r\n display: flex; align-items: center; gap: 12px;\r\n}\r\nh2 .h-icon {\r\n width: 44px; height: 44px; flex-shrink: 0;\r\n background: linear-gradient(135deg, #e4f0fa 0%, #d9f0e8 100%);\r\n border-radius: 9px;\r\n display: flex; align-items: center; justify-content: center;\r\n}\r\nh2 .h-icon svg { width: 22px; height: 22px; }\r\nh2:first-of-type { margin-top: 0; }\r\n\r\nh3 {\r\n font-family: var(--font-head);\r\n font-size: 20px; font-weight: 700;\r\n color: var(--blue);\r\n margin: 40px 0 10px;\r\n display: flex; align-items: center; gap: 10px;\r\n}\r\nh3 .h3-icon {\r\n width: 28px; height: 28px; flex-shrink: 0;\r\n background: linear-gradient(135deg, #ddeeff 0%, #d4f0e6 100%);\r\n border-radius: 7px;\r\n display: flex; align-items: center; justify-content: center;\r\n}\r\nh3 .h3-icon svg { width: 14px; height: 14px; }\r\n\r\n.opener {\r\n font-family: var(--font-head);\r\n font-size: clamp(26px, 2.2vw, 34px);\r\n font-weight: 700; font-style: italic;\r\n color: var(--blue); line-height: 1.4;\r\n border-left: 4px solid var(--teal);\r\n padding-left: 28px; margin-bottom: 52px;\r\n}\r\n\r\n.src {\r\n font-family: var(--font-head);\r\n font-size: 10px; font-weight: 600;\r\n letter-spacing: 1px; text-transform: uppercase;\r\n color: var(--sky); opacity: 0.9;\r\n border: 1px solid rgba(93,146,175,0.3);\r\n border-radius: 4px; padding: 2px 7px;\r\n margin-left: 6px; vertical-align: middle;\r\n white-space: nowrap;\r\n}\r\n\r\n.data-hero {\r\n margin: 56px 0;\r\n background: linear-gradient(135deg, #ffffff 0%, #ecf5fb 100%);\r\n border: 1px solid var(--border);\r\n border-radius: 22px;\r\n min-height: 370px;\r\n overflow: hidden;\r\n position: relative;\r\n display: grid;\r\n grid-template-columns: 1fr 1fr;\r\n}\r\n.data-hero-copy { padding: 42px 42px 38px; display: flex; flex-direction: column; justify-content: center; }\r\n.data-hero-copy .label {\r\n font-family: var(--font-head); font-size: 10px; font-weight: 800; letter-spacing: 2px;\r\n text-transform: uppercase; color: var(--teal-dark); margin-bottom: 14px;\r\n}\r\n.data-hero-copy h2 { display: block; margin: 0 0 14px; }\r\n.data-hero-copy p { font-size: 18px; color: var(--muted); margin-bottom: 0; }\r\n.data-hero-graphic {\r\n background: linear-gradient(145deg, rgba(2,25,58,0.98), rgba(0,54,112,0.96));\r\n position: relative;\r\n display: flex; align-items: center; justify-content: center;\r\n padding: 28px;\r\n}\r\n.data-hero-graphic svg { width: 100%; max-width: 330px; }\r\n\r\n.scene {\r\n background: linear-gradient(135deg, #02193a 0%, #003670 100%);\r\n border-radius: 18px;\r\n padding: 44px 48px;\r\n margin: 52px 0;\r\n position: relative; overflow: hidden;\r\n}\r\n.scene::after {\r\n content: '';\r\n position: absolute; top: -50px; right: -50px;\r\n width: 220px; height: 220px;\r\n border: 42px solid rgba(114,182,153,0.08);\r\n border-radius: 50%;\r\n}\r\n.scene p {\r\n color: rgba(255,255,255,0.8);\r\n font-size: 20px; margin-bottom: 0;\r\n position: relative; z-index: 1;\r\n}\r\n.scene p + p { margin-top: 16px; }\r\n.scene strong { color: #fff; font-weight: 600; }\r\n\r\n.stat-grid {\r\n display: grid;\r\n grid-template-columns: repeat(3, 1fr);\r\n gap: 22px; margin: 60px 0;\r\n}\r\n.stat-card {\r\n background: linear-gradient(160deg, #ffffff 0%, #f4f8fd 100%);\r\n border: 1px solid var(--border);\r\n border-radius: 16px;\r\n padding: 34px 30px;\r\n position: relative; overflow: hidden;\r\n}\r\n.stat-card::after { content: ''; position: absolute; top: 0; left: 0; right: 0; height: 3px; }\r\n.stat-card.c-teal::after { background: linear-gradient(90deg, var(--teal), #4ebf9a); }\r\n.stat-card.c-sky::after { background: linear-gradient(90deg, var(--sky), #3a7fa0); }\r\n.stat-card.c-amber::after { background: linear-gradient(90deg, var(--amber), #e89a4a); }\r\n.stat-card.c-navy::after { background: linear-gradient(90deg, var(--navy), var(--blue)); }\r\n.stat-num {\r\n font-family: var(--font-head);\r\n font-size: 48px; font-weight: 800;\r\n color: var(--navy); line-height: 1; margin-bottom: 10px;\r\n}\r\n.stat-num.up { color: var(--teal-dark); }\r\n.stat-num.down { color: var(--red); }\r\n.stat-label { font-size: 15px; color: var(--muted); line-height: 1.55; }\r\n\r\n.pullquote {\r\n border-left: 4px solid var(--teal);\r\n padding: 6px 0 6px 30px;\r\n margin: 52px 0;\r\n}\r\n.pullquote p {\r\n font-family: var(--font-head);\r\n font-size: 24px; font-weight: 600;\r\n font-style: italic; color: var(--blue);\r\n margin-bottom: 10px; line-height: 1.55;\r\n}\r\n.pullquote cite {\r\n font-family: var(--font-head); font-size: 12px; color: var(--teal-dark);\r\n font-style: normal; font-weight: 700; letter-spacing: 0.3px;\r\n}\r\n\r\n.divider {\r\n height: 1px;\r\n background: linear-gradient(90deg, transparent, var(--border), transparent);\r\n margin: 64px 0;\r\n}\r\n\r\n.module-grid {\r\n display: grid;\r\n grid-template-columns: 1fr 1fr;\r\n gap: 24px;\r\n margin: 46px 0;\r\n}\r\n.module-card {\r\n background: #fff;\r\n border: 1px solid var(--border);\r\n border-radius: 16px;\r\n padding: 34px;\r\n position: relative;\r\n overflow: hidden;\r\n}\r\n.module-card::before {\r\n content: '';\r\n position: absolute;\r\n width: 120px; height: 120px;\r\n right: -62px; top: -62px;\r\n border-radius: 50%;\r\n background: rgba(114,182,153,0.10);\r\n}\r\n.module-kicker {\r\n font-family: var(--font-head); font-size: 10px; font-weight: 800; letter-spacing: 1.8px;\r\n text-transform: uppercase; color: var(--teal-dark); margin-bottom: 10px;\r\n}\r\n.module-card h4 {\r\n font-family: var(--font-head); font-size: 22px; color: var(--navy); line-height: 1.3; margin-bottom: 10px;\r\n}\r\n.module-card p { font-size: 17px; color: var(--muted); line-height: 1.72; margin-bottom: 0; }\r\n\r\n.process {\r\n margin: 48px 0;\r\n border: 1px solid var(--border);\r\n border-radius: 18px;\r\n overflow: hidden;\r\n background: #fff;\r\n}\r\n.process-step {\r\n display: grid;\r\n grid-template-columns: 84px 1fr;\r\n gap: 22px;\r\n padding: 28px 30px;\r\n border-bottom: 1px solid var(--border);\r\n}\r\n.process-step:last-child { border-bottom: none; }\r\n.process-num {\r\n width: 52px; height: 52px;\r\n border-radius: 15px;\r\n background: linear-gradient(135deg, #02193a, #003670);\r\n color: var(--teal);\r\n font-family: var(--font-head);\r\n font-weight: 900;\r\n font-size: 22px;\r\n display: flex; align-items: center; justify-content: center;\r\n}\r\n.process-copy h4 {\r\n font-family: var(--font-head); color: var(--navy); font-size: 21px; margin-bottom: 6px;\r\n}\r\n.process-copy p { font-size: 17px; color: var(--muted); margin: 0; line-height: 1.72; }\r\n\r\n.comparison {\r\n display: grid;\r\n grid-template-columns: 1fr 1fr;\r\n gap: 24px;\r\n margin: 48px 0 26px;\r\n}\r\n.compare-card {\r\n border-radius: 18px;\r\n padding: 32px 30px;\r\n border: 1px solid var(--border);\r\n background: #fff;\r\n}\r\n.compare-card.dark {\r\n background: linear-gradient(135deg, #02193a 0%, #003670 100%);\r\n border-color: rgba(255,255,255,0.08);\r\n}\r\n.compare-label {\r\n font-family: var(--font-head); font-size: 10px; font-weight: 800; letter-spacing: 1.8px;\r\n text-transform: uppercase; color: var(--muted); margin-bottom: 12px;\r\n}\r\n.compare-card.dark .compare-label { color: var(--teal); }\r\n.compare-number {\r\n font-family: var(--font-head); font-size: 56px; line-height: 1; font-weight: 900; color: var(--red); margin-bottom: 10px;\r\n}\r\n.compare-card.dark .compare-number { color: var(--teal); }\r\n.compare-card p { font-size: 17px; color: var(--muted); margin: 0; line-height: 1.68; }\r\n.compare-card.dark p { color: rgba(255,255,255,0.72); }\r\n\r\n.big-number {\r\n display: flex; align-items: baseline; gap: 18px;\r\n background: linear-gradient(135deg, #02193a 0%, #003670 100%);\r\n border-radius: 16px;\r\n padding: 34px 40px; margin: 44px 0;\r\n}\r\n.big-n {\r\n font-family: var(--font-head); font-size: 86px; font-weight: 900;\r\n color: var(--teal); line-height: 1; flex-shrink: 0;\r\n}\r\n.big-n-text { font-size: 19px; color: rgba(255,255,255,0.74); line-height: 1.65; }\r\n.big-n-text strong { color: #fff; font-weight: 600; }\r\n\r\n.impact-grid {\r\n display: grid;\r\n grid-template-columns: repeat(4, 1fr);\r\n gap: 20px;\r\n margin: 48px 0;\r\n}\r\n.impact-card {\r\n background: linear-gradient(160deg, #ffffff 0%, #f4f8fd 100%);\r\n border: 1px solid var(--border);\r\n border-radius: 16px;\r\n padding: 24px 18px;\r\n}\r\n.impact-number {\r\n font-family: var(--font-head);\r\n font-size: 42px;\r\n font-weight: 900;\r\n color: var(--teal-dark);\r\n line-height: 1;\r\n margin-bottom: 12px;\r\n}\r\n.impact-card p { font-size: 15px; line-height: 1.5; color: var(--muted); margin: 0; }\r\n\r\n.insight {\r\n background: linear-gradient(135deg, #e6f2ff 0%, #ddf0ea 100%);\r\n border: 1px solid #bcd8f5;\r\n border-radius: 16px;\r\n padding: 36px 40px; margin: 48px 0;\r\n}\r\n.insight-label {\r\n font-family: var(--font-head);\r\n font-size: 10px; font-weight: 700;\r\n letter-spacing: 2px; text-transform: uppercase;\r\n color: var(--teal-dark); margin-bottom: 12px;\r\n display: flex; align-items: center; gap: 6px;\r\n}\r\n.insight p { font-size: 19px; color: #1b3050; margin-bottom: 0; }\r\n\r\n.cta-block {\r\n background: linear-gradient(145deg, #01112a 0%, #003670 55%, #0a4f6a 100%);\r\n border-radius: 22px;\r\n padding: 68px 54px;\r\n text-align: center; margin-top: 76px;\r\n position: relative; overflow: hidden;\r\n}\r\n.cta-block::before {\r\n content: ''; position: absolute; bottom: -60px; right: -60px;\r\n width: 300px; height: 300px;\r\n border: 52px solid rgba(114,182,153,0.07); border-radius: 50%;\r\n}\r\n.cta-block::after {\r\n content: ''; position: absolute; top: -40px; left: -40px;\r\n width: 190px; height: 190px;\r\n border: 36px solid rgba(93,146,175,0.06); border-radius: 50%;\r\n}\r\n.cta-block h2 {\r\n color: #fff; margin-top: 0; font-size: clamp(20px, 3vw, 30px);\r\n position: relative; z-index: 1; display: block;\r\n}\r\n.cta-block p {\r\n color: rgba(255,255,255,0.62);\r\n max-width: 500px; margin: 0 auto 32px;\r\n font-size: 18px; position: relative; z-index: 1;\r\n}\r\n.cta-btn {\r\n display: inline-block;\r\n background: linear-gradient(135deg, #72B699 0%, #4a9478 100%);\r\n color: var(--navy);\r\n font-family: var(--font-head);\r\n font-size: 15px; font-weight: 700;\r\n padding: 16px 46px; border-radius: 40px;\r\n text-decoration: none; letter-spacing: 0.3px;\r\n position: relative; z-index: 1;\r\n transition: transform 0.18s, box-shadow 0.18s;\r\n box-shadow: 0 6px 24px rgba(72,180,150,0.3);\r\n}\r\n.cta-btn:hover { transform: translateY(-3px); box-shadow: 0 10px 32px rgba(72,180,150,0.4); }\r\n\r\n\r\n@media (min-width: 1180px) {\r\n .hero { min-height: 760px; }\r\n\r\n \/* Desktop amplio: el hero se mantiene, pero el cuerpo usa mucho m\u00e1s ancho \u00fatil. *\/\r\n .article {\r\n max-width: 1680px;\r\n padding-left: clamp(56px, 4vw, 88px);\r\n padding-right: clamp(56px, 4vw, 88px);\r\n }\r\n\r\n .article > p,\r\n .article > h2,\r\n .article > h3,\r\n .article > .opener,\r\n .article > .pullquote,\r\n .article > .scene,\r\n .article > .insight {\r\n max-width: 1320px;\r\n }\r\n\r\n .article > p {\r\n font-size: clamp(20px, 1.15vw, 23px);\r\n line-height: 1.82;\r\n }\r\n\r\n .article > .opener {\r\n max-width: 1400px;\r\n }\r\n\r\n .article > .stat-grid,\r\n .article > .data-hero,\r\n .article > .module-grid,\r\n .article > .process,\r\n .article > .comparison,\r\n .article > .big-number,\r\n .article > .impact-grid,\r\n .article > .cta-block,\r\n .article > .divider {\r\n width: 100%;\r\n max-width: none;\r\n }\r\n\r\n .data-hero {\r\n grid-template-columns: 1.18fr 0.82fr;\r\n min-height: 430px;\r\n }\r\n .data-hero-copy { padding: 56px 64px; }\r\n .data-hero-copy p { font-size: 20px; line-height: 1.75; }\r\n .process-step { grid-template-columns: 104px 1fr; padding: 34px 44px; }\r\n .process-step p { font-size: 18px; }\r\n .process-num { width: 62px; height: 62px; font-size: 26px; }\r\n}\r\n\r\n@media (min-width: 1600px) {\r\n .article {\r\n max-width: 1780px;\r\n padding-left: 64px;\r\n padding-right: 64px;\r\n }\r\n\r\n .article > p,\r\n .article > h2,\r\n .article > h3,\r\n .article > .opener,\r\n .article > .pullquote,\r\n .article > .scene,\r\n .article > .insight {\r\n max-width: 1460px;\r\n }\r\n}\r\n\r\n@media (max-width: 860px) {\r\n .hero-visual { opacity: 0.25; right: -40px; width: 420px; }\r\n .impact-grid { grid-template-columns: 1fr 1fr; }\r\n}\r\n@media (max-width: 680px) {\r\n .hero h1 { font-size: clamp(34px, 11vw, 46px); }\r\n .hero-deck { font-size: 17px; }\r\n p { font-size: 17px; }\r\n h2 { font-size: clamp(22px, 7vw, 29px); }\r\n .hero-inner { padding: 60px 24px 50px; }\r\n .article { max-width: 100%; padding: 44px 20px 72px; }\r\n .stat-grid, .module-grid, .comparison, .data-hero { grid-template-columns: 1fr; }\r\n .impact-grid { grid-template-columns: 1fr 1fr; }\r\n .scene { padding: 30px 28px; }\r\n .cta-block { padding: 44px 28px; }\r\n .big-number { flex-direction: column; gap: 4px; }\r\n .big-n { font-size: 50px; }\r\n .process-step { grid-template-columns: 1fr; gap: 12px; padding: 24px; }\r\n .data-hero-graphic { min-height: 230px; }\r\n}\r\n@media (max-width: 430px) {\r\n .impact-grid { grid-template-columns: 1fr; }\r\n}\r\n<\/style>\r\n<\/head>\r\n<body>\r\n\r\n<header class=\"hero\">\r\n <div class=\"hero-orb1\"><\/div>\r\n <div class=\"hero-orb2\"><\/div>\r\n <div class=\"hero-lines\"><\/div>\r\n <div class=\"hero-grid\"><\/div>\r\n <div class=\"hero-visual\" aria-hidden=\"true\">\r\n <svg viewbox=\"0 0 420 420\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\r\n <rect x=\"62\" y=\"80\" width=\"296\" height=\"230\" rx=\"24\" fill=\"rgba(255,255,255,0.08)\" stroke=\"rgba(255,255,255,0.22)\"\/>\r\n <rect x=\"94\" y=\"118\" width=\"90\" height=\"12\" rx=\"6\" fill=\"#72B699\"\/>\r\n <rect x=\"94\" y=\"152\" width=\"230\" height=\"10\" rx=\"5\" fill=\"rgba(255,255,255,0.34)\"\/>\r\n <rect x=\"94\" y=\"180\" width=\"178\" height=\"10\" rx=\"5\" fill=\"rgba(255,255,255,0.24)\"\/>\r\n <rect x=\"94\" y=\"224\" width=\"48\" height=\"48\" rx=\"12\" fill=\"rgba(114,182,153,0.20)\"\/>\r\n <rect x=\"158\" y=\"224\" width=\"48\" height=\"48\" rx=\"12\" fill=\"rgba(93,146,175,0.22)\"\/>\r\n <rect x=\"222\" y=\"224\" width=\"48\" height=\"48\" rx=\"12\" fill=\"rgba(248,180,117,0.20)\"\/>\r\n <path d=\"M118 248h128\" stroke=\"#72B699\" stroke-width=\"4\" stroke-linecap=\"round\"\/>\r\n <circle cx=\"300\" cy=\"78\" r=\"34\" fill=\"rgba(114,182,153,0.22)\"\/>\r\n <path d=\"M286 78l10 10 20-22\" stroke=\"#72B699\" stroke-width=\"7\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\r\n <circle cx=\"82\" cy=\"318\" r=\"30\" fill=\"rgba(93,146,175,0.22)\"\/>\r\n <path d=\"M70 318h24M82 306v24\" stroke=\"#5D92AF\" stroke-width=\"6\" stroke-linecap=\"round\"\/>\r\n <\/svg>\r\n <\/div>\r\n <div class=\"hero-inner\">\r\n <div class=\"hero-eyebrow\">\r\n <span class=\"hero-tag\">Execu\u00e7\u00e3o no Varejo \u00b7 Extra\u00e7\u00e3o de Dados<\/span>\r\n <span class=\"hero-date\">Teamcore Editorial \u00b7 Consumo massivo<\/span>\r\n <\/div>\r\n <h1>Seus dados de campo j\u00e1 est\u00e3o prontos.<br><em>Quando voc\u00ea os usar\u00e1?<\/em><\/h1>\r\n <p class=\"hero-deck\">A execu\u00e7\u00e3o no ponto de venda gera dados todos os dias. O problema \u00e9 que muitas opera\u00e7\u00f5es ainda os recebem tarde, incompletos ou desorganizados demais para transform\u00e1-los em decis\u00f5es.<\/p>\r\n <div class=\"hero-meta\">\r\n <span class=\"meta-pill\"><span class=\"meta-dot\"><\/span>7 min de leitura<\/span>\r\n <span class=\"meta-pill\"><span class=\"meta-dot\"><\/span>Dados e execu\u00e7\u00e3o comercial<\/span>\r\n <span class=\"meta-pill\"><span class=\"meta-dot\"><\/span>CPG \u00b7 Equipes de Campo \u00b7 Varejo<\/span>\r\n <\/div>\r\n <\/div>\r\n<\/header>\r\n\r\n<article class=\"article\">\r\n\r\n <div class=\"data-hero reveal scale-up\">\r\n <div class=\"data-hero-copy\">\r\n <div class=\"label\">O problema n\u00e3o \u00e9 falta de dados<\/div>\r\n <h2>\u00c9 a velocidade com que chegam a quem deve decidir.<\/h2>\r\n <p>Apenas o 12% dos varejistas transforma dados em a\u00e7\u00f5es preventivas. O restante, 88%, continua operando com visibilidade parcial: identifica o problema quando a venda j\u00e1 foi perdida.<\/p>\r\n <\/div>\r\n <div class=\"data-hero-graphic\" aria-hidden=\"true\">\r\n <svg viewbox=\"0 0 360 260\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\r\n <rect x=\"24\" y=\"30\" width=\"312\" height=\"198\" rx=\"18\" fill=\"rgba(255,255,255,0.08)\" stroke=\"rgba(255,255,255,0.18)\"\/>\r\n <rect x=\"52\" y=\"58\" width=\"102\" height=\"12\" rx=\"6\" fill=\"#72B699\"\/>\r\n <rect x=\"52\" y=\"92\" width=\"256\" height=\"8\" rx=\"4\" fill=\"rgba(255,255,255,0.32)\"\/>\r\n <rect x=\"52\" y=\"114\" width=\"218\" height=\"8\" rx=\"4\" fill=\"rgba(255,255,255,0.22)\"\/>\r\n <rect x=\"52\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(114,182,153,0.20)\"\/>\r\n <rect x=\"112\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(93,146,175,0.22)\"\/>\r\n <rect x=\"172\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(248,180,117,0.20)\"\/>\r\n <rect x=\"232\" y=\"150\" width=\"46\" height=\"46\" rx=\"10\" fill=\"rgba(255,255,255,0.12)\"\/>\r\n <path d=\"M68 172l10 10 20-26\" stroke=\"#72B699\" stroke-width=\"5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\r\n <circle cx=\"135\" cy=\"173\" r=\"11\" stroke=\"#5D92AF\" stroke-width=\"5\"\/>\r\n <path d=\"M190 162v22M179 173h22\" stroke=\"#F8B475\" stroke-width=\"5\" stroke-linecap=\"round\"\/>\r\n <path d=\"M240 162l24 24M264 162l-24 24\" stroke=\"rgba(255,255,255,0.55)\" stroke-width=\"4\" stroke-linecap=\"round\"\/>\r\n <\/svg>\r\n <\/div>\r\n <\/div>\r\n\r\n <p class=\"opener reveal\">Suas equipes j\u00e1 est\u00e3o gerando a informa\u00e7\u00e3o. O que falta \u00e9 convert\u00ea-la em a\u00e7\u00e3o antes que o ponto de venda pague a fatura.<\/p>\r\n\r\n <div class=\"stat-grid stagger-group\">\r\n <div class=\"stat-card c-teal\">\r\n <div class=\"stat-num\">12%<\/div>\r\n <div class=\"stat-label\">dos varejistas transforma dados em a\u00e7\u00f5es preventivas.<\/div>\r\n <\/div>\r\n <div class=\"stat-card c-sky\">\r\n <div class=\"stat-num down\">7h+<\/div>\r\n <div class=\"stat-label\">se perdem por cadeia cada semana gerenciando, limpando e homologando dados.<\/div>\r\n <\/div>\r\n <div class=\"stat-card c-amber\">\r\n <div class=\"stat-num up\">10x<\/div>\r\n <div class=\"stat-label\">ROI m\u00e9dio quando o gargalo operacional \u00e9 eliminado.<\/div>\r\n <\/div>\r\n <\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M10.29 3.86L1.82 18a2 2 0 001.71 3h16.94a2 2 0 001.71-3L13.71 3.86a2 2 0 00-3.42 0z\"\/><line x1=\"12\" y1=\"9\" x2=\"12\" y2=\"13\"\/><line x1=\"12\" y1=\"17\" x2=\"12.01\" y2=\"17\"\/><\/svg>\r\n <\/span>\r\n O problema silencioso que destr\u00f3i resultados\r\n <\/h2>\r\n\r\n <div class=\"scene reveal\">\r\n <p>S\u00e3o 8h00. Seu produto principal esgotou ontem em 15 pontos de venda fundamentais. Suas equipes est\u00e3o revisando rotas, a concorr\u00eancia est\u00e1 repostando seus espa\u00e7os e os consumidores est\u00e3o escolhendo outras marcas.<\/p>\r\n <p><strong>Para quando voc\u00ea souber, j\u00e1 \u00e9 tarde demais.<\/strong><\/p>\r\n <\/div>\r\n\r\n <p class=\"reveal\">Esta cena n\u00e3o \u00e9 uma exce\u00e7\u00e3o: \u00e9 parte do dia a dia em muitas opera\u00e7\u00f5es de bens de consumo. As informa\u00e7\u00f5es sobre o que acontece na g\u00f4ndola chegam fragmentadas, tarde e com ru\u00eddo demais para agir. As equipes comerciais passam horas baixando arquivos, limpando bases, cruzando formatos e homologando dados antes de chegar \u00e0 primeira an\u00e1lise real.<\/p>\r\n\r\n <p class=\"reveal\">O custo n\u00e3o est\u00e1 apenas no tempo perdido. Est\u00e1 nos esgotados que s\u00e3o detectados tarde, nas promo\u00e7\u00f5es que ningu\u00e9m corrige a tempo, nas exibi\u00e7\u00f5es que s\u00e3o auditadas quando a campanha j\u00e1 terminou e nos espa\u00e7os que a concorr\u00eancia ocupa enquanto a equipe ainda tenta organizar a informa\u00e7\u00e3o.<\/p>\r\n\r\n <div class=\"pullquote reveal from-left\">\r\n <p>\u201cA diferen\u00e7a n\u00e3o foi que os problemas desapareceram. Foi que a equipe os viu a tempo de fazer algo a respeito.\u201d<\/p>\r\n <cite>\u2014 Caso de sucesso Teamcore \u00b7 Higiene & Beleza \u00b7 Peru 2025<\/cite>\r\n <\/div>\r\n\r\n <p class=\"reveal\">O gargalo n\u00e3o est\u00e1 na qualidade dos seus equipamentos. Est\u00e1 na dist\u00e2ncia entre os dados gerados em campo e as pessoas que precisam agir sobre eles. O Teamcore Data Extraction existe para eliminar essa dist\u00e2ncia.<\/p>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M21 16V8a2 2 0 00-1-1.73l-7-4a2 2 0 00-2 0l-7 4A2 2 0 003 8v8a2 2 0 001 1.73l7 4a2 2 0 002 0l7-4A2 2 0 0021 16z\"\/><polyline points=\"3.27 6.96 12 12.01 20.73 6.96\"\/><line x1=\"12\" y1=\"22.08\" x2=\"12\" y2=\"12\"\/><\/svg>\r\n <\/span>\r\n O que \u00e9 o Teamcore Data Extraction\r\n <\/h2>\r\n\r\n <p class=\"reveal\">Data Extraction \u00e9 a camada de intelig\u00eancia operacional da plataforma Teamcore que transforma tudo o que acontece no ponto de venda \u2014 visitas, tarefas de execu\u00e7\u00e3o, evid\u00eancias fotogr\u00e1ficas, respostas de campo \u2014 em dados estruturados, baixadores e acion\u00e1veis em tempo real.<\/p>\r\n\r\n <p class=\"reveal\">N\u00e3o \u00e9 um simples exportador de relat\u00f3rios. Funciona como um motor de convers\u00e3o: ele pega a execu\u00e7\u00e3o dispersa de milhares de promotores e supervisores, e a transforma em uma planilha de dados padronizada, filtr\u00e1vel e pronta para a an\u00e1lise estrat\u00e9gica.<\/p>\r\n\r\n <div class=\"module-grid stagger-group\">\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">M\u00f3dulo atual<\/div>\r\n <h4>Baixador Standard de KPIs<\/h4>\r\n <p>Sell-out, estoques e m\u00e9tricas de disponibilidade historizados. At\u00e9 2 anos de dados mais o per\u00edodo atual em uma \u00fanica consulta parametrizada.<\/p>\r\n <\/div>\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">M\u00f3dulo atual<\/div>\r\n <h4>Descarregador de Execu\u00e7\u00e3o<\/h4>\r\n <p>Planilha completa de respostas de campo: tipo de tarefa, usu\u00e1rio, loja, produto at\u00e9 o n\u00edvel SKU, intervalo de tempo e links para evid\u00eancias fotogr\u00e1ficas.<\/p>\r\n <\/div>\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">M\u00f3dulo atual<\/div>\r\n <h4>Baixador de Fotografias<\/h4>\r\n <p>Download em PDF com filtros avan\u00e7ados. Auditoria visual do estado real da g\u00f4ndola sem depender de relat\u00f3rios manuais.<\/p>\r\n <\/div>\r\n <div class=\"module-card\">\r\n <div class=\"module-kicker\">Em desenvolvimento<\/div>\r\n <h4>Smart Downloader<\/h4>\r\n <p>A pr\u00f3xima evolu\u00e7\u00e3o: KPIs inteligentes com IA incorporada para priorizar automaticamente os alertas com maior impacto nas vendas.<\/p>\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><polyline points=\"22 12 18 12 15 21 9 3 6 12 2 12\"\/><\/svg>\r\n <\/span>\r\n Como funciona: do campo \u00e0 decis\u00e3o\r\n <\/h2>\r\n\r\n <p class=\"reveal\">A promessa \u00e9 simples: que o analista comece a gerar insights desde o minuto um, e n\u00e3o a partir da hora sete.<\/p>\r\n\r\n <div class=\"process reveal scale-up\">\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">1<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Execu\u00e7\u00e3o em App Mobile<\/h4>\r\n <p>As equipes de campo concluem tarefas de *facing*, exposi\u00e7\u00e3o e promo\u00e7\u00e3o pelo aplicativo. Cada resposta \u00e9 sincronizada automaticamente ao fazer *check-out*, incluindo evid\u00eancias fotogr\u00e1ficas georreferenciadas.<\/p>\r\n <\/div>\r\n <\/div>\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">2<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Processamento no Datapipe<\/h4>\r\n <p>O motor de dados da Teamcore normaliza, enriquece e estrutura a informa\u00e7\u00e3o em tempo real, cruzando dados de execu\u00e7\u00e3o com sell-out, estoques e metas comerciais.<\/p>\r\n <\/div>\r\n <\/div>\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">3<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Parametriza\u00e7\u00e3o da consulta<\/h4>\r\n <p>A partir da plataforma web, o analista configura o seu download: tipo de tarefa, atributos de usu\u00e1rio, atributos de loja, produto at\u00e9 o n\u00edvel SKU e intervalo de tempo exato.<\/p>\r\n <\/div>\r\n <\/div>\r\n <div class=\"process-step\">\r\n <div class=\"process-num\">4<\/div>\r\n <div class=\"process-copy\">\r\n <h4>Download pronto para an\u00e1lise<\/h4>\r\n <p>A planilha de dados chega limpa, homologada e estruturada. Zero trabalho de prepara\u00e7\u00e3o. A equipe pode passar direto da evid\u00eancia \u00e0 a\u00e7\u00e3o.<\/p>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><polyline points=\"12 6 12 12 16 14\"\/><\/svg>\r\n <\/span>\r\n O custo real de n\u00e3o ter esses dados a tempo\r\n <\/h2>\r\n\r\n <p class=\"reveal\">Uma redu\u00e7\u00e3o de 1% na disponibilidade nas prateleiras pode representar milh\u00f5es em receita perdida por ano. Mas o preju\u00edzo n\u00e3o \u00e9 apenas econ\u00f4mico: cada dia sem visibilidade leva a equipe a agir de forma reativa, em vez de preventiva.<\/p>\r\n\r\n <div class=\"comparison reveal\">\r\n <div class=\"compare-card\">\r\n <div class=\"compare-label\">Sem automa\u00e7\u00e3o<\/div>\r\n <div class=\"compare-number\">7h 10m<\/div>\r\n <p>por semana apenas em gerenciamento, limpeza e homologa\u00e7\u00e3o de dados.<\/p>\r\n <\/div>\r\n <div class=\"compare-card dark\">\r\n <div class=\"compare-label\">Com a Teamcore<\/div>\r\n <div class=\"compare-number\">26m<\/div>\r\n <p>por cadeia toda semana. A diferen\u00e7a n\u00e3o est\u00e1 em fazer mais relat\u00f3rios; est\u00e1 em recuperar tempo para decidir.<\/p>\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"big-number reveal scale-up\">\r\n <div class=\"big-n\">93%<\/div>\r\n <div class=\"big-n-text\">\r\n <strong>de redu\u00e7\u00e3o no tempo de gest\u00e3o de dados.<\/strong> Em uma opera\u00e7\u00e3o com 9 redes, isso equivale a 3.150 horas recuperadas por ano para an\u00e1lise, prioriza\u00e7\u00e3o e a\u00e7\u00e3o no ponto de venda.\r\n <\/div>\r\n <\/div>\r\n\r\n <div class=\"insight reveal\">\r\n <div class=\"insight-label\">\r\n <svg width=\"14\" height=\"14\" viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.2\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><line x1=\"12\" y1=\"8\" x2=\"12\" y2=\"12\"\/><line x1=\"12\" y1=\"16\" x2=\"12.01\" y2=\"16\"\/><\/svg>\r\n O sinal de fundo\r\n <\/div>\r\n <p>Quando a informa\u00e7\u00e3o chega limpa e a tempo, muda a conversa: a equipe deixa de perguntar \u201co que aconteceu\u201d e come\u00e7a a decidir \u201co que fazemos agora\u201d. Essa diferen\u00e7a separa as opera\u00e7\u00f5es que reagem daquelas que previnem.<\/p>\r\n <\/div>\r\n\r\n <div class=\"divider\"><\/div>\r\n\r\n <h2 class=\"reveal\">\r\n <span class=\"h-icon\">\r\n <svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"#003670\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><line x1=\"18\" y1=\"20\" x2=\"18\" y2=\"10\"\/><line x1=\"12\" y1=\"20\" x2=\"12\" y2=\"4\"\/><line x1=\"6\" y1=\"20\" x2=\"6\" y2=\"14\"\/><\/svg>\r\n <\/span>\r\n O impacto global da Teamcore em n\u00fameros\r\n <\/h2>\r\n\r\n <p class=\"reveal\">A visibilidade operativa n\u00e3o apenas organiza a informa\u00e7\u00e3o. Ela tamb\u00e9m melhora a capacidade de recuperar vendas, sustentar a disponibilidade e resolver incid\u00eancias antes que escalem.<\/p>\r\n\r\n <div class=\"impact-grid stagger-group\">\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">+75%<\/div>\r\n <p>m\u00e9dia em vendas recuperadas com visibilidade operacional em tempo real.<\/p>\r\n <\/div>\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">6\u20139%<\/div>\r\n <p>de melhoria na disponibilidade de produtos na g\u00f4ndola.<\/p>\r\n <\/div>\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">\u221211,51 TP3T<\/div>\r\n <p>no tempo de resolu\u00e7\u00e3o de incidentes no ponto de venda.<\/p>\r\n <\/div>\r\n <div class=\"impact-card\">\r\n <div class=\"impact-number\">+23%<\/div>\r\n <p>de otimiza\u00e7\u00e3o do tempo da equipe no ponto de venda.<\/p>\r\n <\/div>\r\n <\/div>\r\n\r\n <p class=\"reveal\">Para uma opera\u00e7\u00e3o comercial, esses n\u00fameros significam menos tempo perdido em tarefas repetitivas e mais capacidade para agir onde a venda acontece: o ponto de venda, a g\u00f4ndola, a exposi\u00e7\u00e3o, o invent\u00e1rio e a visita da equipe de campo.<\/p>\r\n\r\n <p class=\"reveal\">Os dados j\u00e1 est\u00e3o a\u00ed. Est\u00e3o em cada visita, cada fotografia, cada tarefa conclu\u00edda, cada check-out, cada SKU com ruptura, cada evid\u00eancia que a equipe levanta em campo. A diferen\u00e7a est\u00e1 em quanto tempo demoram para se transformar em uma decis\u00e3o.<\/p>\r\n\r\n <div class=\"cta-block reveal scale-up\">\r\n <h2>Pronto para usar seus dados de campo a tempo?<\/h2>\r\n <p>Saiba como o Teamcore Data Extraction transforma a execu\u00e7\u00e3o em dados limpos, estruturados e acion\u00e1veis para as suas equipes comerciais.<\/p>\r\n <a href=\"https:\/\/teamcore.com\/pt\/contato\/\" class=\"cta-btn\">Falar com um especialista \u2192<\/a>\r\n <\/div>\r\n\r\n<\/article>\r\n\r\n<script>\r\n(function(){\r\n var io = new IntersectionObserver(function(entries){\r\n entries.forEach(function(e){\r\n if(e.isIntersecting){\r\n e.target.classList.add('is-visible');\r\n io.unobserve(e.target);\r\n }\r\n });\r\n },{threshold:0.1, rootMargin:'0px 0px -40px 0px'});\r\n document.querySelectorAll('.reveal,.stagger-group').forEach(function(el){ io.observe(el); });\r\n})();\r\n<\/script>\r\n\r\n<\/body>\r\n<\/html>\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div 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class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/el-torneo-empieza-tu-gondola-tambien-esta-jugando\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/friends-toasting-with-beer-watching-soccer-match-i-2026-03-24-12-58-09-utc-768x512.jpg\" alt=\"Jovem grupo de amigos assistindo esporte na televis\u00e3o\" width=\"768\" height=\"512\" title=\"Jovem grupo de amigos assistindo esporte na televis\u00e3o\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/el-torneo-empieza-tu-gondola-tambien-esta-jugando\/\"> <div class=\"uc_post_title\">O torneio come\u00e7ou. A sua g\u00f4ndola tamb\u00e9m est\u00e1 jogando.<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 25\/06\/2026<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >Temporada de futebol e a sua g\u00f4ndola \u2014 Teamcore Blog\n\n\n\n\n\n\n\n Retail & CPG \u00b7 Tend\u00eancias...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/el-torneo-empieza-tu-gondola-tambien-esta-jugando\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n<div class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-768x511.jpg\" alt=\"Cliente abrindo a porta da geladeira no supermercado, escolhendo mantimentos, comida saud\u00e1vel, conceito de compras\" width=\"768\" height=\"511\" title=\"Cliente abrindo a porta da geladeira no supermercado, escolhendo mantimentos, comida saud\u00e1vel, conceito de compras\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/\"> <div class=\"uc_post_title\">Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea os usar\u00e1?<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 08\/06\/2026<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea os usar\u00e1? \u2014 Teamcore Blog...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n<div class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/como-el-mundial-2026-esta-cambiando-la-ejecucion-en-retail-en-latam\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/04\/3-claves-para-entender-el-comportamiento-de-compra-del-consumidor-en-el-Canal-Tradicional-1-768x512.webp\" alt=\"3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional (1)\" width=\"768\" height=\"512\" title=\"3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional (1)\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/como-el-mundial-2026-esta-cambiando-la-ejecucion-en-retail-en-latam\/\"> <div class=\"uc_post_title\">Como o Torneo 2026 est\u00e1 mudando a execu\u00e7\u00e3o no varejo na Am\u00e9rica Latina<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 24\/04\/2026<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >Como o Grande Torneio de 2026 est\u00e1 mudando a execu\u00e7\u00e3o no varejo na Am\u00e9rica Latina\n \n Inscreva-se\n\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\nabril...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/como-el-mundial-2026-esta-cambiando-la-ejecucion-en-retail-en-latam\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n<div class=\"uc_image_carousel_container_holder uc_carousel_item ue-item\">\n \n <div class=\"uc_image_carousel_placeholder\">\n \n <a href=\"https:\/\/teamcore.com\/pt\/insights-propios-vs-estudios-externos-dos-fuentes-una-sola-decision\/\" style=\"display:block;\"> \n <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/04\/Insights-propios-vs-estudios-externos-768x512.webp\" alt=\"Insights pr\u00f3prios vs. estudos externos\" width=\"768\" height=\"512\" title=\"Insights pr\u00f3prios vs. estudos externos\"> \n \t\n <div class=\"ue_pos_carousel_image_overlay\"><\/div>\n <\/a> <\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div 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<\/div> \n\n \n <div class=\"uc_image_carousel_content\" >\n <div class=\"uc_image_carousel_content_holder\">\n\n \n\n <a class=\"uc_post_title-link\" href=\"https:\/\/teamcore.com\/pt\/3-claves-para-entender-el-comportamiento-de-compra-del-consumidor-en-el-canal-tradicional\/\"> <div class=\"uc_post_title\">3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional<\/div>\n <\/a> \n\n <div class=\"ue-meta-data\">\n <div class=\"ue-grid-item-meta-data ue-grid-item-meta-data--date\"><span class=\"ue-grid-item-meta-data-icon\"><i class='fas fa-calendar-week'><\/i><\/span> 14\/03\/2025<\/div> \n \n\t\t \n \n \n \n\n \n\n <\/div>\n <div class=\"uc_paragraph\" >3 chaves para entender o comportamento de compra do consumidor no Canal Tradicional\nA companhia...<\/div>\t\t <\/div>\n \n <div class=\"ue-item-btn-holder\"> \n <a target=\"_blank\" href=\"https:\/\/teamcore.com\/pt\/3-claves-para-entender-el-comportamiento-de-compra-del-consumidor-en-el-canal-tradicional\/\" class=\"uc_more_btn ue-dynamic-popup-single\">Leia mais<\/a>\n <\/div> \n <\/div> \n \n<\/div>\n\n <\/div>\t\n<\/div>\n\n\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea vai us\u00e1-los? \u2014 Blog da Teamcore: Execu\u00e7\u00e3o no Varejo \u00b7 Extra\u00e7\u00e3o de Dados \u00b7 Editorial da Teamcore \u00b7 Consumo de massa Seus dados de campo j\u00e1 est\u00e3o prontos. Quando voc\u00ea vai us\u00e1-los? A execu\u00e7\u00e3o no ponto de venda gera dados todos os dias. O problema \u00e9 que muitas opera\u00e7\u00f5es ainda os recebem tarde, incompletos ou desorganizados demais para serem transformados em decis\u00f5es. 7 min de leitura Dados e execu\u00e7\u00e3o comercial CPG \u00b7 Equipes de campo \u00b7 Varejo O problema n\u00e3o \u00e9 a falta de dados. \u00c9 a velocidade com que eles chegam at\u00e9 quem deve decidir. Apenas 12% dos varejistas transformam dados em a\u00e7\u00f5es preventivas. Os 88% restantes continuam operando com visibilidade parcial: identificam o problema quando a venda j\u00e1 foi perdida. Suas equipes j\u00e1 est\u00e3o gerando as informa\u00e7\u00f5es. O que falta \u00e9 transform\u00e1-la em a\u00e7\u00e3o antes que o ponto de venda cobre a conta. 12% dos varejistas transformam dados em a\u00e7\u00f5es preventivas. Mais de 7h s\u00e3o perdidas por rede a cada semana gerenciando, limpando e padronizando dados. ROI m\u00e9dio 10x maior quando o gargalo operacional \u00e9 eliminado. O problema silencioso que destr\u00f3i resultados S\u00e3o 8h da manh\u00e3. Seu produto estrela esgotou ontem em 15 pontos de venda importantes. Suas equipes est\u00e3o revisando rotas, a concorr\u00eancia est\u00e1 reabastecendo suas prateleiras e os consumidores est\u00e3o escolhendo outras marcas. Quando voc\u00ea descobre, j\u00e1 \u00e9 tarde demais. Essa cena n\u00e3o \u00e9 uma exce\u00e7\u00e3o: faz parte do dia a dia em muitas opera\u00e7\u00f5es de consumo de massa. As informa\u00e7\u00f5es sobre o que ocorre nas prateleiras chegam fragmentadas, atrasadas e com ru\u00eddo demais para que se possa agir. As equipes comerciais passam horas baixando arquivos, limpando bancos de dados, cruzando formatos e padronizando dados antes de chegar \u00e0 primeira an\u00e1lise real. O custo n\u00e3o est\u00e1 apenas no tempo perdido. Est\u00e1 nos produtos esgotados que s\u00e3o detectados tarde demais, nas promo\u00e7\u00f5es que ningu\u00e9m corrige a tempo, nas exposi\u00e7\u00f5es que s\u00e3o auditadas quando a campanha j\u00e1 terminou e nos espa\u00e7os que a concorr\u00eancia ocupa enquanto a equipe ainda tenta organizar as informa\u00e7\u00f5es. \u201cA diferen\u00e7a n\u00e3o foi que os problemas desapareceram. Foi que a equipe os identificou a tempo de fazer algo a respeito.\u201d \u2014 Caso de sucesso Teamcore \u00b7 Higiene e Beleza \u00b7 Peru 2025 O gargalo n\u00e3o est\u00e1 na qualidade de suas equipes. Est\u00e1 na dist\u00e2ncia entre os dados gerados em campo e as pessoas que precisam agir com base neles. O Teamcore Data Extraction existe para eliminar essa dist\u00e2ncia. O que \u00e9 o Teamcore Data Extraction O Data Extraction \u00e9 a camada de intelig\u00eancia operacional da plataforma Teamcore que transforma tudo o que acontece no ponto de venda \u2014 visitas, tarefas de execu\u00e7\u00e3o, evid\u00eancias fotogr\u00e1ficas, respostas de campo \u2014 em dados estruturados, baix\u00e1veis e acion\u00e1veis em tempo real. N\u00e3o \u00e9 um simples exportador de relat\u00f3rios. Funciona como um mecanismo de convers\u00e3o: pega a execu\u00e7\u00e3o dispersa de milhares de profissionais de merchandising e supervisores e a transforma em uma planilha de dados padronizada, filtr\u00e1vel e pronta para an\u00e1lise estrat\u00e9gica. M\u00f3dulo atual: Downloader Padr\u00e3o de KPIs de sell-out, estoques e m\u00e9tricas de disponibilidade hist\u00f3ricas. At\u00e9 2 anos de dados mais o per\u00edodo atual em uma \u00fanica consulta parametrizada. M\u00f3dulo atual: Downloader de Execu\u00e7\u00e3o. Planilha completa de respostas de campo: tipo de tarefa, usu\u00e1rio, loja, produto at\u00e9 o n\u00edvel de SKU, intervalo de tempo e links para evid\u00eancias fotogr\u00e1ficas. M\u00f3dulo atual: Downloader de Fotos \u2013 Download em PDF com filtros avan\u00e7ados. Auditoria visual do estado real da prateleira, sem depender de relat\u00f3rios manuais. Em desenvolvimento: Downloader Smart \u2013 A pr\u00f3xima evolu\u00e7\u00e3o: KPIs inteligentes com IA incorporada para priorizar automaticamente os alertas com maior impacto nas vendas. Como funciona: do campo \u00e0 decis\u00e3o A promessa \u00e9 simples: que o analista comece a gerar insights desde o primeiro minuto, n\u00e3o s\u00f3 a partir da s\u00e9tima hora. 1 Execu\u00e7\u00e3o no aplicativo m\u00f3vel As equipes de campo realizam tarefas de facing, exposi\u00e7\u00e3o e promo\u00e7\u00e3o diretamente pelo aplicativo. Cada resposta \u00e9 sincronizada automaticamente ao fazer o check-out, incluindo evid\u00eancias fotogr\u00e1ficas georreferenciadas. 2 Processamento no Datapipe O mecanismo de dados da Teamcore normaliza, enriquece e estrutura as informa\u00e7\u00f5es em tempo real, cruzando dados de execu\u00e7\u00e3o com vendas, estoques e metas comerciais. 3 Configura\u00e7\u00e3o da consulta A partir da plataforma web, o analista configura seu download: tipo de tarefa, atributos do usu\u00e1rio, atributos da loja, produto at\u00e9 o n\u00edvel de SKU e intervalo temporal exato. 4 Download pronto para an\u00e1lise A planilha de dados chega limpa, homologada e estruturada. Sem trabalho de prepara\u00e7\u00e3o. A equipe pode passar diretamente das evid\u00eancias para a a\u00e7\u00e3o. O custo real de n\u00e3o ter esses dados em tempo h\u00e1bil: uma redu\u00e7\u00e3o de 1% na disponibilidade nas prateleiras pode representar milh\u00f5es em receitas perdidas por ano. Mas o preju\u00edzo n\u00e3o \u00e9 apenas econ\u00f4mico: cada dia sem visibilidade leva a equipe a reagir, em vez de prevenir. Sem automa\u00e7\u00e3o: 7h 10m por rede por semana apenas em gerenciamento, limpeza e homologa\u00e7\u00e3o de dados. Com o Teamcore: 26m por rede por semana. A diferen\u00e7a n\u00e3o est\u00e1 em produzir mais relat\u00f3rios; est\u00e1 em recuperar tempo para decidir. Redu\u00e7\u00e3o de 93% no tempo de gerenciamento de dados. Em uma opera\u00e7\u00e3o com 9 linhas de produ\u00e7\u00e3o, isso equivale a 3.150 horas recuperadas por ano para an\u00e1lise, prioriza\u00e7\u00e3o e a\u00e7\u00e3o no ponto de venda. O recado fundamental: quando as informa\u00e7\u00f5es chegam organizadas e na hora certa, a conversa muda: a equipe deixa de perguntar \u201co que aconteceu\u201d e come\u00e7a a decidir \u201co que faremos agora\u201d. Essa diferen\u00e7a separa as opera\u00e7\u00f5es que reagem daquelas que previnem. O impacto global do Teamcore em n\u00fameros A visibilidade operacional n\u00e3o apenas organiza as informa\u00e7\u00f5es. Ela tamb\u00e9m melhora a capacidade de recuperar vendas, manter a disponibilidade e resolver incidentes antes que eles se agravem. +75%, em m\u00e9dia, em vendas recuperadas com visibilidade operacional em tempo real. 6\u20139% de melhoria na disponibilidade de produtos nas prateleiras. \u221211,5% no tempo de resolu\u00e7\u00e3o de incidentes no ponto de venda. +23% de otimiza\u00e7\u00e3o do tempo da equipe no ponto de venda. Para uma opera\u00e7\u00e3o comercial, esses n\u00fameros significam menos tempo perdido em tarefas repetitivas e mais capacidade de agir onde a venda realmente acontece: o ponto de venda,<\/p>","protected":false},"author":2,"featured_media":5708,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[8],"tags":[],"class_list":["post-5706","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"\n<title>Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? - Teamcore<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? - Teamcore\" \/>\n<meta property=\"og:description\" content=\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? \u2014 Teamcore Blog Retail Execution \u00b7 Data Extraction Teamcore Editorial \u00b7 Consumo masivo Tus datos de campo ya est\u00e1n listos.\u00bfCu\u00e1ndo los usar\u00e1s? La ejecuci\u00f3n en punto de venta genera datos todos los d\u00edas. El problema es que muchas operaciones todav\u00eda los reciben tarde, incompletos o demasiado desordenados para convertirlos en decisiones. 7 min de lectura Data & ejecuci\u00f3n comercial CPG \u00b7 Field Teams \u00b7 Retail El problema no es falta de datos Es la velocidad con la que llegan a quien debe decidir. Solo el 12% de los retailers convierte datos en acciones preventivas. El 88% restante sigue operando con visibilidad parcial: encuentra el problema cuando la venta ya se perdi\u00f3. Tus equipos ya est\u00e1n generando la informaci\u00f3n. Lo que falta es convertirla en acci\u00f3n antes de que el punto de venta cobre la factura. 12% de los retailers convierte datos en acciones preventivas. 7h+ se pierden por cadena cada semana gestionando, limpiando y homologando datos. 10x ROI promedio cuando se elimina el cuello de botella operativo. El problema silencioso que destruye resultados Son las 8:00 AM. Tu producto estrella se agot\u00f3 ayer en 15 puntos de venta clave. Tus equipos est\u00e1n revisando rutas, la competencia est\u00e1 reponiendo sus espacios, y los consumidores est\u00e1n eligiendo otras marcas. Para cuando te enteres, ya es demasiado tarde. Esta escena no es una excepci\u00f3n: es parte del d\u00eda a d\u00eda en muchas operaciones de consumo masivo. La informaci\u00f3n sobre lo que ocurre en la g\u00f3ndola llega fragmentada, tarde, y con demasiado ruido para actuar. Los equipos comerciales pasan horas descargando archivos, limpiando bases, cruzando formatos y homologando datos antes de llegar al primer an\u00e1lisis real. El costo no est\u00e1 solo en el tiempo perdido. Est\u00e1 en los agotados que se detectan tarde, en las promociones que nadie corrige a tiempo, en las exhibiciones que se auditan cuando ya termin\u00f3 la campa\u00f1a y en los espacios que la competencia ocupa mientras el equipo todav\u00eda intenta ordenar la informaci\u00f3n. \u201cLa diferencia no fue que los problemas desaparecieran. Fue que el equipo los vio a tiempo para hacer algo al respecto.\u201d \u2014 Caso de \u00e9xito Teamcore \u00b7 Higiene & Belleza \u00b7 Per\u00fa 2025 El cuello de botella no est\u00e1 en la calidad de tus equipos. Est\u00e1 en la distancia entre los datos que se generan en terreno y las personas que necesitan actuar sobre ellos. Teamcore Data Extraction existe para eliminar esa distancia. Qu\u00e9 es Teamcore Data Extraction Data Extraction es la capa de inteligencia operativa de la plataforma Teamcore que transforma todo lo que sucede en el punto de venta \u2014visitas, tareas de ejecuci\u00f3n, evidencias fotogr\u00e1ficas, respuestas de campo\u2014 en datos estructurados, descargables y accionables en tiempo real. No es un simple exportador de reportes. Funciona como un motor de conversi\u00f3n: toma la ejecuci\u00f3n dispersa de miles de mercaderistas y supervisores, y la transforma en una s\u00e1bana de datos homologada, filtrable y lista para el an\u00e1lisis estrat\u00e9gico. M\u00f3dulo actual Descargador Standard de KPIs Sell-out, inventarios y m\u00e9tricas de disponibilidad historizados. Hasta 2 a\u00f1os de datos m\u00e1s el per\u00edodo actual en una sola consulta parametrizada. M\u00f3dulo actual Descargador de Ejecuci\u00f3n S\u00e1bana completa de respuestas de campo: tipo de tarea, usuario, tienda, producto hasta nivel SKU, rango de tiempo y links a evidencias fotogr\u00e1ficas. M\u00f3dulo actual Descargador de Fotograf\u00edas Descarga en PDF con filtros avanzados. Auditor\u00eda visual del estado real de la g\u00f3ndola sin depender de reportes manuales. En desarrollo Descargador Smart La pr\u00f3xima evoluci\u00f3n: KPIs inteligentes con IA incorporada para priorizar autom\u00e1ticamente las alertas con mayor impacto en ventas. C\u00f3mo funciona: del campo a la decisi\u00f3n La promesa es simple: que el analista empiece a generar insights desde el minuto uno, no desde la hora siete. 1 Ejecuci\u00f3n en App Mobile Los equipos de campo completan tareas de facing, exhibici\u00f3n y promoci\u00f3n desde la app. Cada respuesta se sincroniza autom\u00e1ticamente al hacer check-out, incluyendo evidencias fotogr\u00e1ficas georreferenciadas. 2 Procesamiento en Datapipe El motor de datos de Teamcore normaliza, enriquece y estructura la informaci\u00f3n en tiempo real, cruzando datos de ejecuci\u00f3n con sell-out, inventarios y metas comerciales. 3 Parametrizaci\u00f3n de la consulta Desde la plataforma web, el analista configura su descarga: tipo de tarea, atributos de usuario, atributos de tienda, producto hasta nivel SKU y rango temporal exacto. 4 Descarga lista para el an\u00e1lisis La s\u00e1bana de datos llega limpia, homologada y estructurada. Cero trabajo de preparaci\u00f3n. El equipo puede pasar directo de la evidencia a la acci\u00f3n. El costo real de no tener estos datos a tiempo Un 1% menos de disponibilidad en g\u00f3ndola puede representar millones en ingresos perdidos al a\u00f1o. Pero el da\u00f1o no es solo econ\u00f3mico: cada d\u00eda sin visibilidad empuja al equipo hacia la reacci\u00f3n en lugar de la prevenci\u00f3n. Sin automatizaci\u00f3n 7h 10m por cadena cada semana solo en gesti\u00f3n, limpieza y homologaci\u00f3n de datos. Con Teamcore 26m por cadena cada semana. La diferencia no est\u00e1 en hacer m\u00e1s reportes; est\u00e1 en recuperar tiempo para decidir. 93% de reducci\u00f3n en tiempo de gesti\u00f3n de datos. En una operaci\u00f3n con 9 cadenas, eso equivale a 3.150 horas recuperadas al a\u00f1o para an\u00e1lisis, priorizaci\u00f3n y acci\u00f3n en punto de venta. La se\u00f1al de fondo Cuando la informaci\u00f3n llega limpia y a tiempo, cambia la conversaci\u00f3n: el equipo deja de preguntar \u201cqu\u00e9 pas\u00f3\u201d y empieza a decidir \u201cqu\u00e9 hacemos ahora\u201d. Esa diferencia separa a las operaciones que reaccionan de las que previenen. El impacto global de Teamcore en n\u00fameros La visibilidad operativa no solo ordena la informaci\u00f3n. Tambi\u00e9n mejora la capacidad de recuperar venta, sostener disponibilidad y resolver incidencias antes de que escalen. +75% promedio en venta recuperada con visibilidad operativa en tiempo real. 6\u20139% de mejora en disponibilidad de productos en g\u00f3ndola. \u221211.5% en tiempo de resoluci\u00f3n de incidencias en punto de venta. +23% de optimizaci\u00f3n del tiempo del equipo en el punto de venta. Para una operaci\u00f3n comercial, estos n\u00fameros significan menos tiempo perdido en tareas repetitivas y m\u00e1s capacidad para actuar donde se juega la venta: el punto de venta,\" \/>\n<meta property=\"og:url\" content=\"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/\" \/>\n<meta property=\"og:site_name\" content=\"Teamcore\" \/>\n<meta property=\"article:published_time\" content=\"2026-06-08T20:39:56+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-06-11T16:20:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1703\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Contacto\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Contacto\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\"},\"author\":{\"name\":\"Contacto\",\"@id\":\"https:\\\/\\\/teamcore.com\\\/#\\\/schema\\\/person\\\/9a2c803c1b62f1939d4d7b59c3eb7825\"},\"headline\":\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s?\",\"datePublished\":\"2026-06-08T20:39:56+00:00\",\"dateModified\":\"2026-06-11T16:20:03+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\"},\"wordCount\":1181,\"image\":{\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/teamcore.com\\\/wp-content\\\/uploads\\\/2026\\\/06\\\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg\",\"articleSection\":[\"Blog\"],\"inLanguage\":\"pt-BR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\",\"url\":\"https:\\\/\\\/teamcore.com\\\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\\\/\",\"name\":\"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? 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Quando voc\u00ea os usar\u00e1? - Teamcore","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/","og_locale":"pt_BR","og_type":"article","og_title":"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? - Teamcore","og_description":"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s? \u2014 Teamcore Blog Retail Execution \u00b7 Data Extraction Teamcore Editorial \u00b7 Consumo masivo Tus datos de campo ya est\u00e1n listos.\u00bfCu\u00e1ndo los usar\u00e1s? La ejecuci\u00f3n en punto de venta genera datos todos los d\u00edas. El problema es que muchas operaciones todav\u00eda los reciben tarde, incompletos o demasiado desordenados para convertirlos en decisiones. 7 min de lectura Data & ejecuci\u00f3n comercial CPG \u00b7 Field Teams \u00b7 Retail El problema no es falta de datos Es la velocidad con la que llegan a quien debe decidir. Solo el 12% de los retailers convierte datos en acciones preventivas. El 88% restante sigue operando con visibilidad parcial: encuentra el problema cuando la venta ya se perdi\u00f3. Tus equipos ya est\u00e1n generando la informaci\u00f3n. Lo que falta es convertirla en acci\u00f3n antes de que el punto de venta cobre la factura. 12% de los retailers convierte datos en acciones preventivas. 7h+ se pierden por cadena cada semana gestionando, limpiando y homologando datos. 10x ROI promedio cuando se elimina el cuello de botella operativo. El problema silencioso que destruye resultados Son las 8:00 AM. Tu producto estrella se agot\u00f3 ayer en 15 puntos de venta clave. Tus equipos est\u00e1n revisando rutas, la competencia est\u00e1 reponiendo sus espacios, y los consumidores est\u00e1n eligiendo otras marcas. Para cuando te enteres, ya es demasiado tarde. Esta escena no es una excepci\u00f3n: es parte del d\u00eda a d\u00eda en muchas operaciones de consumo masivo. La informaci\u00f3n sobre lo que ocurre en la g\u00f3ndola llega fragmentada, tarde, y con demasiado ruido para actuar. Los equipos comerciales pasan horas descargando archivos, limpiando bases, cruzando formatos y homologando datos antes de llegar al primer an\u00e1lisis real. El costo no est\u00e1 solo en el tiempo perdido. Est\u00e1 en los agotados que se detectan tarde, en las promociones que nadie corrige a tiempo, en las exhibiciones que se auditan cuando ya termin\u00f3 la campa\u00f1a y en los espacios que la competencia ocupa mientras el equipo todav\u00eda intenta ordenar la informaci\u00f3n. \u201cLa diferencia no fue que los problemas desaparecieran. Fue que el equipo los vio a tiempo para hacer algo al respecto.\u201d \u2014 Caso de \u00e9xito Teamcore \u00b7 Higiene & Belleza \u00b7 Per\u00fa 2025 El cuello de botella no est\u00e1 en la calidad de tus equipos. Est\u00e1 en la distancia entre los datos que se generan en terreno y las personas que necesitan actuar sobre ellos. Teamcore Data Extraction existe para eliminar esa distancia. Qu\u00e9 es Teamcore Data Extraction Data Extraction es la capa de inteligencia operativa de la plataforma Teamcore que transforma todo lo que sucede en el punto de venta \u2014visitas, tareas de ejecuci\u00f3n, evidencias fotogr\u00e1ficas, respuestas de campo\u2014 en datos estructurados, descargables y accionables en tiempo real. No es un simple exportador de reportes. Funciona como un motor de conversi\u00f3n: toma la ejecuci\u00f3n dispersa de miles de mercaderistas y supervisores, y la transforma en una s\u00e1bana de datos homologada, filtrable y lista para el an\u00e1lisis estrat\u00e9gico. M\u00f3dulo actual Descargador Standard de KPIs Sell-out, inventarios y m\u00e9tricas de disponibilidad historizados. Hasta 2 a\u00f1os de datos m\u00e1s el per\u00edodo actual en una sola consulta parametrizada. M\u00f3dulo actual Descargador de Ejecuci\u00f3n S\u00e1bana completa de respuestas de campo: tipo de tarea, usuario, tienda, producto hasta nivel SKU, rango de tiempo y links a evidencias fotogr\u00e1ficas. M\u00f3dulo actual Descargador de Fotograf\u00edas Descarga en PDF con filtros avanzados. Auditor\u00eda visual del estado real de la g\u00f3ndola sin depender de reportes manuales. En desarrollo Descargador Smart La pr\u00f3xima evoluci\u00f3n: KPIs inteligentes con IA incorporada para priorizar autom\u00e1ticamente las alertas con mayor impacto en ventas. C\u00f3mo funciona: del campo a la decisi\u00f3n La promesa es simple: que el analista empiece a generar insights desde el minuto uno, no desde la hora siete. 1 Ejecuci\u00f3n en App Mobile Los equipos de campo completan tareas de facing, exhibici\u00f3n y promoci\u00f3n desde la app. Cada respuesta se sincroniza autom\u00e1ticamente al hacer check-out, incluyendo evidencias fotogr\u00e1ficas georreferenciadas. 2 Procesamiento en Datapipe El motor de datos de Teamcore normaliza, enriquece y estructura la informaci\u00f3n en tiempo real, cruzando datos de ejecuci\u00f3n con sell-out, inventarios y metas comerciales. 3 Parametrizaci\u00f3n de la consulta Desde la plataforma web, el analista configura su descarga: tipo de tarea, atributos de usuario, atributos de tienda, producto hasta nivel SKU y rango temporal exacto. 4 Descarga lista para el an\u00e1lisis La s\u00e1bana de datos llega limpia, homologada y estructurada. Cero trabajo de preparaci\u00f3n. El equipo puede pasar directo de la evidencia a la acci\u00f3n. El costo real de no tener estos datos a tiempo Un 1% menos de disponibilidad en g\u00f3ndola puede representar millones en ingresos perdidos al a\u00f1o. Pero el da\u00f1o no es solo econ\u00f3mico: cada d\u00eda sin visibilidad empuja al equipo hacia la reacci\u00f3n en lugar de la prevenci\u00f3n. Sin automatizaci\u00f3n 7h 10m por cadena cada semana solo en gesti\u00f3n, limpieza y homologaci\u00f3n de datos. Con Teamcore 26m por cadena cada semana. La diferencia no est\u00e1 en hacer m\u00e1s reportes; est\u00e1 en recuperar tiempo para decidir. 93% de reducci\u00f3n en tiempo de gesti\u00f3n de datos. En una operaci\u00f3n con 9 cadenas, eso equivale a 3.150 horas recuperadas al a\u00f1o para an\u00e1lisis, priorizaci\u00f3n y acci\u00f3n en punto de venta. La se\u00f1al de fondo Cuando la informaci\u00f3n llega limpia y a tiempo, cambia la conversaci\u00f3n: el equipo deja de preguntar \u201cqu\u00e9 pas\u00f3\u201d y empieza a decidir \u201cqu\u00e9 hacemos ahora\u201d. Esa diferencia separa a las operaciones que reaccionan de las que previenen. El impacto global de Teamcore en n\u00fameros La visibilidad operativa no solo ordena la informaci\u00f3n. Tambi\u00e9n mejora la capacidad de recuperar venta, sostener disponibilidad y resolver incidencias antes de que escalen. +75% promedio en venta recuperada con visibilidad operativa en tiempo real. 6\u20139% de mejora en disponibilidad de productos en g\u00f3ndola. \u221211.5% en tiempo de resoluci\u00f3n de incidencias en punto de venta. +23% de optimizaci\u00f3n del tiempo del equipo en el punto de venta. Para una operaci\u00f3n comercial, estos n\u00fameros significan menos tiempo perdido en tareas repetitivas y m\u00e1s capacidad para actuar donde se juega la venta: el punto de venta,","og_url":"https:\/\/teamcore.com\/pt\/seus-dados-de-campo-ja-estao-prontos-quando-voce-vai-usa-los\/","og_site_name":"Teamcore","article_published_time":"2026-06-08T20:39:56+00:00","article_modified_time":"2026-06-11T16:20:03+00:00","og_image":[{"width":2560,"height":1703,"url":"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg","type":"image\/jpeg"}],"author":"Contacto","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Contacto","Est. reading time":"6 minutos"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/#article","isPartOf":{"@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/"},"author":{"name":"Contacto","@id":"https:\/\/teamcore.com\/#\/schema\/person\/9a2c803c1b62f1939d4d7b59c3eb7825"},"headline":"Tus datos de campo ya est\u00e1n listos. \u00bfCu\u00e1ndo los usar\u00e1s?","datePublished":"2026-06-08T20:39:56+00:00","dateModified":"2026-06-11T16:20:03+00:00","mainEntityOfPage":{"@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/"},"wordCount":1181,"image":{"@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/#primaryimage"},"thumbnailUrl":"https:\/\/teamcore.com\/wp-content\/uploads\/2026\/06\/customer-opening-refrigerator-door-in-supermarket-2026-03-26-10-36-51-utc-scaled.jpg","articleSection":["Blog"],"inLanguage":"pt-BR"},{"@type":"WebPage","@id":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/","url":"https:\/\/teamcore.com\/tus-datos-de-campo-ya-estan-listos-cuando-los-usaras\/","name":"Seus dados de campo j\u00e1 est\u00e3o prontos. 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