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It should measure how they *actually feel*. Emotion Logic decodes involuntary vocal acoustics to reveal genuine passion, indifference, and emotional resonance."}),e.jsxs("div",{className:"flex flex-col gap-3",children:[e.jsxs("a",{href:"https://app.emotionlogic.ai/register",target:"_blank",rel:"noopener noreferrer",className:"min-h-[48px] w-full bg-purple-600 text-white rounded-2xl font-bold active:scale-[0.98] transition-transform shadow-lg flex items-center justify-center gap-2 text-sm",children:["Open Free Account ",e.jsx(i,{className:"w-4 h-4"})]}),e.jsx(l,{to:"/ai-faq",className:"min-h-[48px] w-full border border-black/10 dark:border-white/20 bg-black/5 dark:bg-white/5 text-black dark:text-white rounded-2xl font-bold active:scale-[0.98] transition-transform flex items-center justify-center text-sm",children:"Emotion Logic FAQ"})]}),e.jsx("p",{className:"mt-4 text-[12px] text-black/50 dark:text-white/50 text-center",children:"Get free credits on signup. No commitment required."})]})]}),e.jsx("section",{className:"py-16 bg-theme-main relative overflow-hidden border-t border-theme-subtle",children:e.jsxs("div",{className:"px-4",children:[e.jsxs("h2",{className:"text-3xl font-black mb-6 leading-tight tracking-tight italic",children:["Passion is not ",e.jsx("br",{}),"an Emoji."]}),e.jsx("p",{className:"text-base text-black/70 dark:text-white/70 mb-8 leading-relaxed",children:"Traditional surveys capture what people choose to say. But according to Harvard Business Sc
1hool Professor Gerald Zaltman, up to 95% of purchasing decisions happen below conscious awareness - driven by emotions people can't articulate in a text field or a 1-to-5 scale. Emotion Logic reads these hidden signals directly from the voice, giving researchers an authentic layer of emotional data that no survey can capture."}),e.jsxs("div",{className:"relative rounded-[2rem] overflow-hidden shadow-xl mb-8",children:[e.jsx("img",{src:"/market_research_emotion.png",alt:"Focus group expressing genuine emotions",className:"w-full aspect-[4/3] object-cover"}),e.jsx("div",{className:"absolute inset-0 bg-gradient-to-t from-black/90 via-black/40 to-transparent"}),e.jsxs("div",{className:"absolute bottom-0 left-0 right-0 p-6",children:[e.jsx("p",{className:"text-white/90 italic leading-relaxed text-[13px] mb-3 font-medium",children:`"There was a clear gap between customers' expressed reactions and their actual level of satisfaction. Voice analysis revealed what surveys never could."`}),e.jsx("div",{className:"text-[10px] font-mono uppercase tracking-[0.1em] font-bold text-purple-400",children:"- Senior MR Director"})]})]}),e.jsxs("div",{className:"flex flex-col gap-4",children:[e.jsxs("div",{className:"flex items-start gap-3 p-4 rounded-2xl bg-theme-secondary border border-theme-subtle",children:[e.jsx(a,{className:"w-5 h-5 text-purple-600 shrink-0 mt-0.5"}),e.jsx("span",{className:"text-sm font-bold text-black dark:text-white leading-tight",children:"Automated Audio Transcription & Analysis"})]}),e.jsxs("div",{className:"flex items-start gap-3 p-4 rounded-2xl bg-theme-secondary border border-theme-subtle",children:[e.jsx(a,{className:"w-5 h-5 text-purple-600 shrink-0 mt-0.5"}),e.jsx("span",{className:"text-sm font-bold text-black dark:text-white leading-tight",children:"Real-time Consumer Confidence Index"})]}),e.jsxs("div",{className:"flex items-start gap-3 p-4 rounded-2xl bg-theme-secondary border border-theme-subtle",children:[e.jsx(a,{className:"w-5 h-5 text-purple-600 shrink-0 mt-0.5"}),e.jsx("span",{className:"text-sm font-bold text-black dark:text-white leading-tight",children:"Topic-Specific Emotional Heatmapping"})]})]})]})}),e.jsx("section",{className:"py-16 bg-theme-secondary/30 border-y border-theme-subtle",children:e.jsx("div",{className:"px-4",children:e.jsxs("div",{className:"flex flex-col gap-6",children:[e.jsxs("div",{className:"p-6 rounded-[2rem] bg-theme-secondary border border-theme-subtle shadow-sm flex gap-4",children:[e.jsx("div",{className:"w-12 h-12 rounded-xl bg-purple-500/10 flex items-center justify-center shrink-0",children:e.jsx(c,{className:"w-6 h-6 text-purple-600"})}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-lg font-bold mb-2",children:"Emotional Resonance"}),e.jsx("p",{className:"text-black/60 dark:text-white/60 text-[13px] leading-relaxed",children:"Measure the depth of connection between consumer and brand. Identify the specific phrases and topics that trigger genuine resonance or unseen frustration."})]})]}),e.jsxs("div",{className:"p-6 rounded-[2rem] bg-theme-secondary border border-theme-subtle shadow-sm flex gap-4",children:[e.jsx("div",{className:"w-12 h-12 rounded-xl bg-pink-500/10 flex items-center justify-center shrink-0",children:e.jsx(k,{className:"w-6 h-6 text-pink-600"})}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-lg font-bold mb-2",children:"Sentiment Integrity"}),e.jsx("p",{className:"text-black/60 dark:text-white/60 text-[13px] leading-relaxed",children:`Filters out 'Social Desirability Bias'. When consumers say they "love the product" but their voice shows indifference, we flag the truth for better data accuracy.`})]})]}),e.jsxs("div",{className:"p-6 rounded-[2rem] bg-theme-secondary border border-theme-subtle shadow-sm flex gap-4",children:[e.jsx("div",{className:"w-12 h-12 rounded-xl bg-indigo-500/10 flex items-center justify-center shrink-0",children:e.jsx(N,{className:"w-6 h-6 text-indigo-600"})}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-lg font-bold mb-2",children:"Predictive Analytics"}),e.jsx("p",{className:"text-black/60 dark:text-white/60 text-[13px] leading-relaxed",children:"Combine emotional data with historical behavior to predict market shifts and product success with unprecedented accuracy."})]})]})]})})}),e.jsx("section",{className:"py-16 bg-theme-main border-b border-theme-subtle",children:e.jsxs("div",{className:"px-4",children:[e.jsxs("div",{className:"mb-10 text-center",children:[e.jsxs("div",{className:"inline-flex items-center gap-1.5 px-3 py-1 rounded-full border border-purple-500/30 bg-purple-500/10 text-[11px] font-mono text-purple-600 dar
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1k:text-purple-400 mb-1 ml-4 pt-4",children:"Step 01"}),e.jsx("h3",{className:"text-xl font-bold mb-2 text-black dark:text-white ml-4",children:"Input"}),e.jsx("p",{className:"text-[13px] text-black/60 dark:text-white/60 leading-relaxed ml-4",children:"Capture focus group discussions, phone interviews, consumer sessions, or use AppTone voice questionnaires. Any audio source works."})]}),e.jsxs("div",{className:"relative pl-10 pr-2",children:[e.jsx("div",{className:"absolute left-[-2rem] top-2 w-16 h-16 rounded-2xl bg-theme-main border-2 border-pink-500/30 flex items-center justify-center shadow-lg mx-auto z-10 shrink-0",children:e.jsx(v,{className:"w-7 h-7 text-pink-500"})}),e.jsx("div",{className:"text-[10px] font-black uppercase tracking-[0.2em] text-pink-600 dark:text-pink-400 mb-1 ml-4 pt-4",children:"Step 02"}),e.jsx("h3",{className:"text-xl font-bold mb-2 text-black dark:text-white ml-4",children:"Analyze"}),e.jsx("p",{className:"text-[13px] text-black/60 dark:text-white/60 leading-relaxed ml-4",children:"Emotion Logic engines automatically extract emotional biomarkers, transcribe content, and map sentiment to every phrase."})]}),e.jsxs("div",{className:"relative pl-10 pr-2",children:[e.jsx("div",{className:"absolute left-[-2rem] top-2 w-16 h-16 rounded-2xl bg-theme-main border-2 border-indigo-500/30 flex items-center justify-center shadow-lg mx-auto z-10 shrink-0",children:e.jsx(w,{className:"w-7 h-7 text-indigo-500"})}),e.jsx("div",{className:"text-[10px] font-black uppercase tracking-[0.2em] text-indigo-600 dark:text-indigo-400 mb-1 ml-4 pt-4",children:"Step 03"}),e.jsx("h3",{className:"text-xl font-bold mb-2 text-black dark:text-white ml-4",children:"Insight"}),e.jsx("p",{className:"text-[13px] text-black/60 dark:text-white/60 leading-relaxed ml-4",children:"By aggregating emotional responses and putting them in context, a unique set of insights can be created - second to none."})]})]})]})}),e.jsx("section",{className:"py-16 bg-theme-main border-b border-theme-subtle",children:e.jsxs("div",{className:"px-4",children:[e.jsxs("div",{className:"mb-10 text-center",children:[e.jsxs("div",{className:"inline-flex items-center gap-1.5 px-3 py-1 rounded-full border border-purple-500/30 bg-purple-500/10 text-[11px] font-mono text-purple-600 dark:text-purple-400 mb-4",children:[e.jsx(y,{className:"w-3 h-3"})," USE CASES"]}),e.jsx("h2",{className:"text-3xl font-bold tracking-tight text-black dark:text-white leading-[1.1] mb-4",children:"Where Voice Meets Insight."}),e.jsx("p",{className:"text-[14px] text-black/60 dark:text-white/60 leading-relaxed",children:"Every time a consumer speaks, they reveal more than words. Use Emotion Logic across multiple scenarios."})]}),e.jsx("div",{className:"flex flex-col gap-4",children:[{icon:S,title:"Focus Groups",desc:"Analyze recorded discussions to uncover the real emotional reaction - not just the loudest voice in the room.",color:"purple"},{icon:c,title:"Brand Perception",desc:"Measure authentic emotional connection to brand names. Detect passion, indifference, and concealed aversion.",color:"pink"},{icon:T,title:"Product Testing",desc:"When testers say 'it's nice' - do they mean it? Voice analysis reveals genuine excitement vs. polite approval.",color:"indigo"},{icon:A,title:"Ad Testing",desc:"Test campaign concepts before launch. Measure real emotional arousal to visual and audio stimuli.",color:"purple"},{icon:E,title:"Political Polling",desc:"Decode genuine candidate enthusiasm, undecided voter anxiety, and emotional weight behind policy preferences.",color:"pink"},{icon:I,title:"CSAT",desc:"Transform NPS scores into real emotional data. 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