/* Shared case-study data, exposed globally so each page can render. */ window.CASE_STUDIES = { "ai-voice-agent": { slug: "ai-voice-agent", label: "Trading Coaching Business", descriptor: "High-ticket coaching · 30,000-person active list · Tested end-2025", headline: "We reactivated 2,825 idle leads with an AI voice agent — and generated $6,800 in 15 days.", heroStat: "14.9x ROI", cardTitle: "AI Voice Agent", cardMetric: "$457 → $6,800", cardBody: "2,825 dead leads contacted. 22 qualified appointments booked in 15 days. Cost per booked call: $200 → $20.", outcomes: [ { metric: "$457 in spend → $6,800 in revenue", context: "14.9x ROI in 15 days" }, { metric: "22 qualified appointments", context: "booked automatically by the agent" }, { metric: "Cost per booked call: $50–$200 → $20", context: "driven down by agent efficiency" }, { metric: "AI response rate 4.7% vs human 3.5%", context: "outperformed human setters" }, { metric: "Monthly setting cost: $3,000 → $500", context: "human-to-AI replacement" }, ], challenge: "The business had 2,825 leads sitting idle in their CRM — people who had purchased a low-ticket introductory course but never converted to the high-ticket program. Manual outbound calling was expensive, inconsistent, and demoralising for the team. The list was being ignored. Revenue was sitting uncollected.", solution: [ "Deployed an outbound AI voice agent trained on a proven appointment-setting script.", "Applied BANT qualification on every call — Budget, Authority, Need, Timing.", "Agent called each lead multiple times on a structured schedule — 11,423 total calls placed.", "When a lead qualified, the agent booked directly into the calendar without human involvement.", "Human closers handled only the booked, pre-qualified appointments.", "Full CRM integration — every call logged, tagged, and synced automatically.", ], tags: ["AI Voice Agents", "Dead Lead Reactivation", "CRM Integration"], videoUrl: "https://www.youtube.com/embed/hXljA_sSljY", }, "ai-email-engine": { slug: "ai-email-engine", label: "Trading Coaching Business", descriptor: "30,000-person list · Partner webinar promotion · $1,200 offer", headline: "We built an entire webinar follow-up sequence in 4 hours. It generated $85,532 in 30 days.", heroStat: "$85,532", cardTitle: "AI Email Engine", cardMetric: "$85,532 / 30 days", cardBody: "One webinar follow-up sequence built in 4 hours. 6,000-person list. $1,200 offer.", outcomes: [ { metric: "$85,532 in revenue", context: "from a single email sequence" }, { metric: "4 hours to build", context: "vs. 20–30 hours manually" }, { metric: "6,000 engaged subscribers", context: "converted from the 30,000 active list" }, { metric: "1h 50m webinar replay", context: "mined automatically with full chat log" }, { metric: "Human time: review only", context: "final editorial judgement, nothing else" }, ], challenge: "The business ran a partner webinar promoting a $1,200 offer. The follow-up sequence had to ship fast, while the webinar was still fresh. Manual copywriting at that pace meant either slow turnaround or generic output. Using AI without structured context produced copy that sounded nothing like the brand.", solution: [ "Built a 5-module AI email engine that processed the full webinar replay and chat log.", "AI extracted belief-shift moments, key objections, value-dense timestamps, and questions clustered by fit, complexity, and comparison.", "Human team made every editorial decision: what converts, what stays out, what to lead with.", "Sequence: belief shift, replay invite, objection handling, value delivery, ethical urgency close.", "Full sequence delivered in approximately 4 hours, reviewed and sent the same day.", ], tags: ["AI Email Automation", "Sales Copywriting Systems", "Revenue Operations"], videoUrl: null, imageUrl: "/assets/email-case-study.png", imageAlt: "Email campaign results — $85,532.97 revenue across 1,657 clicks from one webinar follow-up sequence", }, "ai-sales-manager": { slug: "ai-sales-manager", label: "High-Ticket Coaching & Consulting", descriptor: "Small sales team · $15,000–$30,000/month revenue stage", headline: "We automated sales call review for an entire team. Close rate went from 19% to 42%.", heroStat: "19% → 42%", cardTitle: "AI Sales Manager", cardMetric: "19% → 42%", cardBody: "Every sales call reviewed automatically. 10% of calls reviewed became 100% — without adding headcount.", outcomes: [ { metric: "Close rate: 19% → 42%", context: "team-wide improvement" }, { metric: "100% of calls reviewed", context: "up from 10% via manual review" }, { metric: "Feedback in minutes, not days", context: "delivered to reps via Slack" }, { metric: "Manager time redirected", context: "from reviewing to coaching" }, { metric: "Unlocked path past $100K/month", context: "via consistent rep performance" }, ], challenge: "The business had a performance consistency problem. Their best rep closed 30–40% of calls. The average rep closed 15–20%. Manual review covered only 10% of calls at best, feedback arrived days later, and quality swung with the manager's bandwidth. The gap between top and average performers cost real revenue every month.", solution: [ "Built an AI Sales Manager that reads the transcript of every sales call automatically.", "Scores rep performance and buyer readiness on every call.", "Checks script adherence step by step against the established sales framework.", "Produces instant coaching notes, rephrase suggestions, and a lead snapshot for follow-up.", "Posts analysis directly into Slack — reps and managers see feedback while the day is still fresh.", "Calls that never moved past intro or were reschedules get a short summary only.", ], tags: ["AI Sales Systems", "Call Analysis Automation", "Revenue Operations"], videoUrl: "https://www.youtube.com/embed/OXIF45DNZQU", }, "content-repurposing": { slug: "content-repurposing", label: "Coaching & Consulting Business", descriptor: "YouTube-first content strategy · Multi-platform distribution", headline: "One YouTube video now produces 20+ posts per week. Content costs dropped from $3,000 to $60 a month.", heroStat: "$3,000 → $60/mo", cardTitle: "Content Repurposing Engine", cardMetric: "$3,000 → $60 / mo", cardBody: "One YouTube video became 20+ platform posts per week. Team time: 40 hours/month → 6 hours.", outcomes: [ { metric: "Content cost: $3,000 → $60/mo", context: "team replaced with automation" }, { metric: "Team time: 40h → 6h/month", context: "founder only needs to record and approve" }, { metric: "1 video → 20+ posts/week", context: "native format per platform" }, { metric: "Authentic founder voice", context: "maintained across every platform" }, { metric: "Email + YouTube highest engagement", context: "validated by test output" }, ], challenge: "The business knew consistent content was essential but kept hitting the same two traps: either burning out writing separately for every platform, or outsourcing to a team whose output sounded nothing like the founder. A $3,000/month content team was producing inconsistent results with no clear ROI.", solution: [ "Built an n8n automation workflow that takes one YouTube video as the input.", "AI analyses the video, extracts key insights, and adapts the content to each platform's native format and audience expectations.", "Output: email newsletter, YouTube posts, Instagram content, X posts — all in the founder's verified tone.", "Google Sheet dashboard tracks every output and publishing status in one place.", "System refined over time: Instagram X-style posts underperformed; email and YouTube formats led engagement.", "Human involvement reduced to recording the original video and final approval.", ], tags: ["AI Content Automation", "Repurposing Systems", "n8n Workflows"], videoUrl: "https://www.youtube.com/embed/U6qiJbdq6Gw", }, "ai-qa-clone": { slug: "ai-qa-clone", label: "Online Coaching Business", descriptor: "Flagship course with live group Q&A model · Multi-year content library", headline: "We cloned the coach's expertise into an AI. 9 out of 10 responses matched live coaching quality.", heroStat: "9/10 quality match", cardTitle: "AI Q&A Clone", cardMetric: "9/10 quality", cardBody: "AI coach deployed inside the course portal, answering student questions 24/7. 88% rated answers Excellent or Good.", outcomes: [ { metric: "9 / 10 responses matched live quality", context: "validated by existing clients" }, { metric: "88% rated Excellent or Good", context: "by actual students" }, { metric: "Q&A: weekly → 24/7", context: "always-on support" }, { metric: "Live calls freed up", context: "for high-value coaching only" }, { metric: "New monetisation paths unlocked", context: "without founder time" }, ], challenge: "The business ran a course-plus-live-Q&A model. Most student questions were repetitive — the answers already existed inside the course. But the founder still spent significant time on weekly Q&A calls. Students waited days for answers. Founder burnout was building and live calls were being diluted by questions that didn't need a human.", solution: [ "Built an AI clone of the coach trained on flagship program content and a multi-year library of historical Q&A recordings.", "Deployed as a widget inside the existing course portal — always available, no new platform needed.", "Students submit questions using a structured format: current situation → desired situation → specific question.", "AI answers in the coach's authentic tone and links directly to the exact lesson that addresses the question.", "System validated against the existing client base before full rollout.", "Live calls reserved exclusively for deep strategy, complex personal cases, and live implementations.", ], tags: ["AI Delivery Systems", "Coach Clone", "Course Automation"], videoUrl: "https://www.youtube.com/embed/wD6k3140R7k", }, }; window.CASE_STUDIES_ORDER = [ "ai-voice-agent", "ai-email-engine", "ai-sales-manager", "content-repurposing", "ai-qa-clone", ];