Pain Point #1: “I see many business owners who first tried running ads themselves, lost money, then hired someone, and they still didn’t perform” — Post 22 “spent $3K+ per month on ads in the home improvement space and ended up with no results at all?” — Post 41 “If referrals slowed down…what’s your reason for not using Google Ads?” — Post 46 Opportunity: Ads With a Warranty — Pay-per-Booked-Job for Home Services, or We Refund Our Fee - Verticalized acquisition for home improvement trades (roofing/HVAC/solar/plumbing): you own the ad accounts, we deploy proven creatives/keywords + LSA + call-only flows + call-rail verification + human qualification. You pay only for booked estimates that match pre-set criteria. If CPA exceeds the warrantied ceiling for the month, we refund our management fee. - Pricing: $2,000 setup + 15% of ad spend + $200–$350 per booked appointment (by trade/market) with a 10-appointment/month minimum. Optional “Spend Insurance” add-on (+8% of ad spend) that refunds our fee if booked-job count misses SLA. First 10 Customers: - Owners of roofing/HVAC/plumbing companies with 3–20 techs in metros where LSA is active and referrals have softened - Franchisees/regional managers in home services who have burned $3k+/mo on underperforming Meta/Google campaigns - Marketing directors at multi-location home services doing <$15M revenue who need guaranteed appointments during slow seasons MVP in 48 Hours: - Niche landing page for 1–2 trades in 1 metro, with clear guarantee, pricing, and qualifying checklist + Calendly - Set up CallRail with whisper, recordings, DNI; build a Google Sheet CRM; use Twilio SMS for confirmations - Launch templated Google LSA + call-only + branded search + competitor conquest; spin 10 proven creatives for Meta Lead Ads - Manually qualify every lead for 2 pilot clients; only bill for booked estimates; publish anonymized dashboard Justification (infer this in detail): - Demand: Multiple posts show acute frustration: “lost money…hired someone…still didn’t perform,” “$3K+ per month…no results,” and fear of referrals drying up. They don’t want another agency; they want booked jobs. - ROI: In roofing/HVAC, 1 closed job ($2k–$15k revenue) often covers an entire month’s fee. Paying $250 per booked estimate with 20% close rate yields $1,250 CAC on a $6k job—solid unit economics. - Scalable: Tight vertical focus + geo playbooks + shared creative library + standardized call qualification. 150 clients x 12 booked appts/mo x $250 = $450k MRR ($5.4M ARR) before ad-spend commissions. - Purple Cow/Controversial: An actual warranty in ads. Agencies hate guarantees; you embrace it with transparent tracking, your creatives, their ad accounts, and fee refunds when you miss SLAs. --- Pain Point #2: “Since traditional Google search is slowly declining and people are shifting to other platforms like ChatGPT and Perplexity” — Post 23 Opportunity: LLM-SEO (AIO): Get your brand “named by ChatGPT/Perplexity” on intent queries within 30 days, or you don’t pay - Offer a guaranteed “LLM discoverability sprint” that seeds authoritative, structured, sentiment-positive signals across the sources ChatGPT/Perplexity ingest (Reddit/Quora Q&A, niche directories, JSON-LD org/FAQ schema, citations, third-party reviews) and monitors weekly if the model now recommends the client for their top 10 commercial prompts. If not, refund or keep working free until it does. - Price: $2,500 setup + $750/month per location/brand; multi-location discount. First 10 Customers (specific): - Owner/GM at local travel/tour agencies with <20 employees and low organic traffic in competitive destinations - Practice managers at dental/med-spa/telehealth clinics in Tier-1 cities competing on discovery - Marketing leads at boutique B2B services (e.g., app dev shops, ERP implementers) who rely on inbound queries - D2C brand CMOs with <$5M ARR seeing flat Google traffic but high “chat assistant” usage among customers MVP in 48 Hours: - Build a one-page Webflow landing with 10-headline “LLM-mentions or free” guarantee + Calendly + Stripe - Spreadsheet: map top 25 “commercial intent” prompts (e.g., “best [service] in [city]”) - Run scripted weekly queries in ChatGPT and Perplexity; capture screenshots baseline vs. after - Execute manually: 20 authoritative citations, 5 Reddit/Quora answers seeded with brand proof, publish FAQ/How-to pages with JSON-LD, solicit 10 fresh third-party reviews; re-test models in 14–21 days - Share a before/after “LLM Mentions Report” as the deliverable Justification (infer this in detail): - Demand: The travel-agency founder explicitly pivoted because “traditional Google search is slowly declining.” If he’s succeeding, competitors will pay to catch up. Multiple posts ask how to get US clients or better leads (Posts 21, 46), confirming discovery pain. - ROI: If ChatGPT starts recommending a $1.5k-margin tour operator 2 extra times/month, that’s ~$3k/mo; a $750 retainer is a no-brainer. Similar math holds for dentists/med-spas (single case covers fee). - Scalable: Repeatable playbooks per vertical + offshore content ops + automated model monitoring = 200 clients at ~$750 MRR = $1.8M ARR with service margins >60%. - Purple Cow/Controversial: You’re openly “optimizing” LLM outputs—today’s equivalent of 2010 SEO, with a hard “named-by-ChatGPT” guarantee. That stance will polarize, but it’s the unfair advantage early buyers want. --- Pain Point #3: “I have created conversational bot system…it is failing in the application due to VRAM overflow (8 GB VRAM)…How do I quantize both these models from FP16 to Q8 or Q6 to manage the memory budget?” — Post 2 Opportunity: CompressLab – 8GB-Ready TTS/ASR in a Box - A done-for-you model compression and packaging service that takes your TTS/ASR stack and returns a production-ready Docker image that runs on 8–12 GB GPUs (or CPU fallback) via quantization (Q6/Q8), distillation, ONNX/TensorRT/ggml ports, and streaming chunking. Includes benchmarks, latency targets, and a minimal REST/gRPC API. - Price: $1,500 per model pack (ASR or TTS) or $2,500 for both, delivered in 5 business days; $149/month support and updates. “Fit-in-8GB or money-back” guarantee. First 10 Customers: - Founders/CTOs at seed-stage voicebot/contact-center startups deploying on Hetzner/OVH/Vultr with 8–16 GB GPUs - Indie devs/agencies building IVR/voice assistants who must run on client-side Jetsons/NUCs or single 3060s - Heads of Engineering at telehealth or logistics startups adding call transcription/voice alerts without $1k+/mo GPU bills - AI automation agencies offering call summaries who need to cut inference costs 50–80% MVP in 48 Hours: - Landing page + Typeform intake (model links, target latency, hardware) + deposit via Stripe - Prepare two public demo SKUs: faster-whisper (Q5/Q6) and a lightweight TTS (e.g., Coqui XTTS/GPT-SoVITS) with quantized builds; publish benchmark video running on 8GB 3060 - Use open-source toolchain (whisper.cpp/faster-whisper, onnxruntime, TensorRT, ggml) to compress a sample model; deliver a Dockerfile + API + latency readme - Slack/Discord for support; manual engineering behind the scenes Justification: - Demand: The exact quote shows a founder’s bot “failing…due to VRAM overflow (8 GB VRAM)” and a direct ask for FP16→Q8/Q6. This is widespread among budget builders in 2025. - ROI: Moving from FP16 on 24GB GPUs ($300–$1,200/mo) to Q6 on 8–12GB or CPU can save $200–$800/mo per service and unlock on-prem deals where cloud is banned. Latency improvements reduce call drops and increase CSAT. - Scalable: Productize per-model recipes, templatize Docker bundles, build a catalog of “known-good” compressed models. 400 packs/year at $1.5k average = $600k services, plus $149/mo support across 200 clients = $358k ARR. - Purple Cow/Controversial: Promise “Fit-in-8GB or money-back.” Most consultants won’t guarantee footprint and latency. You will, because you specialize and pre-bake kernels.