How It Works
FAQ: The Deep Questions CMOs Actually Ask
Q: Can't I just use ChatGPT to analyze my customer reviews?
A: ChatGPT is a general-purpose writing tool. Jeenyus.ai is a specialized Analytics Infrastructure.
Key differences:
  • Accuracy: ChatGPT hallucinates. Our models are trained specifically for intent classification, sentiment synthesis, and objection extraction—then verified by human analysts.
  • Scale: ChatGPT can process a few hundred reviews. We process tens of thousands across multiple sources simultaneously.
  • Integration: ChatGPT gives you text. We give you CRM tags, creative briefs, and predictive churn scores that plug directly into your existing workflow.
  • Verification: We map every qualitative insight to your quantitative data. If it doesn't correlate with revenue, we don't report it.
Think of it this way: ChatGPT is a calculator. We're the accounting department.
Q: Why do I need this if I have Google Analytics?
A: Google Analytics tells you where they clicked. We tell you why they clicked—and why they didn't.
What GA measures:
  • Traffic sources
  • Bounce rates
  • Conversion funnels
  • Time on page
What GA can't measure:
  • Why Feature A converts better than Feature B
  • What objection is killing your landing page
  • Which creative elements resonate vs. which are ignored
  • What customers wished you offered
You can't fix a narrative problem with a traffic report. They're complementary tools serving different purposes.
Q: Is our data secure? What happens to our customer information?
A: Security is our baseline, not a feature.
Our Zero-Retention Model:
  1. PII scrubbed locally before data enters our system (names, emails, phone numbers automatically redacted)
  1. AES-256 encryption for all data in transit and at rest
  1. No raw data storage — we only retain aggregated linguistic patterns, never individual conversations
  1. GDPR & CCPA compliant infrastructure
  1. SOC 2 Type II aligned security protocols
  1. Audit logs for every data access point
What we analyze: Patterns, themes, behavioral clusters
What we never see: Individual customer identities
Q: How long until we see results?
A: Depends on the suite and your current baseline.
Performance Engine: Most brands see CAC reduction within 30–60 days of implementing Signal-Dense creative. The algorithm learning phase accelerates immediately.
Narrative Intelligence: Messaging shifts take 60–90 days to fully manifest (rewrite copy, update assets, train sales team). But brands typically see landing page conversion lifts within the first month.
Lifecycle Enricher: Predictive churn alerts begin within 45 days of integration. LTV impact compounds over 6–12 months as you prevent more exits.
The "Signal Dividend"—measurable ROI from reduced Learning Tax—typically appears in 7–14 days once signal-dense creative goes live.
Q: We already have a data team. Why can't they do this?
A: They probably could—if they had 6 months, specialized NLP infrastructure, and no other responsibilities.
Why internal teams struggle with unstructured data:
  • Most data teams manage SQL databases and BI dashboards (structured data). Processing 50,000 support tickets requires different infrastructure and skill sets.
  • It's a one-time project for you, but it's all we do. We've built the models, workflows, and verification frameworks over hundreds of engagements.
  • Your team's time is better spent on execution, not months of data pipeline development.
We act as an Intelligence Extension for your existing team, providing the qualitative layer they're missing so they can focus on activation.
Q: How do we get our data to you safely?
A: Three integration methods, your choice:
  1. Secure API Handshake: View-only access to your tools (Zendesk, Shopify, Meta Ads, etc.) via OAuth
  1. SFTP Transfer: Encrypted file uploads for legacy systems or custom databases
  1. Cloud-to-Cloud Integration: Direct connection via Snowflake, BigQuery, AWS S3, or Azure
We're platform-agnostic. If you have text data, we can synthesize it.
Q: What exactly is the "Signal Dividend"?
A: The measurable ROI from reducing your "Learning Tax."
When you launch generic creative, modern ad algorithms enter expensive "learning phases" where they spend your budget testing thousands of people until they stumble onto someone who cares.
The math:
  • Average learning phase: 7–14 days
  • Typical wasted spend: 30–50% of budget during this period
  • For a brand spending $50K/month on Meta: $15K–$25K wasted every campaign
Signal-Dense creative bypasses this by feeding the algorithm high-resonance hooks from day one. The platform matches intent immediately instead of guessing.
The Signal Dividend is the money you stop wasting. Most clients recoup their Jeenyus investment in the first 30–45 days from Learning Tax savings alone—before accounting for sustained lower CAC.
Q: Do you need access to our ad accounts to make this work?
A: No. We work with unstructured data exports or API connections to support/CRM tools.
We provide the intelligence. You execute.
Typical workflow:
  1. We deliver Signal-Dense Briefs showing exactly what hooks, messaging, and creative elements to use
  1. Your internal team (or agency) builds the assets
  1. You launch via your existing ad accounts
  1. We monitor performance and refine recommendations weekly/monthly
We never touch your ad spend or login credentials.
Q: How is this different from traditional sentiment analysis?
A: Sentiment analysis tells you if customers are "Happy" or "Sad." We tell you what to do about it.
Traditional sentiment analysis:
  • Output: "70% positive, 20% neutral, 10% negative"
  • Action: ¯_(ツ)_/¯
Jeenyus Synthesis:
  • Output: "Customers mentioning 'setup complexity' in support tickets within 14 days have 73% higher churn. Trigger proactive outreach at day 10 with this specific messaging framework."
  • Action: Concrete, revenue-driving intervention
We don't just report sentiment. We synthesize strategy.
Q: What if our industry is too niche? Will this still work?
A: Especially effective in niche industries.
Why? Less noise. More signal density. Your customers use highly specific language that generic tools miss but that's gold for algorithms.
We've worked with brands in:
  • Industrial B2B manufacturing
  • Specialty healthcare devices
  • Boutique financial services
  • Regional consumer products
  • Technical SaaS for niche verticals
Niche = fewer competitors doing this = bigger first-mover advantage.
Q: Can you work with our existing agency/marketing team?
A: Absolutely. We're designed to enhance, not replace.
Common setups:
  • With agencies: We provide the intelligence layer (what to say, who to target), they execute the creative and media buying
  • With in-house teams: We deliver strategic briefs, they implement across channels
  • With fractional CMOs: We provide the data backbone for strategic decision-making
We're Switzerland. We make everyone better at their jobs.
Q: What size company is this built for?
A: Mid-market brands: $2M–$50M annual revenue.
Why this range?
Too small (under $2M): May not have enough data volume or marketing infrastructure to extract full value
Just right ($2M–$50M):
  • Enough data to mine meaningful patterns
  • Established marketing function (ads, CRM, support infrastructure)
  • Budget to invest in growth but not Fortune 500 data science teams
  • High growth potential from operational efficiency gains
Too large ($50M+): Often have internal data science teams, though we do work with enterprise brands on specific projects
Q: What happens after the 30-day pilot?
A: Three paths:
  1. Continue with one suite ($1,500–$2,500/month depending on scope)
  1. Expand to multiple suites for compounding intelligence across performance, brand, and retention
  1. Graduate to enterprise engagement with dedicated analyst support and custom modeling
No long-term contracts. Month-to-month after pilot. You stay because it works, not because you're locked in.
Q: What do you need from us to get started?
A: Surprisingly little.
Minimum requirements:
  • Access to 1–2 data sources (support desk, ad platform, review site, CRM)
  • 3–6 months of historical data (more is better)
  • 30-minute kickoff call to align on goals and KPIs
  • Contact at your company for questions during analysis
We handle the rest. Integration, processing, analysis, synthesis, delivery.
Q: What if the insights you find don't match our brand strategy?
A: Then your brand strategy is probably wrong.
We're not here to validate assumptions. We're here to show you what customers actually think vs. what you hope they think.
The hard truth: Most narrative friction comes from brands promoting what they want to be known for rather than what customers actually value.
The opportunity: When you align messaging with market reality, everything gets easier. Lower CAC. Higher conversion. Better retention. Less friction.
We deliver evidence, not opinions. What you do with it is your call—but the data doesn't lie.
Q: Can you guarantee specific results?
A: No one can guarantee marketing outcomes. Anyone who does is lying.
What we can guarantee:
  • Insights backed by statistically significant data
  • Human-verified analysis (not raw AI output)
  • Actionable recommendations you can implement immediately
  • Transparent methodology you can audit
  • Clear correlation between our insights and your business metrics
What we've seen across 100+ engagements:
  • 85% of clients see measurable CAC reduction within 60 days
  • 90% report improved message resonance
  • 78% identify churn signals they'd previously missed
But your results depend on execution. We provide the intelligence. You (or your team) activate it.
Q: How do you ensure the AI doesn't "make up" insights?
A: Double verification. Our AI identifies patterns; our analysts verify them against your structured data. Does this "Linguistic Trigger" actually appear in high-ROAS ad sets? If the data doesn't back it up, it doesn't make the report.
Q: Is this just a fancy version of ChatGPT for my data?
A: No. ChatGPT is a generative tool. Jeenyus.ai is a Synthesis Engine. We don't generate text; we map behavioral cues to financial outcomes. We use specialized models optimized for sentiment, intent classification, and objection extraction—all overseen by data scientists.
Q: We already have a data team. Why do we need Jeenyus.ai?
A: Most internal data teams are overwhelmed managing SQL databases and BI dashboards. Processing 50,000 support tickets or 100,000 Reddit comments requires different infrastructure and expertise. We act as an Intelligence Extension, providing the qualitative layer your team is missing.
Q: How do we get our data to you safely?
A: Three integration methods:
  1. Secure API Handshake: View-only access to tools (Zendesk, Shopify, Meta)
  1. SFTP Transfer: Encrypted file uploads for legacy systems
  1. Cloud-to-Cloud: Direct connection via Snowflake, BigQuery, or AWS
Q: What is the "Signal Dividend"?
A: The measurable ROI from reducing your Learning Tax. When your creative is signal-dense, algorithms spend less time and money "guessing" your audience. Most clients see 20–40% CAC reduction within 60 days.
Q: Do you need access to our ad accounts?
A: No. We work with unstructured data exports or API connections to support/CRM tools. We provide the intelligence; you execute.
Q: How is this different from sentiment analysis?
A: Traditional sentiment tells you if a customer is "Happy" or "Sad." We tell you exactly which words and intentions will lower your CAC and prevent churn. We don't just report sentiment. We synthesize strategy.
Ready to See What's Hidden in Your Data?
Your competitors are either already mining their unstructured data or about to start. Every quarter you wait, the gap widens.
Let's Get Started
Free Discovery Session: We'll review your "dark" data channels, provide a Dark Data Potential Score and show you one 'Ghost Objection' you didn't know existed. No cost. No obligation.
Schedule Free Discovery Call or Email: ​ambar@jeenyus.ai​ for more information.