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healthtech-gtm-consulting

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B2C GTM consulting engagement — AI health-tech startup | Primary research n=30 | Wedge strategy, behavioral adoption model, unit economics | Rutgers MSMAI Capstone 2026

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# HealthTech GTM Consulting — B2C Awareness, Adoption & Growth Strategy

**12-week B2C go-to-market engagement** for an AI health-tech startup in the cognitive aging space. Rutgers MSMAI Capstone, Spring 2026. Engagement lead: Sahifa Pervaiz (6-person team).

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## The Business Problem

An AI platform for family caregivers — designed to detect early cognitive decline and generate an Aging In Place Score™ — had validated product-market fit but zero market traction. 100% of primary research respondents rated the core product concept useful (mean 4.04/5, n=27). The problem was not the product. The problem was that discovery solves only 20% of the adoption challenge. The rest is behavioral friction, clinical GTM complexity, and the absence of a focused market entry strategy.

**The brief:** Build a complete B2C strategy from zero — primary research to 90-day execution roadmap — that a CEO could defend against board-level scrutiny.

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## My Role

Engagement lead on a 6-person Rutgers consulting team. Responsible for research design, primary survey execution (n=30), strategic synthesis, unit economics modeling, and final deliverable quality.

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## What We Built

### 1. Primary Research — 30 NJ Caregiver Interviews

Designed and administered a 24-question Qualtrics survey with adult-child caregivers in New Jersey. Key findings that shaped the entire strategy:

| Finding | Strategic Implication |
|---|---|
| 40% triggered by cognitive decline (Q5) | Defines the beachhead segment |
| 52% cite cost as hesitation (Q17) | Freemium model is mandatory, not optional |
| 44% cite data privacy (Q17) | Onboarding friction is behavioral, not messaging |
| 59% go to doctor first (Q10) | Clinical referral is a primary channel, not secondary |
| 85% open to a free first score (Q21) | Freemium conversion model validated |
| 78% female, 48% HHI $150K+ (Q22–24) | Buyer persona locked: high-income adult daughter |

### 2. Wedge Strategy — Beachhead Market Definition

Evaluated three candidate wedges against CAC efficiency, product-market fit, and LTV runway:

- **Post-hospital discharge families** — highest activation, but 6–18 month hospital sales cycle makes it the wrong *starting* wedge
- **Early cognitive decline families in NJ** ✅ *Recommended* — 40% of survey triggered here, longest engagement runway, highest emotional urgency, most defensible product advantage
- **High-income urban NJ/NYC caregivers** — strong secondary wedge after social proof is established

The strategic principle: *start narrow → build proof → expand with lower CAC.*

### 3. Messaging Architecture — 3-Layer Behavioral Model

Caregiving decisions are driven by guilt, identity, and denial — not rational decision-making. Fear-only messaging works for clicks but increases anxiety and drives churn. We built a three-layer emotional model:

- **Layer 1 — Fear & Guilt** ("Don't miss the signs") — top-of-funnel, Google Ads, scroll-stops
- **Layer 2 — Identity & Reassurance** ("You're the kind of family that catches things early") — landing page hero, onboarding, score delivery
- **Layer 3 — Trust & Low Commitment** ("A quick look. Nothing to decide yet.") — testimonials, clinical proof

The identity layer is the retention driver. *"I am a good daughter who catches things early"* is a self-concept — once formed, it is the strongest anti-churn mechanism available.

### 4. Onboarding Funnel — Realistic Benchmarks & Design Fixes

The original proposal assumed 100% onboarding completion. Real health app benchmarks say otherwise:

| Funnel Stage | Realistic Rate | n (from 1,000 landers) |
|---|---|---|
| Start onboarding | 45–55% | ~500 |
| Pass Q3 (first health data ask) | 28–38% | ~330 |
| Complete full score flow | 18–25% | ~210 |
| Return within 7 days | 8–12% | ~90 |
| Convert to paid (Day 14) | ~15% of completers | ~32 |

**Four design fixes to lift completion 40–60%:**
1. Progress bar ("Step 2 of 5") — reduces perceived commitment
2. "I don't know" option on every health question — eliminates the Q3 drop-off
3. Partial score preview after Q3 — rewards early engagement with tangible value
4. SMS re-engagement at 2-hour abandonment

### 5. Habit Formation — 3-Loop Retention Architecture

Email sequences are not retention systems. We designed three behavior loops:

- **Loop 1 — The Weekly Pulse** (Weeks 1–4): Monday score update. One number. One change. The habit forms when *missing* the update creates anxiety.
- **Loop 2 — Identity Milestone** (Weeks 4–8): "You've checked in 4 weeks in a row. Here's what you noticed before anyone else did." Identity reinforcement is the deepest retention driver.
- **Loop 3 — Family Network Effect** (Month 2+): Invite a sibling to the shared dashboard. When a second family member joins, churn drops 40–60% — two users must leave simultaneously for the account to cancel.

### 6. Clinical GTM — Reality Check & 90-Day Pilot

Hospital tool adoption runs 6–18 months. HIPAA/BAA negotiation alone takes 4–12 weeks. We designed a structured pilot that doesn't pretend otherwise:

- **Month 1:** 2–3 warm physician contacts. QR code at discharge. No paperwork, no BAA, no cold outreach.
- **Month 2:** Measure QR scan rate, score completion, conversion vs. digital cohort. If physician-referred users convert at >2x digital rate, proceed. If not, stop.
- **Month 3:** Formalize one relationship. One signed partner is the proof of concept that makes every subsequent clinical conversation easier.

Clinical is a *credibility channel first*, not a scalable acquisition engine.

### 7. Unit Economics — Three-Scenario Model with Named Pivot Triggers

| Metric | Optimistic | Base Case | Worst Case |
|---|---|---|---|
| CAC (paid search) | $35–50 | $65–90 | $120–160 |
| Freemium → paid conversion | 15% of completers | 10% | 5% |
| LTV:CAC ratio | 5–7x | 2.7–3.7x | 1.1–1.5x |
| Payback period | 2–3 months | 4–5 months | 8–10 months |

**Named pivot triggers — not assumptions:**
- CAC exceeds $100 by Month 3 → pause broad terms, shift to wedge keywords
- Onboarding completion <15% → implement the four design fixes immediately
- Day-14 conversion <3% of completers → test $9.99 tier before abandoning freemium

### 8. Competitive Defensibility — Honest Moat Assessment

| Moat | Strength | Reality |
|---|---|---|
| Academic partnerships | WEAK | Big tech replicates in 12–18 months |
| Patent-pending methodology | MODERATE | ~3 years if granted |
| Family-centric architecture | STRONG (2–4yr) | Apple/Google build for individuals; rewriting for family-facing decisions requires a new product |
| Longitudinal data asset | STRONG (12–18mo+) | Real moat — but only after sustained enrollment |
| Clinical workflow integration | STRONG (3–5yr) | First to sign discharge protocols owns this lane |
| Brand trust — caregiver community | STRONG (18mo+) | Compounds through word-of-mouth |

Defensibility is not built at launch — it is earned through usage, data, and trust over time.

### 9. 90-Day Execution Roadmap

**Phase 1 (Days 1–30) — 80% of Year-1 Impact**
Brand relaunch with emotion-led messaging, free score landing page with behavioral UX fixes, 3 caregiver video testimonials, Google Ads (wedge keywords only), clinical warm pilot with 2–3 physicians, SMS abandonment flow.

**Phase 2 (Days 31–60) — Close the Gaps**
Habit loop architecture live, freemium pricing A/B test ($9.99 / $14.99 / $19.99), family invite feature, Facebook retargeting to NJ Alzheimer's caregiver communities, CAC + conversion dashboard.

**Phase 3 (Days 61–90) — Compound and Scale**
SEO content (4 posts/month, wedge keywords), YouTube Q&A series, formal BAA negotiation if clinical signal confirmed, AI-assistant optimization (structured data for ChatGPT/Claude/Copilot), 90-day KPI review and 12-month growth roadmap.

**KPIs tracked from Day 1:** Onboarding completion · CAC by channel · Day-14 conversion · Weekly return rate · Clinical vs. digital conversion

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## Frameworks Applied

- Fogg Behavior Model (behavioral friction diagnosis)
- Nir Eyal's Hooked framework (habit loop design)
- Jobs-to-be-Done (trigger-moment segmentation)
- Three-scenario unit economics with explicit pivot triggers
- Wedge strategy / beachhead market methodology
- Healthcare GTM reality framework (HIPAA/BAA cycle planning)

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## Deliverables

- `Healthtech_AI_Report.pdf` — Full 13-section written submission (McKinsey-style, CEO-question-ready)
- `Health_Tech_Ai.pdf` — 37-slide executive presentation deck

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## Key Results

- Primary research: n=30 NJ caregiver survey, 24 questions, Qualtrics
- 90-day GTM roadmap currently being piloted by client leadership
- Unit economics model: 3-scenario CAC sensitivity ($35–160 range) with named pivot triggers
- Onboarding redesign: 4 behavioral fixes modeled to lift completion 40–60%

---

*Rutgers MSMAI Capstone | Spring 2026 | Client details anonymized per professional standards*

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