# doany.ai — Investor Market Analysis
### AI Support Copilot for Shopify Brands | April 2026

---

## 1. Market Sizing

### Top-Down

| Layer | Estimate | Methodology |
|-------|----------|-------------|
| Global customer service software market | ~$18B (2026) | Gartner/Grand View Research projections; ~15% CAGR from $11B in 2022 |
| E-commerce segment (~22% of CS spend) | ~$4.0B | E-commerce overindexes on ticket volume vs. other verticals |
| Shopify share of e-commerce (~10% of global GMV) | ~$400M | Shopify powers ~5.6M stores, ~10% of global e-commerce GMV |
| AI-layer spend (est. 25-35% of helpdesk budget) | ~$100-140M | AI add-ons/copilots priced at a fraction of full helpdesk seats |

### Bottom-Up

| Segment | Stores | Addressable | Avg ACV | Revenue Pool |
|---------|--------|-------------|---------|-------------|
| Shopify Plus ($10M+ GMV) | ~47,000 | ~32,000 (with 3+ agents) | $12,000 | $384M |
| High-growth standard ($1M-$10M GMV) | ~180,000 | ~90,000 (scaling support) | $5,000 | $450M |
| Long-tail standard (<$1M GMV) | ~5.4M | ~250,000 (active support needs) | $1,800 | $450M |

### Summary

| | Value | Notes |
|---|-------|-------|
| **TAM** | ~$1.3B | All Shopify stores that could use AI-assisted support tooling |
| **SAM** | ~$400M | Shopify Plus + high-growth standard stores with active support teams |
| **SOM (3-year)** | ~$8-15M ARR | ~1,200-2,000 paying merchants at blended $520 ARPU; <1% SAM penetration |

**Triangulation check:** Bottom-up TAM ($1.3B) and top-down narrowed estimate ($100-140M for AI-layer only) are consistent when you account for the bottom-up including full support-stack displacement over time, not just AI add-on spend today. The near-term AI-layer opportunity (~$100-140M) is the realistic revenue pool for the next 3-5 years.

---

## 2. Three-Year Revenue Scenarios

### Assumptions Common to All Scenarios

- Paid launch: Q3 2026 (Month 0 = July 2026)
- Blended ARPU: $520/mo at launch, growing with mix shift toward Pro/Enterprise
- Gross margin: 78% (LLM API costs as primary COGS)
- Pilot conversion: 38 brands in pipeline at launch

### Conservative

| | Y1 (Jul 26–Jun 27) | Y2 | Y3 |
|---|---|---|---|
| New customers/mo | 5 → 10 | 10 → 15 | 15 → 22 |
| End-of-year paying customers | 75 | 175 | 330 |
| Monthly churn | 5% | 4% | 3.5% |
| Net revenue retention | 105% | 108% | 112% |
| Blended ARPU | $490 | $510 | $540 |
| Exit MRR | $37K | $89K | $178K |
| **Annual Revenue** | **$250K** | **$720K** | **$1.5M** |

### Base

| | Y1 | Y2 | Y3 |
|---|---|---|---|
| New customers/mo | 8 → 15 | 15 → 25 | 25 → 40 |
| End-of-year paying customers | 120 | 310 | 620 |
| Monthly churn | 4% | 3% | 2.5% |
| Net revenue retention | 110% | 115% | 120% |
| Blended ARPU | $510 | $550 | $600 |
| Exit MRR | $61K | $171K | $372K |
| **Annual Revenue** | **$430K** | **$1.4M** | **$3.2M** |

### Optimistic

| | Y1 | Y2 | Y3 |
|---|---|---|---|
| New customers/mo | 12 → 22 | 22 → 45 | 45 → 70 |
| End-of-year paying customers | 180 | 500 | 1,050 |
| Monthly churn | 3% | 2.5% | 2% |
| Net revenue retention | 115% | 125% | 135% |
| Blended ARPU | $530 | $590 | $660 |
| Exit MRR | $95K | $295K | $693K |
| **Annual Revenue** | **$680K** | **$2.4M** | **$5.8M** |

**Series A readiness:** Base case reaches ~$1.4M ARR by end of Y2 (early 2028), which aligns with typical Series A thresholds. Optimistic case could be Series A-ready by late 2027.

---

## 3. Unit Economics

| Metric | Current / Projected | Benchmark (Seed SaaS) | Assessment |
|--------|--------------------|-----------------------|------------|
| Blended ARPU | $520/mo ($6,240 ACV) | Varies | Healthy for vertical SaaS; room to grow with seat expansion |
| Gross margin | ~78% | >70% = good | Strong. LLM costs trending down; margin should improve to 82-85% |
| Estimated CAC | $2,800 | <$8K for this ACV | Attractive if holds; founder-led sales will keep this low early |
| Target LTV (36-mo) | $18,720 | — | Conservative 36-mo lifetime; could extend with low churn |
| LTV:CAC | 6.7x | >3x acceptable, >5x good | Best-in-class territory. Key risk: CAC rises as you move past founder-led sales |
| Payback period | ~5.4 months | <12mo = good | Excellent. Investors will like this |
| Burn multiple (Y1 base) | ~4.2x | <3x = good, <2x = great | Elevated but expected at seed; should improve to <2x by Y2 |

### Key Unit Economics Risks
- **LLM cost volatility:** API pricing from OpenAI/Anthropic could shift; mitigate by building model-agnostic infra and exploring fine-tuned open-source models
- **CAC inflation:** Moving from founder-led to hired-AE sales typically 2-3x's CAC; plan for $5K-$7K CAC by Y2
- **Churn at conversion:** Pilot-to-paid conversion is unproven; 50-65% conversion of the 38 pilots is a reasonable target

---

## 4. Competitive Landscape

### Positioning Map

```
                    AI-Native
                       ▲
                       │
           Siena AI ●  │  ● doany.ai
                       │     (target position)
                       │
  Generic ◄────────────┼────────────► Shopify-
  Platform             │               Specialized
                       │
          Intercom ●   │   ● Gorgias
          Fin          │
          Zendesk ●    │   ● Richpanel
                       │
                       │   ● Tidio
                       ▼
                   Legacy/Bolt-on
```

### Competitive Matrix

| | Gorgias | Richpanel | Siena AI | Intercom Fin | Tidio (Lyro) | **doany.ai** |
|---|---|---|---|---|---|---|
| Shopify depth | ★★★★ | ★★★ | ★★ | ★ | ★★ | **★★★★★** |
| AI sophistication | ★★★ | ★★ | ★★★★ | ★★★★ | ★★ | **★★★★** |
| SMB pricing fit | ★★★ | ★★★ | ★★ | ★★ | ★★★★ | **★★★★** |
| Market traction | ★★★★★ | ★★★ | ★★ | ★★★★★ | ★★★★ | **★★** |
| Threat to doany.ai | High | Medium | Medium | Low-Med | Low | — |

### Competitive Moat Strategy

1. **Shopify data depth** — Deep integration with Shopify admin APIs (orders, inventory, customer history, Shopify Flow) that horizontal players won't prioritize
2. **Copilot > full automation** — Agents trust copilots more than autonomous bots; higher adoption, lower risk of bad customer experiences
3. **Vertical training data** — Every pilot generates Shopify-specific training data that improves the model; network effect within the vertical
4. **Ecosystem lock-in** — Shopify App Store distribution + integrations with Shopify-native tools (Klaviyo, Recharge, Loop Returns) create switching costs

### Gorgias: The Elephant in the Room

Gorgias is the primary competitive threat with ~14,000 Shopify merchants and strong brand. However:
- Their AI is an add-on to a legacy helpdesk architecture, not AI-native
- Their incentive is to protect helpdesk seat revenue, not cannibalize it with AI
- Innovator's dilemma: doany.ai can price aggressively and build AI-first while Gorgias protects margins
- Gorgias acquisition of doany.ai is a plausible exit path ($30-50M+ if traction proves out)

---

## 5. KPIs — Seed Stage Dashboard

### Primary Metrics (Report Monthly to Board)

| KPI | Current | 6-Mo Target | 12-Mo Target | Why It Matters |
|-----|---------|-------------|--------------|----------------|
| MRR | $0 (pre-revenue) | $35-50K | $80-120K | Core growth signal |
| Paying customers | 0 | 60-80 | 120-180 | Market validation |
| Pilot → paid conversion | TBD | 55-65% | — | Product-market fit proof |
| Logo churn (monthly) | 5.3% (pilot) | <5% | <4% | Retention = PMF |
| Net revenue retention | TBD | >105% | >110% | Expansion potential |
| AI resolution rate | 34% | 40% | 50% | Core product value |
| CSAT improvement | +11 pts | +12 pts | +15 pts | ROI story for customers |
| CAC | TBD | <$3,500 | <$5,000 | Efficiency as sales scales |
| Burn multiple | — | <5x | <3x | Capital efficiency |
| Runway (months) | 5 mo | 18 mo (post-raise) | 14 mo | Survival |

### Product-Specific Metrics (Track Internally)

- Tickets handled per brand per month (usage depth)
- Copilot suggestion acceptance rate (agent trust signal)
- Time-to-value: days from install to first AI-assisted resolution
- Shopify App Store rating and reviews
- Feature adoption by tier (which features drive upgrades)

---

## 6. Strategic Roadmap — Next 18 Months

### Phase 1: Convert & Close (Months 0-3, Post-Seed)

| Priority | Action | Success Metric |
|----------|--------|----------------|
| 🔴 Critical | Close seed round ($3M) | Funded, 20-mo runway |
| 🔴 Critical | Convert pilots to paid (target 20-25 of 38) | 55%+ conversion rate |
| 🔴 Critical | Hire 1st AE + 1 ML engineer | Onboarded and ramping |
| 🟡 Important | Launch on Shopify App Store | Listed, first organic installs |
| 🟡 Important | Secure 2-3 lighthouse case studies | Published with quantified ROI |

### Phase 2: Find the Repeatable Motion (Months 3-9)

| Priority | Action | Success Metric |
|----------|--------|----------------|
| 🔴 Critical | Reach $50K MRR | ~100 paying customers |
| 🔴 Critical | Prove repeatable sales cycle (<45 days) | Consistent close rates |
| 🟡 Important | Build integrations: Klaviyo, Recharge, Loop Returns | 3 integrations live |
| 🟡 Important | Launch content engine (SEO + Shopify community) | 500+ inbound leads/mo |
| 🟡 Important | Iterate pricing with willingness-to-pay analysis | Validated tier structure |
| 🟢 Nice-to-have | Explore Shopify Plus partner program | Application submitted |

### Phase 3: Scale for Series A (Months 9-18)

| Priority | Action | Success Metric |
|----------|--------|----------------|
| 🔴 Critical | Reach $100K+ MRR ($1.2M+ ARR run rate) | Series A threshold |
| 🔴 Critical | Demonstrate NRR >110% | Expansion revenue proven |
| 🟡 Important | Hire 2nd AE + CS manager | Sales team beyond founder |
| 🟡 Important | Develop enterprise features (SSO, audit logs, custom workflows) | 3+ enterprise deals |
| 🟡 Important | Begin Series A prep (data room, narrative, target investors) | Process-ready by M15 |
| 🟢 Explore | Evaluate adjacent platform expansion (WooCommerce, BigCommerce) | Market research complete |

---

## 7. Key Risks & Mitigations

| Risk | Severity | Likelihood | Mitigation |
|------|----------|------------|------------|
| Gorgias ships competitive AI-native product | High | Medium | Move fast on Shopify depth; build switching costs via integrations |
| Shopify builds native AI support tooling | High | Low-Med | Become acquisition target; build on top of Shopify's AI, not competing with it |
| Pilot-to-paid conversion below 40% | High | Low-Med | Offer extended trials, usage-based entry tier, concierge onboarding |
| LLM costs spike or API access restricted | Medium | Low | Multi-model architecture; invest in fine-tuned open-source fallback |
| CAC blows up beyond founder-led sales | Medium | Medium | Invest in Shopify App Store organic channel; build referral program early |
| Churn exceeds 5% monthly at scale | High | Medium | Dedicated CS hire; build stickiness via workflow automation, not just chat |

---

## 8. Investment Thesis Summary

**doany.ai is positioned to own the AI support layer for Shopify's ecosystem.** The thesis rests on four pillars:

1. **Timing:** Shopify merchants are actively adopting AI tooling, but no player owns the AI-native support copilot position for this vertical. Gorgias is the incumbent but is architecturally constrained. The window is 12-18 months before the market consolidates.

2. **Wedge:** The copilot model (augmenting agents, not replacing them) is the right entry point for mid-market merchants who aren't ready for full automation. This drives faster adoption and higher trust than autonomous agent competitors like Siena AI.

3. **Economics:** Projected unit economics are strong (6.7x LTV:CAC, 5.4-month payback, 78% gross margin). Even with CAC inflation from scaling sales, the model supports a capital-efficient path to $1M+ ARR.

4. **Team:** Rare combination of domain expertise (Alex's DTC/CX background), technical depth (Priya's Intercom ML experience), and competitive intelligence (Jordan's Gorgias product knowledge). This team knows the customer, the technology, and the competition.

**The $3M seed provides ~20 months of runway to convert pilots, prove repeatable sales, and reach Series A readiness at $1M+ ARR.**

---

*Prepared for doany.ai investor discussions. All market estimates are based on publicly available data, analyst reports, and internal company metrics as of April 2026. Projections involve assumptions that should be validated with actual operating data post-launch.*