Research Report
typeahead.ai · Full Findings
Synthetic data — directional for product decisions, validate before launch.
1. Executive Summary
Product-Market Fit
41.5% "very disappointed" (Superhuman method) — crossing the 40% threshold. An additional 37.2% "somewhat disappointed" represents a large swing segment convertible with better messaging and onboarding.
Top 3 Actionable Findings
"Works in every app" is the killer feature. Ranked #1. Browser/Electron app support is the highest-impact technical investment.
One-time purchase at $49–$79 is optimal. 86% chose one-time. Zero chose subscription. $49–$79 band captures 51% of demand.
"Learns your voice" is the #1 value claim. Every interview participant independently prioritized voice learning over grammar correction.
Top 3 Risks
Accuracy kills trust fast. Wrong suggestions in client-facing communication are "worse than no suggestion."
"Does it work in my app?" will dominate objections. Universal app support is an anxiety point, not an assumption.
Privacy positioning has a ceiling. Users want quality AND privacy. Don't lead with privacy at the expense of demonstrating quality.
Recommended Next Steps
- Validate with real users: Van Westendorp pricing survey (n=100+) and 5–8 interviews
- Ship browser/Electron app support before native-only polish
- A/B test landing page: productivity-forward vs. privacy-forward messaging
2. Research Context
What Was Studied
Market demand for an AI autocomplete tool for macOS — feature priorities, pricing preferences, competitive perceptions, privacy attitudes, and segment-specific needs.
Methodology
Three research streams, all synthetic:
- Personas (8): Extracted from ~40 real HackerNews comments (2022–2026) on adjacent products
- Interviews (10): Synthetic interviews covering VP Sales, developer, researcher, privacy activist, content creator, support lead, UX designer, tech writer, consultant, copywriter
- Survey (100 respondents, 94 completed): PMF question, feature ranking, WTP, pricing model preference, competitor usage, privacy attitudes
Limitations
- All data is synthetic — real responses will differ
- Platform bias: 100% HN voices (skews technical, male, North American)
- Geographic bias: North America / Europe dominant
- No real user validation — pricing predictions are directional only
- Missing voices: non-technical writers, older demographics, enterprise IT
3. Key Findings
Finding 1: "Works in every app" is the #1 feature request
Universality across all Mac text fields is the single most demanded feature, outranking privacy, speed, and price.
- Feature ranking: avg rank 2.17 (1st of 5)
- 6/10 interview participants named Google Docs as primary writing app
- 59% use Google Docs; 88% use email clients; 69% use Slack/Teams
Recommendation: Prioritize browser extension or accessibility-based approach. Google Docs support is the single highest-impact technical feature.
Finding 2: "Learns your voice" is the highest-value differentiator
Users don't want AI to write better — they want AI to write like them, faster.
- Feature ranking: avg rank 2.22 (2nd of 5)
- Anika (researcher): "I don't want to sound like a native speaker. I want to sound like me, but clearer."
- Alex (copywriter): "They all try to write FOR me instead of WITH me."
Recommendation: Lead with "learns your voice" on the landing page. Avoid "improve your writing" — users hear "change your writing."
Finding 3: One-time purchase is non-negotiable
86% chose one-time purchase. Zero chose subscription. The strongest signal in the entire dataset.
- Priya (creator): "I pay for like eight subscriptions. The question is how much."
- Alex (copywriter): "What am I paying for monthly if the model is running on my machine?"
Recommendation: Ship at one-time purchase. Consider "pro" tier or paid updates as revenue expansion.
Finding 4: Accuracy is the primary trust factor
Users will abandon the tool faster for wrong suggestions than for missing suggestions.
- Sarah (VP Sales): "If it suggests something and I don't catch it... that's my reputation."
- Marcus (developer): "If it's right 70% of the time, I'll probably turn it off."
- Daniel (tech writer): "Better to suggest nothing than to suggest something wrong."
Recommendation: Default to conservative suggestions. Add user-adjustable confidence setting.
Finding 5: Privacy is a genuine purchase driver
Privacy-conscious users have significantly higher purchase intent. Local-first is trusted (4.02/5), cloud is distrusted (2.14/5).
- High-privacy respondents (4–5 score) = 54% "very disappointed" vs. 0% for low-privacy
- Jim (privacy activist): "I've read the privacy policies. They're all the same."
Recommendation: Lead with productivity messaging, embed privacy as a supporting pillar. Don't make it the headline — make it the reassurance.
Finding 6: Text expansion users are the ripest market
41% use text expanders. They're pre-sold on the concept — they just need a smarter tool.
Recommendation: Create migration content: "Import your Espanso/TextExpander snippets." Position as an upgrade.
Finding 7: Non-native English speakers are underserved
They want assistance that preserves their voice, not erases it. Currently paying Grammarly ($12/mo) reluctantly.
Recommendation: Create specific messaging for non-native English users. Consider multi-language support as v2.
Finding 8: The "somewhat disappointed" 37% is the growth opportunity
Casual users (4–6 hrs typing) who see value but aren't fully convinced. WTP clusters at $39–$49.
Recommendation: Generous free trial (14 days, full features). Value demonstration within 5 minutes. Price at $49.
Finding 9: Team/enterprise use is real but blocked by IT
Several participants expressed interest in team deployment, but IT approval is the primary barrier.
Recommendation: Defer enterprise features. Build a security whitepaper for future use.
Finding 10: Users want AI to be invisible, not impressive
Even creative professionals don't want AI to be creative. They want it to suggest what they'd type — boring, accurate, invisible.
Recommendation: Optimize for next-word/next-phrase prediction, not paragraph generation.
4. Target Market Analysis
Primary Beachhead: Power Users (39%)
Type 6+ hours/day. Mostly developers (30%) and writers (16%). Already use 2–4 productivity tools. Highest WTP ($79–$129). Strongest privacy concerns.
Persona Summary
| # | Name | Segment | Key Motivation | WTP | Adoption |
|---|---|---|---|---|---|
| 1 | Marcus | Privacy-First Dev | Local + system-wide | $49-99 | 85% |
| 2 | Priya | Freelancer | One-time + voice | $49 (99 ⚠️) | 80% |
| 3 | David | RSI Manager | Reduce keystrokes | $99 | 90% |
| 4 | Kenji | Non-Native English | Privacy + natural English | $79-99 | 88% |
| 5 | Elena | Indie Hacker | Zero-config + adaptable | $79-99 | 82% |
| 6 | Sarah | Enterprise Consultant | IT-approved + web apps | $99 (expense) | 55% |
| 7 | Tyler | Student | Cheap + Obsidian | $29-49 | 70% |
| 8 | Jordan | Content Creator | Voice learning + web | $99 | 85% |
5. Feature Prioritization
Must-Have (Ship with v1)
| Feature | Evidence | Priority |
|---|---|---|
| Universal app support | #1 ranked (2.17 avg). 59% use Google Docs. | P0 |
| Learns writing style | #2 ranked (2.22 avg). Every interview prioritized. | P0 |
| 100% local processing | #3 ranked (2.73 avg). 4.02/5 trust local. | P0 |
| Sub-200ms latency | "If it takes more than 200ms, I've already typed the next word." | P0 |
| Keyboard-dismissable suggestions | "One key to dismiss, no mouse. Table stakes." | P0 |
Should-Have (v1.1)
| Feature | Evidence |
|---|---|
| Import Espanso/TextExpander snippets | Rachel and Daniel both have 100+ snippets. Easiest conversion path. |
| Per-app enable/disable | Jim (privacy): "If I'm writing under NDA, I want to be damn sure no AI is learning from it." |
| Confidence/aggressiveness setting | Anika: "It should know when to help and when to stay out of the way." |
| Google Docs specific support | 59% of respondents. Emily: "It has to work in Google Docs in Chrome." |
Nice-to-Have (v2+)
| Feature | Evidence |
|---|---|
| Team/shared voice profiles | Tomás: "I'd want it for all 12 agents." |
| Multi-language support | "multi-language support, especially for non-english writers" (P020) |
| Terminal/vim support | "none of them work in terminal" (P036) |
| Analytics/acceptance tracking | Tomás: "I need to justify the purchase to leadership." |
| Custom vocabulary | "support for custom vocabulary and technical terms" (P031) |
6. Pricing Analysis
Willingness-to-Pay Distribution
| Price | % of Respondents | Segment |
|---|---|---|
| $79 | 20% | Power users (devs, writers) |
| $49 | 16% | Mixed (strongest single point) |
| $99 | 15% | High-intent power users |
| $39 | 15% | Casual users, students |
| $29 | 15% | Students, budget-constrained |
| $59 | 9% | Mid-range (gap in data) |
| $19 | 6% | Skeptical, low-intent |
| $129+ | 3% | Enthusiasts |
Recommended: $49 for launch, with a $79 "pro" tier. $49 captures the largest segment. $79 captures high-intent power users. The $49–$79 band covers 51% of demand. One-time purchase eliminates the subscription objection entirely.
7. Competitive Positioning
Competitor Usage (Survey)
| Tool | % Tried | Key Weakness |
|---|---|---|
| Apple Intelligence | 62% | Generic suggestions, limited app support |
| Grammarly | 51% | Cloud-based, changes voice, subscription |
| GitHub Copilot | 32% | IDE-only, not for prose |
| Espanso | 32% | Manual setup, static snippets |
| TextExpander | 27% | Expensive subscription, dated UI |
Where typeahead.ai Wins
Universal app support — No competitor does this well
Local-first privacy — No cloud dependency
Voice learning — No competitor preserves your specific writing voice
One-time purchase — Unique in the market
Where typeahead.ai Is Vulnerable
Quality of local models — Users skeptical that local inference can match cloud quality
Brand trust — Grammarly and Apple have established trust
Google Docs support — Technically hard; if unsolved, loses to browser extensions
Apple Intelligence evolution — Window is now
8. Messaging Recommendations
Lead With
- "Works in every app" — Show it, don't just say it
- "Learns your voice" — "Sounds like you, not AI"
- "Pay once, yours forever" — Compare to $144/yr Grammarly
- "100% private, 100% local" — "Nothing leaves your Mac"
Segment-Specific Messages
| Segment | Lead Message | Avoid |
|---|---|---|
| Developers | "Copilot for everything outside your IDE" | Don't call it a "writing tool" |
| Content creators | "Your voice, faster" | Don't mention AI generation |
| Non-native English | "Your English, your way" | Don't say "improve your English" |
| Freelancers | "One-time purchase. No subscriptions. Ever." | Don't show monthly pricing |
| RSI sufferers | "Type less, say more" | Don't over-medicalize |
| Students | "The tool that pays for itself in a week" | Don't ignore budget sensitivity |
Messages That Fall Flat
- "AI-powered" — Overused, meaningless, off-putting to privacy-conscious users
- "Improve your writing" — Users hear "change your writing" and reject it
- "Like having a co-writer" — Creepy for some, inaccurate for others
- "Replace Grammarly" — Too confrontational
9. Opportunity Map
| # | Opportunity | Impact | Effort | Next Step |
|---|---|---|---|---|
| 1 | Browser/Electron support | High | High | Technical spike on accessibility approach |
| 2 | Espanso/TextExpander import | High | Low | Build import tool + migration guide |
| 3 | Demo video | High | Medium | Record completions in Gmail, Slack, Docs, VS Code |
| 4 | Generous free trial (14-day) | High | Low | Implement trial, track activation |
| 5 | "Learns your voice" landing test | Medium | Low | A/B test hero messaging |
| 6 | Non-native English messaging | Medium | Low | Dedicated landing page variant |
| 7 | Confidence/aggressiveness slider | Medium | Medium | UX design + implementation |
| 8 | Student pricing tier ($29–$39) | Medium | Low | Student discount + referral tracking |
| 9 | Team voice profiles | Low | High | Defer. Build security whitepaper first. |
| 10 | Terminal/vim support | Low | Medium | Post-launch niche feature |
10. Appendix
Survey Methodology
| Type | Synthetic survey, Superhuman PMF framework |
| N | 100 respondents, 94 completed (94% completion rate) |
| Avg completion | 189 seconds |
| Questions | 21 (screening, PMF, feature ranking, pricing, privacy, competitors, open-ended) |
| Segments | 39% power user, 35% casual, 19% skeptical, 1% disengaged, 6% incomplete |
Confidence Assessment
| Dimension | Score | Notes |
|---|---|---|
| Evidence quality | 18/25 | ~40 real HN voice samples |
| Data provenance | 15/20 | Primary sources but single platform |
| Internal consistency | 18/20 | No contradictions across data |
| External validation | 12/20 | No real user interviews or survey data |
| Predictive power | 12/15 | 7 testable predictions |
| Total | 75/100 | Medium — directional for product decisions |
To Reach 90% Confidence
- Run 5–8 real user interviews across primary personas
- Van Westendorp pricing survey with n=100+ real respondents
- Beta test with 30–50 real users, track completions per app and acceptance rates
- Validate "learns your voice" feature interest vs. other features
- A/B test landing page messaging with real traffic