HikeoProduct Requirements Document
Executive Summary
Planning a trek in India today requires stitching together at least 6–8 sources: outdated blog posts, scattered Reddit threads, WhatsApp groups that take days to respond, and separate portals for permits and gear. There is no single, personalised, altitude-safe planning tool for Indian treks. Hikeo solves this with an AI planner that generates a personalised, day-by-day itinerary in under 40 seconds - grounded in a hand-curated database of 149 Indian treks - paired with a discovery engine, a real-time community, and an affiliate gear marketplace. The MVP is live. Marketing, affiliate integration, and SEO pages per trek are the immediate next steps.
The product in one sentence
Hikeo is the single destination for anyone planning a trek in India - from first-timers researching Kedarkantha to experienced trekkers seeking hidden routes in Arunachal Pradesh. Planning, discovery, maps, community, and gear. One platform.
| Dimension | Detail |
|---|---|
| Product type | 0→1 AI consumer web app (solo build, full-stack) |
| Status | MVP shipped · Active development · Live at hikeo.vercel.app |
| Primary user | First-time and intermediate Himalayan trekkers (India, 22–35, metro-based) |
| Revenue model | Gear affiliate commissions (primary, active) · B2B planner licensing (future) · Premium tier (future) |
| Tech stack | Next.js · Groq + LLaMA 3.3 70B · Supabase · Leaflet · Tailwind CSS · Vercel |
| Status | MVP live at hikeo.vercel.app · Marketing, affiliate integration, and SEO pages are immediate next steps · ~₹67/mo burn |
Problem Statement
The Himalayan trekking market in India is growing - estimated 2–3M trekkers/year - but the planning infrastructure has not kept up. Three compounding problems make planning genuinely hard and, in some cases, dangerous:
Information is fragmented and stale
The top results for any Indian trek search are 2018 blog posts with broken links and outdated permit information. Reddit threads are scattered. WhatsApp groups take days to respond. There is no single, reliable, up-to-date source.
No personalisation for fitness level or group type
A plan for a solo experienced trekker and a group of college first-timers require fundamentally different day-structures, gear lists, and safety margins. No existing tool accounts for this. Generic itineraries are the default.
Altitude safety is expert knowledge most users lack
Acute Mountain Sickness (AMS) is the leading cause of serious incidents on Himalayan treks. The 300–500m/day altitude-gain rule is medically grounded but unknown to most first-timers. No consumer planning tool enforces it at the generation layer.
Supporting evidence
- →Planning friction is the dominant complaint across r/IndiaHiking, trek vlogs, and planning blogs - corroborated by 3-4 interviews with first-time trekkers
- →India has ~3,000 documented trekking routes but fewer than 200 have reliable, up-to-date digital information
- →The top 10 treks receive 90% of all traffic - discovery of alternatives is broken
- →Gear confusion leads to significant drop-off among first-time trekkers - they simply don't attempt trips
- →No existing platform combines planning + maps + community + gear in one place
Competitive Landscape
The white space
No product currently combines AI-assisted self-planning + deep India trek data + community + gear in a single modern experience. The two nearest categories are GPS apps (AllTrails, Wikiloc) and organised group operators (India Hikes, Trek The Himalayas) - neither serves the self-planner JTBD.
- →AllTrails / Wikiloc - GPS apps built for Western trails. India data is sparse. They surface GPX tracks, not personalised day-plans. Zero AI, zero India-specific community.
- →India Hikes / Trek The Himalayas - organised group operators. Different JTBD entirely. Hikeo competes for the self-planner, which is the larger and faster-growing segment.
- →No existing tool enforces altitude safety at the planning layer - Hikeo is the only platform where an unsafe itinerary cannot be generated.
User Personas
Ananya Sharma
First-time trekker · 23 · Mumbai
Goal: Plan her first Himalayan trek without hiring an agency
Jobs to be done
- →Find a trek that matches her beginner fitness level and available budget
- →Understand exactly what gear she needs - not a generic list
- →Know she won't get altitude sickness
Frustrations
- ✗Conflicting advice across 12 different blogs - no single source of truth
- ✗No way to know if an itinerary is actually altitude-safe
- ✗Gear shopping feels overwhelming without a specific, curated list
Rohan Mehta
Experienced trekker · 29 · Delhi
Goal: Find a hidden gem in the Northeast and plan it quickly - he's done this before
Jobs to be done
- →Discover treks he didn't know existed - not just the top 10
- →Get a solid starting itinerary in minutes, not hours
- →Connect with other serious trekkers who can verify route conditions
Frustrations
- ✗Every planning tool is built for beginners - too much hand-holding for his level
- ✗No platform covers remote treks in Sikkim and Arunachal Pradesh with real data
- ✗Having to manually filter noise from trekking WhatsApp groups
Goals & Success Metrics
| Goal | Metric | Target (6-month post-marketing launch) |
|---|---|---|
| Solve the planning problem | Plan generation completions | 1,000+ itineraries generated |
| Altitude safety enforcement | Plans with >500m/day gain generated | 0 (hard constraint at AI layer - this should always be 0) |
| User retention | Return visit rate (D30) | >25% of users return within 30 days |
| Gear monetisation | Affiliate click-through rate | >15% of plan-view sessions click ≥1 gear link |
| Community depth | Forum posts per week | >50 posts/week by month 3 |
| Trust & quality | Plan 4+ star rating rate | >80% of rated plans score 4–5 stars |
| Discovery engagement | Trek Discover page sessions with ≥3 trek views | >40% of Discover visitors |
Guardrail Metrics
Things that must not regress while we chase the targets above:
| Guardrail | Threshold | Why |
|---|---|---|
| Unsafe itineraries generated | 0 (absolute) | A single plan that violates the acclimatisation rule is a safety failure, not a metric miss. This is a hard constraint, not a target. |
| Planner completion rate | ≥70% of starts finish the 4-step form | If a richer planner adds friction and fewer people reach a plan, we are losing the core value event to chase depth. |
| Time-to-first-itinerary | ≤45 seconds | The streaming WOW moment depends on speed. If model or prompt changes push generation past ~45s, drop-off returns. |
| AI factual error rate on trek data | <2% of generated plans | Grounding in the 149-trek dataset keeps hallucination low. Rising errors erode the trust the whole product rests on. |
| Forum spam / abuse rate | <1% of messages | The 30-word filter + OAuth set a quality floor. A noisy forum is worse than no forum for trust. |
Feature Scope
The philosophy: solve the planning problem first. Community and monetisation are retention flywheels - but they require planning to be genuinely good before they add value. Discovery creates intent; the AI planner fulfils it; the community sustains it; the marketplace monetises it.
In scope - MVP (shipped)
AI Trek Planner (11 parameters)
Core value prop. Enforces altitude safety at generation layer. Follow-up chatbot in session detects AMS and gear questions.
Trek Discovery (149 treks, 7 filters)
Answers "which trek should I do?" before the planner answers "how do I do it?" - creates intent, not just serves it.
Community Forum (17 topic groups)
Real-time chat, reply threading, reactions, Reddit sidebar. 17 groups across 5 categories. Builds trust that enables marketplace conversion.
Trek Comparison Panel
41 fully-detailed trek cards with 7 filter dimensions. Side-by-side view for decision-making.
Gear Store (~98 products, 7 categories)
Contextual gear recommendations inside itinerary at highest purchase-intent moment. Amazon / Flipkart / Decathlon affiliate links.
Interactive India Trek Map
149 treks pinned with custom terrain icons. MarkerCluster for density. Enables serendipitous discovery by region.
Compass /compass
Interactive SVG physics-based compass fidget. Brand identity centrepiece - signals craft to the target audience.
Floating Chat Widget
Compass-rose button on every page. Mini planner in a modal - removes friction for mid-session users on non-planner pages.
Profile & Saves
Google OAuth, saved itineraries, direct messaging - user retention layer and the DM channel between trekkers.
In scope - v2 (roadmap)
Downloadable PDF itinerary
Offline use on trail. Increases perceived value and shareability.
User trek log
Save and track completed treks. Increases D30+ retention for experienced users like Rohan.
SEO-optimised trek landing pages
One page per trek ("Kedarkantha trek plan") for organic search acquisition.
B2B planner licensing
White-label planner to trekking agencies. Recurring revenue stream.
Out of scope - v1 and v2
Booking / payments
Requires guide partnerships and live inventory. Out of scope until v1 validates demand.
Native mobile app (iOS/Android)
Web-first. PWA covers mobile. App store review cycles slow iteration at this stage.
Guide marketplace
Two-sided marketplace complexity. Sequence after B2C trust is established.
Offline mode
Service worker caching adds complexity. Trekkers plan before leaving connectivity - PDF export covers the real need.
User Stories & Acceptance Criteria
Epic hypothesis
We believe that giving Indian trekkers an AI planner that generates an altitude-safe, personalised itinerary in under 40 seconds will convert planning-paralysed users into confident trekkers - because the dominant reason people don't trek is that planning feels overwhelming and unsafe. We'll know we're right when >25% of users who generate a plan return within 30 days.
As a first-time trekker, I want to generate a day-by-day itinerary by answering a few questions, so I can plan a safe trek without expert knowledge.
Acceptance criteria
- ✓The planner collects departure city, budget, group type, trek/state, duration, experience, terrain, accommodation, intensity, fitness, and dietary preference
- ✓An itinerary streams to the screen within 40 seconds of submitting
- ✓The generated plan never exceeds 300-500m/day altitude gain, regardless of inputs
- ✓The plan includes a day-by-day breakdown, gear checklist, and budget table
As an anxious first-timer, I want the AI to flag altitude-safety risks, so I trust the plan is medically sound.
Acceptance criteria
- ✓AMS, HACE, and HAPE keywords in the follow-up chat trigger protocol-level safety responses
- ✓Itineraries surface a visible AMS callout box on high-altitude days
- ✓The plan cannot be generated with an unsafe acclimatisation profile - it is a hard constraint, not a warning
As a trekker comparing options, I want to discover and compare treks I didn't know existed, so I can choose the right one for my level.
Acceptance criteria
- ✓Discover page shows curated trek cards filterable by 7 dimensions (difficulty, terrain, duration, altitude, distance, season, fitness)
- ✓A comparison panel shows up to 3 treks side by side across all dimensions
- ✓An interactive map shows all 149 treks pinned by terrain type
As a trekker who wants reassurance, I want to ask real trekkers questions, so I can validate my plan before committing.
Acceptance criteria
- ✓Forum has 17 topic groups across 5 categories (General, By State, By Gender, By Age Group, Trek Style)
- ✓Messages support reply threading and ThumbsUp/Down reactions in real time
- ✓A 30-word abuse filter blocks inappropriate content before insert
- ✓Authenticated users can DM each other from forum avatars
As a returning user, I want to save my itineraries and access them later, so I can reference my plan on the trail.
Acceptance criteria
- ✓Google OAuth sign-in via Supabase
- ✓Generated itineraries and trek plans can be saved to the user's profile
- ✓Saved items are accessible from /profile across sessions
Feature Specifications
AI Trek Planner
| Input Parameter | Type | Safety Constraint |
|---|---|---|
| Trek name | Dropdown (149 options) | - |
| Start date | Date picker | Flags off-season dates for the selected trek |
| Duration (days) | Slider 3–21 | Minimum enforced per trek altitude profile |
| Group size | Number 1–20 | - |
| Fitness level | Select: Beginner / Intermediate / Expert | Affects max daily km and altitude gain cap |
| Age range | Select | Flags AMS risk for 60+ and under-16 |
| Accommodation type | Select: Camping / Guesthouses / Mix | - |
| Budget range | Select: Economy / Mid / Premium | - |
| Special requirements | Free text | - |
| Previous trek experience | Multi-select | Informs difficulty recommendation |
| Gear available | Multi-select checklist | Excludes already-owned items from gear checklist output |
The altitude safety constraint
The AI system prompt hard-enforces the 300–500m/day altitude-gain rule. No output can exceed this limit regardless of user-provided fitness level. This is a hard constraint at the generation layer - not a warning surfaced post-generation. The AI is powered by Groq + LLaMA 3.3 70B, temperature tuned for factual accuracy. ReadableStream piped directly to client - no buffer, streaming builds engagement over the 30–40s generation window.
Trek Discovery
| Feature | Spec |
|---|---|
| Database | 149 treks across 8 Indian states; 41 with full curated detail cards |
| Filter dimensions | Difficulty · Terrain · Duration · Altitude · Distance · Season · Fitness level |
| Comparison panel | Side-by-side view of up to 3 treks across all 7 dimensions |
| Map | Interactive Leaflet map; all 149 treks pinned with custom terrain icons; MarkerCluster for density |
| Detail card | Altitude profile · Day-by-day overview · Best season · Required fitness · Gear essentials · Highlights |
Discover ≠ Search
Search assumes intent. Discover creates it. Most users don't know which trek they want - they know roughly what kind of experience they want. The filter-driven Discover experience surfaces treks they didn't know existed. This is the emotional engine of the platform.
Community Forum
| Feature | Spec |
|---|---|
| Topic groups | 17 groups across 5 categories: General · By State (Uttarakhand, HP, J&K, Sikkim & NE, Maharashtra, Karnataka & Kerala) · By Gender · By Age Group · Trek Style |
| Realtime | Supabase Postgres + Realtime subscriptions. Zero polling. Presence counter shows live user count per thread. |
| Reactions | ThumbsUp / ThumbsDown per message. Stored as JSONB in Supabase. |
| Reply threading | Quote a message and reply inline - preserves conversation context |
| DMs | Direct messages between authenticated users - same realtime layer as forum |
| Reddit sidebar | Live trending posts from r/IndiaHiking, r/india, r/SoloTravel_India, r/backpacking, r/CampingandHiking, r/mountaineering |
| Abuse filter | 30-word blocklist server-side before insert. Warns on first violation, signs out on second. Admin mod-delete with Shield icon. |
| Auth | Google OAuth via @supabase/ssr. No anonymous posting. |
Gear Store
| Feature | Spec |
|---|---|
| Products | ~98 curated trekking products across 7 categories |
| Categories | Backpacks & Bags · Footwear · Camping (sleeping bags/tents/mats) · Clothing · Navigation & Safety · Hydration · Accessories |
| UX | Search, category filter (SVG icons per category), sort by popularity / price |
| Affiliate partners | Amazon Associates (4–5%) · Flipkart Affiliate (3–5%) · Decathlon Affiliate (variable) |
| Contextual gear | GearRecommendations panel surfaces trek-matched products from the checklist inside the itinerary using keyword rules - not a generic sidebar |
Compass - /compass
Brand identity, not just a feature
An interactive brass compass fidget - spin the needle, find your bearing. SVG physics-based animation. Also present in the nav and as a loader across the app. Outdoor platforms are visually generic; the compass creates a distinctive, tactile identity that signals the product was built by someone who actually treks.
Floating Chat Widget
| Feature | Spec |
|---|---|
| Trigger | Compass-rose floating button - visible on all pages except /gears, /planner, /compass, /about, /privacy |
| Behaviour | Opens a mini 4-step planner in a modal. Streams a full itinerary without leaving the page. |
| Backend | Same Groq + LLaMA 3.3 70B endpoint as /planner - no separate infrastructure |
| Purpose | Removes friction for users who discover Hikeo mid-session on a non-planner page |
Profile & Saves
| Feature | Spec |
|---|---|
| Auth | Google OAuth via Supabase SSR |
| Saves | Save itineraries and trek plans to profile - accessible at /profile |
| Profile | Custom display name and avatar. View and manage all saved items. |
| DMs | Direct messages accessible from forum avatars or profile. Supabase Realtime. Same backend as forum. |
Cash Flow & Unit Economics
Current status: MVP live, marketing next
Hikeo is built, live, and functional. All infrastructure is on free tiers. Marketing launch, affiliate link integration, and SEO pages per trek are the immediate next steps. The model below shows what the business is designed to earn once those are in place.
| Cost item | Current cost | Scale trigger | Paid tier cost |
|---|---|---|---|
| AI inference (Groq free tier) | ₹0 / month | >14,400 req/day | ~₹4,200/mo (Groq Dev tier) |
| Database + auth (Supabase free) | ₹0 / month | >500MB storage / 2GB bandwidth | ~₹1,700/mo (Pro) |
| Hosting (Vercel free) | ₹0 / month | Sustained high traffic | ~₹1,700/mo (Pro) |
| Domain | ~₹67 / month | N/A (already paying) | ~₹800/year fixed |
| Total burn (current) | ~₹67 / month | - | - |
At current scale, Hikeo runs on ~₹67/month (domain only). Scale triggers only kick in well above current traffic. Until then, gross margin on first affiliate revenue is near 100%.
Revenue model - gear affiliate (primary, active)
Revenue model - future streams (not built)
Illustrative revenue scenario - 1,000 monthly active users
1,000
Plans generated/month
at 1,000 MAU, ~1 plan/user
150
Gear link clicks (15% CTR)
sessions clicking ≥1 gear link
15–30 units
Purchases @ ₹3,000 avg order
10–20% conversion on clicks
₹1,800–₹3,600 / mo
Affiliate revenue (4% avg)
at 15–30 conversions × 4%
~₹67 / mo
Infra cost at 1K MAU
still within free tiers at this volume
~98%
Gross margin
near-zero COGS at early scale
All figures are model projections. Not current actuals.
Business Model Canvas
Value Proposition
- AI-generated altitude-safe trek itinerary in <40 seconds - enforced at AI layer, not a post-generation warning
- Single platform for discovery, planning, community, and gear - no tab-switching across 6–8 sources
- Curated database of 149 Indian treks, hand-verified for accuracy and depth
Customer Segments
- First-time Himalayan trekkers (Ananya) - high anxiety, high gear spend, strong word-of-mouth potential
- Experienced trekkers (Rohan) - want speed and depth, not hand-holding; high forum contribution
- Group coordinators - managing logistics for 6–12 people; high gear conversion per session
Channels
- SEO - optimised trek landing pages per route ("Kedarkantha trek plan")
- Community - Reddit (r/india, r/hiking), Discord, NexTrek forums
- Word-of-mouth - itinerary output is shareable by design; users forward to trip-mates
Key Resources
- 149-trek curated database - hand-verified, not scraped (the durable moat)
- Groq + LLaMA 3.3 70B - altitude-safety constraint baked into system prompt at generation layer
- Supabase backend - forum, saves, user profiles, real-time chat
- Custom markdown renderer - produces richer itinerary output than any off-the-shelf library
Key Partners
- Amazon Associates - gear affiliate programme (4–5% commission)
- Flipkart Affiliate - supplementary gear channel (3–5%)
- Decathlon Affiliate - preferred for budget and mid-range gear
- Vercel, Supabase - infrastructure (all on free tier at current scale)
Cost Structure
AI inference (Groq + LLaMA 3.3 70B)
Free tierSufficient at current volume
Database + auth (Supabase)
₹0 / moFree tier - sufficient at current volume
Hosting (Vercel)
₹0 / moFree tier
Domain (hikeo.vercel.app)
~₹67 / moOnly hard cost - ₹800/year
Revenue Streams
Gear affiliate commissions (primary, active)
B2B guide licensing (future)
White-label planner to trekking agencies. Not yet built or validated.
Premium tier (future, potential)
Saved itineraries, offline PDF, priority AI, multi-trek comparison.
MVP live. Marketing and affiliate integration are the immediate next steps. No revenue generated yet.
Go-to-Market Strategy
GTM philosophy: community-led, SEO-anchored
No paid acquisition at MVP stage. The product has to earn its audience. Each channel below is sequenced deliberately - community seeding first to generate real feedback and social proof, then SEO to capture organic intent, then word-of-mouth as the compounding flywheel.
| Phase | Channel | Action | Target |
|---|---|---|---|
| Phase 1 · Community seeding | Reddit, Discord, NexTrek | Post AI planner as a free tool. Share demo itineraries. Collect feedback on plan quality. | 200+ plans generated; structured feedback on altitude safety accuracy |
| Phase 1 · Community seeding | India Hikes newsletter | Pitch for a feature mention - free tool for their audience, no competitive overlap. | Newsletter placement; first 500 unique visitors |
| Phase 2 · SEO foundation | Organic search | One SEO-optimised landing page per trek: "Kedarkantha trek plan", "Chopta trek itinerary" etc. Planner pre-loaded for that trek. | Top 5 ranking for 10+ trek-specific long-tail queries |
| Phase 2 · SEO foundation | Itinerary indexing | Each generated itinerary publicly accessible and SEO-indexed with trek name, route, and key data. | Evergreen backlink source from sharers |
| Phase 3 · Word-of-mouth | Shareable output | "Generated by Hikeo" attribution on itineraries. Users forward to trip-mates. Each converted user generates 1.5–2x referrals. | 40%+ of new users arrive via referral link |
| Phase 4 · B2B | Trekking agencies | Outreach to India Hikes, Bikat Adventures for white-label planner licensing. Depends on validated consumer demand. | First B2B licensing conversation at 5K+ MAU |
Ideal Customer Profile (ICP)
Primary
First-time Himalayan trekkers, 22–30, metro-based (Bangalore, Delhi, Mumbai, Pune). Planning their first non-resort mountain experience. High information anxiety, high gear spend potential, strong word-of-mouth velocity.
Secondary
Intermediate trekkers, 28–36, planning a harder route than their last. Less anxious, more specific. High forum contribution potential. Refer friends who are also planning.
Tertiary
Group coordinators managing treks for 6–15 people (corporate, college, friend groups). Higher gear conversion per session. Solve the same planning problem repeatedly - high retention potential.
Non-Goals
Weather forecasting integration
Real-time weather APIs add cost and fragility. Hikeo is a planning tool, not a day-of conditions app. Season guidance in the trek database covers the planning-time need.
Real-time availability / booking
Requires live inventory from permit offices and guiding agencies - a separate B2B integration problem. Out of scope for v1 and v2.
Video content / trek documentation
High production cost, low marginal value vs text-based plans. Competes with YouTube, not a complement to it. User-generated content in the forum serves this need adequately.
Insurance product
Regulatory complexity in India. Would require partnership with a licensed insurer. Defer to v3+, and only if user research shows clear demand.
Global trek coverage
India-first is the moat. Going global dilutes the data quality advantage and the community relevance. Own India deeply before expanding.
Risks & Mitigations
AI generates medically unsafe itinerary despite constraint
HighHard system-prompt constraint caps altitude gain at 500m/day regardless of user input. Output validation layer flags any generated plan exceeding this limit before serving to user. This is a safety-critical feature - any regression here is a P0.
AI inference costs spike with growth
HighFree tier covers current volume. Mitigation: client-side queuing, graceful degradation message, and upgrade path to paid API tier at sustained higher traffic. Unit economics of affiliate revenue should cover AI costs at moderate scale.
Trek database becomes stale (trail closures, permit changes)
Medium149 treks are hand-curated. Committed to quarterly review cycle. User-reported corrections via forum serve as an early warning system. Stale data erodes trust faster than most other issues.
Low gear affiliate conversion rate
MediumGear checklist is auto-generated from the itinerary and appears at highest purchase-intent moment. If CTR <10% at 90 days post-marketing launch, test: (a) inline product cards vs (b) dedicated gear page, (c) curated starter bundles per trek type.
Forum quality degrades at scale
Low30-word abuse filter + Google OAuth (no anonymous posting) sets a quality floor. Trek-specific threading prevents general noise from contaminating high-value discussions. Moderation overhead is low at current scale.
Community cold-start problem
MediumA forum with no users is not useful. Mitigation: seed the forum with real trek reports from the builder, invite early users personally, and tie community seeding to GTM Phase 1 outreach to trekking communities.
Dependencies
| Dependency | Type | Status / risk |
|---|---|---|
| Groq + LLaMA 3.3 70B | External | The AI planner depends on Groq inference. Free tier covers current volume. Risk: model deprecation or pricing change; mitigated by a provider-agnostic prompt layer. |
| Curated 149-trek dataset | Internal | Hand-verified data grounds the AI and powers Discover. Quarterly refresh required as trails close and permits change. The durable moat and the maintenance burden. |
| Supabase (Postgres, auth, realtime) | Technical | Powers profiles, saves, forum, and DMs. Free tier sufficient now. RLS isolates user data without custom middleware. |
| Affiliate programmes (Amazon/Flipkart/Decathlon) | External | Gear revenue depends on affiliate approval. Not yet integrated. On the critical path for the primary revenue stream. |
| Vercel hosting | Technical | Web + API hosting on free tier. No blocker until sustained high traffic. |
Launch Plan
| Phase | Timeline | Focus | Success Gate |
|---|---|---|---|
| Alpha (done) | Month 1 | Planner live with core treks. Invite-only. Gather structured feedback on plan quality and altitude safety accuracy. | ≥80% of users rate plan quality 4+/5 |
| Beta (done) | Month 2–3 | Open access. Full 149-trek database. Forum and comparison panel live. | 200+ plans generated; forum seeded with real trek reports |
| MVP Live (current) | Month 3 | Gear affiliate links embedded. Product feature-complete. | Product live - marketing, SEO, and affiliate integration are next steps |
| Marketing Launch | Month 4 | Community seeding: Reddit (r/india, r/hiking), NexTrek, Discord. India Hikes newsletter pitch. | 1K+ plans generated; >15% gear CTR |
| SEO + Word-of-mouth | Month 5–6 | SEO-optimised landing pages per trek indexed. Shareable itinerary attribution live. | Top 5 ranking for 5+ trek queries; 40%+ referral share of new users |
| v2 Planning | Month 6+ | PDF export, user trek log, B2B licensing outreach. Native app assessment based on PWA data. | MoM plan growth ≥20%; first B2B conversation |
Open Questions
Unresolved decisions that need validation through usage data or further discovery before they're locked in.
?Should the AI planner require sign-in, or stay anonymous until save?
Anonymous lowers the barrier to the first plan (the WOW moment), but loses the data and re-engagement hook. Leaning anonymous-first with a save-gated sign-in. Needs a funnel test.
?What's the right moment to introduce the gear store?
Inside the itinerary at generation time (highest intent) vs a separate browse tab. Risk of feeling salesy too early. A/B the inline checklist vs a dedicated page once affiliate links are live.
?Is the forum viable pre-scale, or does it need seeding?
An empty forum is worse than no forum. Open question: seed with real trek reports manually, or hide the forum until a critical mass of users exists?
?Premium tier - what actually converts?
Offline PDF export, priority generation, multi-trek comparison are candidates. None validated. Free tier must prove retention before any paywall is tested.
?Quarterly data refresh - manual or community-sourced?
149 treks are hand-curated. As trails close and permits change, who keeps data fresh? Forum-reported corrections could work but need a verification workflow.