| name | competitor-mapper |
| description | Maps the full competitive landscape — direct, indirect, substitute, and emerging competitors — with positioning gap analysis, review mining, and market_insights-calibrated saturation scoring. Feeds into idea-scoring, cac-modeler, pricing-and-wtp, and tam-sam-som-builder. |
Skill: competitor-mapper
Purpose
Understand what the user is actually competing against — not just other apps, but also spreadsheets, habits, free alternatives, and human services. The goal is not an exhaustive list but a strategic map: who owns the space, where the gaps are, and whether this idea can occupy a position that incumbents can't easily copy.
Input
- Idea slug
memory/ideas/<slug>/idea.md (app concept, key features, differentiator)memory/market_insights/<niche>-*-<YYYY>-<MM>.md (trend analysis files — use all available platform files for this niche)
Using Market Insights
Trend analysis files are a primary research source for competitor mapping. Extract the following:
| Platform file | What to extract for competitor mapping |
|---|
Apps (<niche>-apps-*.md) | Category rankings, new entrants, top apps by downloads/revenue, review complaint patterns, pricing models in use |
Reddit (<niche>-reddit-*.md) | Apps and tools users mention by name (both praised and hated), non-software workarounds users describe, recurring complaints about existing solutions |
TikTok (<niche>-tiktok-*.md) | Apps featured in viral content (free marketing = distribution advantage), creator-promoted tools, "alternatives to X" content trends |
Web Search (<niche>-web-search-*.md) | Top-ranking apps for category keywords, "best X apps" list winners, SEO-dominant competitors |
monetization_evidence (from any platform) | Which competitors are actively monetizing (proves the market supports revenue, identifies pricing benchmarks) |
trend_velocity | Rising-fast markets attract new entrants quickly — flag that emerging threats will increase |
If no market_insights files exist, note this as a gap and rely on direct research only.
Competitor Categories
| Category | Definition | Why it matters | Examples |
|---|
| Direct | Same solution, same audience | Head-to-head competition for the same users | Apps solving the exact same problem on the same platform |
| Indirect | Different solution, same problem | User might choose this instead, even though it works differently | A meditation app competing with a journaling app for "stress relief" |
| Substitute | Non-software solution the user currently employs | The real baseline — what happens if the user never installs any app | Spreadsheets, pen-and-paper, hiring a person, doing nothing, a WhatsApp group |
| Emerging | New entrants, beta products, or announced features from incumbents | Future competitive pressure — the landscape 6–12 months from now | YC-backed startups, Product Hunt launches, Apple/Google adding native features |
Process
Step 1 — Research Checklist by Category
Direct competitors (find 3–8)
Search these sources in order:
- App Store / Play Store category browse: Search the primary category and 2–3 keyword variations. Record the top 10 results for each search.
- "Best X apps" articles: Search Google for
best [category] apps 2026. The top 3 listicle results typically capture the market leaders.
- Product Hunt: Search the category. Sort by most upvoted. Focus on launches from the past 18 months (recent entrants).
- Market insights (Apps file): If
<niche>-apps-*.md exists, extract any competitors named in the narrative.
- Market insights (Reddit file): If
<niche>-reddit-*.md exists, extract apps users mention by name in discussions.
- AlternativeTo.net: Search the closest existing app. Lists adjacent competitors you may have missed.
For each direct competitor, record:
- Name, platform(s), pricing model and price
- Estimated user base (from App Store ratings count × 50–100, or from market_insights narrative)
- App Store rating (stars + review count)
- Last updated date (stale = opportunity)
- Top 3 features
- Top 3 complaints (from review mining — see Step 3)
Indirect competitors (find 2–5)
Ask: "What else might someone use to solve the same underlying problem, even if the approach is completely different?"
Sources:
- Reddit threads where users describe their current workflow for this problem
- "How to [solve problem]" search results — the solutions that appear ARE the indirect competition
- Market insights narratives that describe alternative approaches to the same pain
Substitutes (find 2–4)
Ask: "What is the user doing RIGHT NOW, before they know this app exists?"
Common substitute categories:
- Manual process: Spreadsheet, notes app, pen-and-paper, calendar reminders
- Human service: Coach, therapist, accountant, personal trainer
- Social workaround: Group chat, Facebook group, Discord server
- Inaction: Doing nothing (this is the strongest competitor for low-urgency problems)
Record the estimated cost and friction of each substitute — this is the switching-cost baseline the app must beat.
Emerging threats (find 1–3)
Sources:
- Product Hunt launches in the past 6 months
- YC / startup accelerator demo day lists
- Apple WWDC / Google I/O feature announcements that could obviate the app
- If
trend_velocity = "rising-fast" in market_insights, note that new entrants are likely
Flag any emerging competitor that has raised funding — they have resources to move fast.
Step 2 — App Store Search Methodology
The App Store is the most important research surface for B2C apps. Use this systematic approach:
- Primary keyword search: The most obvious term a user would search (e.g., "habit tracker").
- Problem keyword search: The problem statement (e.g., "build better habits").
- Audience keyword search: The target user + need (e.g., "ADHD planner").
- Adjacent keyword search: Related but broader terms (e.g., "daily routine", "productivity").
For each search, record:
- Number of results that are clearly relevant (not spam/unrelated)
- Rating and review count of the top 3 results
- Whether the top result has > 50K ratings (signals an entrenched incumbent)
- Date of last update for top 5 results (stale apps = opportunity to displace)
Step 3 — Review Mining for Positioning Gaps
Competitor reviews are the richest source of positioning gaps. Mine them systematically:
1-star reviews (frustration signals)
These reveal what users hate about existing solutions. Look for patterns:
- Bugs and reliability complaints (opportunity: "the one that actually works")
- Missing features that users expected (opportunity: build the feature they want)
- Pricing complaints (opportunity: better value or different model)
- Privacy/data concerns (opportunity: privacy-first positioning)
- UX complexity complaints (opportunity: simpler alternative)
3-star reviews (unmet expectation signals)
These are often more valuable than 1-star reviews. 3-star reviewers liked the app enough to keep using it but something important is missing:
- "Great app BUT..." — the "but" is the positioning gap
- "Would be perfect IF..." — the "if" is the feature opportunity
- "Works for X but not for Y" — the "Y" is the underserved segment
5-star reviews (what's defensible)
Read competitor 5-star reviews to understand what they do well. These strengths are hard to compete against directly — don't try. Instead, find the orthogonal angle that the incumbent's strength doesn't cover.
Mining process
For each direct competitor (top 3–5):
- Read the 20 most recent 1-star reviews
- Read the 20 most recent 3-star reviews
- Read 10 recent 5-star reviews
- Categorize complaints into themes (max 5 themes per competitor)
- Identify the most common complaint shared across 2+ competitors — this is the strongest gap signal
Step 4 — Positioning Gap Analysis
A positioning gap is a real user need that no current competitor serves well. Classify each gap:
| Gap type | Description | Defensibility |
|---|
| Audience gap | No competitor targets this specific user segment | Medium — easy to copy if proven |
| Feature gap | A commonly requested feature that no competitor has built | Low — incumbents can add it |
| Experience gap | Existing solutions work but the UX is painful | Medium — hard for bloated incumbents to simplify |
| Price gap | All competitors are expensive; a free or cheap alternative would win | Low — race to the bottom |
| Philosophy gap | Existing solutions have a fundamentally different worldview (e.g., "gamified" vs. "minimalist") | High — incumbents can't pivot their core identity |
| Platform gap | No good solution exists on a specific platform (e.g., iOS-only need, Apple Watch, visionOS) | Medium — temporary, but first-mover advantage is real |
| Trust gap | Users don't trust existing solutions (privacy, data ownership, ads) | High — trust is hard to build retroactively |
Prioritize philosophy gaps and trust gaps — these are the hardest for incumbents to copy and the most defensible for an indie developer.
Step 5 — Market Saturation Scoring
Saturation reflects how crowded the space is and how difficult it will be to get noticed.
| Factor | Low (1 pt) | Medium (2 pts) | High (3 pts) |
|---|
| Direct competitor count | 0–2 relevant apps | 3–6 relevant apps | 7+ relevant apps |
| Incumbent dominance | No app has > 10K ratings | 1–2 apps have 10K–100K ratings | An app has > 100K ratings |
| Funding in space | No funded competitors | 1–2 funded startups | Multiple funded companies or a FAANG player |
| App Store keyword saturation | Primary keywords show few relevant results | Moderate results, some quality variance | Top results are all high-quality, well-maintained apps |
| Content saturation | Few "best X apps" articles exist | Some articles, moderate SEO competition | Many SEO-optimized listicles, hard to rank |
Total score (5–15 points):
| Total | Saturation level |
|---|
| 5–7 | low — Blue ocean. Few competitors, clear opportunity to establish position. |
| 8–11 | medium — Competitive but gaps exist. Success requires clear differentiation. |
| 12–15 | high — Red ocean. Dominated by well-funded or well-established players. Indie success requires a genuinely novel angle or underserved niche. |
Output
Write to memory/ideas/<slug>/competitors.json:
{
"direct_competitors": [
{
"name": "",
"platform": "",
"estimated_users": "",
"app_store_rating": 0,
"review_count": 0,
"last_updated": "",
"pricing": "",
"pricing_model": "",
"top_features": [],
"top_complaints": [],
"complaint_themes": [],
"distribution_channels_observed": []
}
]
Notes
- The
most_common_complaint_across_competitors from review mining is one of the highest-signal data points in the entire validation system. If the same complaint appears in 3+ competitor review sets, it's a validated pain point — the market is telling you what to build.
distribution_channels_observed for each competitor helps downstream skills (distribution-analysis, cac-modeler) understand which channels actually work in this category.- If market_insights show
trend_velocity = "rising-fast", note in emerging_threats that the competitor landscape will shift quickly. Rising markets attract builders.
- Substitutes with
friction_level = "low" are the hardest to displace — if doing nothing or using a spreadsheet is easy enough, the app must provide dramatically more value to justify the download.
