competitor-mapper

<!-- version: 0.2.0 | outputs: memory/ideas/<slug>/competitors.json -->

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:

1. App Store / Play Store category browse: Search the primary category and 2–3 keyword variations. Record the top 10 results for each search.
2. "Best X apps" articles: Search Google for best [category] apps 2026. The top 3 listicle results typically capture the market leaders.
3. Product Hunt: Search the category. Sort by most upvoted. Focus on launches from the past 18 months (recent entrants).
4. Market insights (Apps file): If <niche>-apps-*.md exists, extract any competitors named in the narrative.
5. Market insights (Reddit file): If <niche>-reddit-*.md exists, extract apps users mention by name in discussions.
6. 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:

1. Primary keyword search: The most obvious term a user would search (e.g., "habit tracker").
2. Problem keyword search: The problem statement (e.g., "build better habits").
3. Audience keyword search: The target user + need (e.g., "ADHD planner").
4. 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):

1. Read the 20 most recent 1-star reviews
2. Read the 20 most recent 3-star reviews
3. Read 10 recent 5-star reviews
4. Categorize complaints into themes (max 5 themes per competitor)
5. 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": []
    }
  ],
  "indirect_competitors": [
    {
      "name": "",
      "approach": "",
      "why_users_choose_it": ""
    }
  ],
  "substitutes": [
    {
      "description": "",
      "cost": "",
      "friction_level": "low | medium | high",
      "switching_cost_to_app": ""
    }
  ],
  "emerging_threats": [
    {
      "name": "",
      "stage": "beta | launched | announced",
      "funded": false,
      "threat_level": "low | medium | high",
      "notes": ""
    }
  ],
  "review_mining_summary": {
    "most_common_complaint_across_competitors": "",
    "strongest_gap_signal": "",
    "competitors_mined": 0
  },
  "positioning_gaps": [
    {
      "gap_type": "audience | feature | experience | price | philosophy | platform | trust",
      "description": "",
      "defensibility": "low | medium | high",
      "evidence": ""
    }
  ],
  "saturation_score": {
    "direct_competitor_count": 0,
    "incumbent_dominance": 0,
    "funding_in_space": 0,
    "keyword_saturation": 0,
    "content_saturation": 0,
    "total": 0
  },
  "market_saturation": "low | medium | high",
  "differentiation_opportunities": [],
  "market_insights_sources_used": []
}

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.