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competitive-positioning-research

Strategic competitive analysis skill for positioning research. Defines comparison dimensions, selects structural analogues, researches each comp, scores your approach 1-5, and produces ranked recommendations. Use before writing public-facing pages or when product positioning decisions are being made. Hard limit: 4 web searches per session.

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competitive-positioning-research

# Skill: Competitive Positioning Research _Owner: Archie | Maintained by: Sara_ --- ## When to Use This Skill **Triggers:** - "How does our X compare to how [category] leaders do it?" - "Research how successful [category] platforms handle [specific problem]" - "What can we learn from [Platform A / Platform B] for our [page/feature/approach]?" - Pre-ship review Phase 3 (strategic positioning check) - Before writing any public-facing page that has direct category comps **Not for:** - Technical claim accuracy — that's the **technical accuracy review** pattern (fee amounts, hash functions, protocol specs) - Deep product research — that's a **full Archie research brief** - Pricing analysis — that's **Becky** This skill is for *strategic/UX research* — "how did the best examples in this space solve this specific problem, and how do we stack up?" Not "is this claim correct?" --- ## The Research Pattern ### Step 1: Define the comparison dimensions Before searching, lock down: - **What specific problem** are we researching? (e.g. "two-sided marketplace landing page hero CTA — which side to prioritise?") - **What category** are the comps in? (e.g. "developer-facing two-sided marketplace") - **3–5 dimensions** to score on (e.g. side prioritisation, cold-start handling, social proof, trust signals) - **Target output:** scored table + ranked recommendations Don't start searching until you've written these down. Undefined scope = research sprawl. ### Step 2: Select comps Pick **4–6 platforms**. More is noise. Selection criteria: - Same audience type (developer, consumer, enterprise) - Same structural problem (two-sided, subscription, usage-based) - Mix of early-stage (how they launched) and mature (how they evolved) - **Prioritise structural analogues over direct competitors** — defensive bias corrupts the analysis ### Step 3: Research each comp For each platform, find: - How they handled the *specific problem* (not general company history) - What they prioritised early vs. mature stage - What worked and what they changed - One key lesson that applies to your situation **Search patterns that work:** - `"[platform] landing page teardown"` - `"[platform] early growth strategy"` - `"[platform] cold start problem"` - `"two-sided marketplace [specific problem] best practices"` - `"[platform] how they solved [problem]"` **Model knowledge vs. web search:** For well-known platforms (Airbnb, Stripe, Uber, Replicate), Archie has sufficient model knowledge for structural patterns. Use web search for specifics — a changed CTA, a pivot, a dated case study. ### Step 4: Score our approach Build a scoring table against the dimensions from Step 1. Score each **1–5** with a brief, honest note. A 2/5 with a real explanation is more useful than a 4/5 that flatters the team. Score what exists, not what was intended. ### Step 5: Produce recommendations Ranked by **impact**, not effort. For each recommendation: - What to change - Why (which comp's evidence supports it) - Approximate effort: one-line fix / section rewrite / new feature --- ## Output Format ```markdown # [Topic] — Competitive Positioning Research _Date: YYYY-MM-DD | Analyst: Archie_ ## Executive Summary [3–4 sentences: headline finding + top recommendation] ## Comparison Dimensions [The 3–5 dimensions being scored, and why they matter] ## Case Studies ### [Platform] - **What they did:** ... - **When (early vs mature):** ... - **Key lesson:** ... ## Scoring Table | Dimension | Score (1-5) | Notes | |---|---|---| ## Recommendations (ranked by impact) 1. **[Change]** — [why, which comp supports it] — [effort] ## What We Got Right [Strengths to preserve] ``` --- ## Time Budget and Scope | Type | Comps | Time | |---|---|---| | Quick (known category) | 2–4 | 8–10 min | | Full (novel category) | 5–6 | 15–20 min | **Hard limit: 4 web searches.** Synthesise from what you find. If you haven't found enough after 4 searches, scope was too broad — narrow the question, not the search count. --- ## Worked Example **Date:** 2026-03-24 **Product:** Reddi Agent Protocol (two-sided agent marketplace) **Problem:** Two-sided landing page hero CTA — which side to prioritise? **File:** `projects/reddi-agent-protocol/reviews/archie-marketplace-research-2026-03-24.md` **Comps studied:** Stripe, Uber, Airbnb, Hugging Face, Replicate (5 — right call, stopped before noise) **Dimensions scored:** Side prioritisation, supply-side hook, demand-side hook, chicken-and-egg acknowledgement, social proof, trust signals **Headline finding:** Seller-first hero is defensible at pre-supply stage, but the page is missing three things: cold-start acknowledgement, zero-friction demo, and any social proof. The "Browse Agents" CTA risks leading to a near-empty index — an active anti-signal. **Top recommendation:** Add a dual-path hero split so both sides feel directly spoken to without diluting the primary message. **Surprise:** Replicate — the closest structural analogue — led with *consumers* from day one, and made a live runnable demo the primary conversion mechanism on the landing page. Not a "coming soon" but an actual working model you could run from the hero. That's the bar for our live demo CTA. **Score that stung:** Chicken-and-egg handling got 1/5. The page doesn't acknowledge it's early-stage, and "why join a marketplace with no one in it yet?" has no answer anywhere on the page. Honest score, actionable gap. --- ## Common Mistakes **Too many comps.** Six becomes noise. Pick four or five strong structural analogues, research them properly, and stop. **Comparing to direct competitors.** Direct comp analysis introduces defensive bias. Structural analogues (same problem, different space) produce better lessons. Airbnb teaches more about marketplace cold starts than any other agent marketplace would. **Generous scoring.** A scoring table where everything is 3–4/5 is useless. The purpose of the table is to surface gaps. If nothing scores below 3, you're flattering the work, not analysing it. **Searching too broadly.** `two-sided marketplace` returns 10 years of generic content. `Replicate model provider growth strategy` returns the specific insight you need. Start specific, widen only if necessary. **Grepping the full repo.** Archie times out on `grep -r` across a full project directory. Always read targeted files by path. Never use recursive search on a large workspace. --- _This skill was written 2026-03-24 by Sara, based on Archie's marketplace research for Reddi Agent Protocol._

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文件大小: 4.1 KB | 发布时间: 2026-4-13 09:50

v1.0.0 最新 2026-4-13 09:50
New skill: competitive intelligence research framework for market positioning

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