--- name: market-trend-customer-insight-synthesizer description: "Synthesizes raw market research and scattered customer signals into a structured strategic brief covering trend classification, customer jobs-to-be-done, competitive shifts, opportunity sizing, 5 ranked strategic implications, and a 90-day recommended action set. Use when consolidating market research, distilling customer feedback into strategy, or turning fragmented signals into a defensible product or GTM decision." argument-hint: "[market-segment] [signal-sources]" allowed-tools: ["Read"] --- # Market Trend & Customer Insight Synthesizer ## Purpose Turn a pile of market research, customer interviews, support tickets, and win/loss notes into a single strategic brief that separates durable trends from noise, maps signals to customer jobs, and produces ranked implications a product or growth team can act on. Solves the problem of insight overload — where teams have plenty of data but no shared read on what it means or what to do next. ## When to Use Invoke this skill when the user asks to: - Synthesize market research, analyst reports, or industry data into strategic takeaways - Distill customer interviews, surveys, or support signals into product or GTM direction - Consolidate win/loss notes and competitive intel into a clear picture of where the market is moving - Build a strategy brief or insight readout for a planning cycle, QBR, or roadmap review - Decide whether an emerging trend is worth building for or is a passing fad - Turn fragmented signals into a defensible recommendation for leadership ## Inputs Required Before starting, collect: - **Market segment**: The specific market, vertical, or product category being analyzed - **Signal sources**: What raw material exists — analyst reports, customer interviews, surveys, support tickets, win/loss notes, sales calls, usage data, competitor moves (list what's available) - **Key questions**: The 1–3 strategic questions this synthesis needs to answer - **Target customer / ICP**: Who the insights should be interpreted through - **Time horizon**: The planning window this feeds — next quarter, next year, or multi-year - **Current strategy or bets**: What the team is doing now, so implications can be framed as confirm / adjust / reverse - **Decision owner**: Who acts on this brief and what decision they need to make If key questions or time horizon are missing, default to a 12-month product-and-GTM horizon and infer the questions from the segment and current strategy — noting the assumption. ## Instructions ### Step 1: Signal Inventory & Credibility Weighting Catalog every signal source and assign each a credibility weight before synthesizing: - **First-party behavioral** (usage data, cohort trends): highest weight — reveals what customers do, not what they say - **First-party stated** (interviews, surveys, support tickets, win/loss): high weight — reveals motivation and language, but subject to recency and vocal-minority bias - **Third-party** (analyst reports, industry surveys, market sizing): medium weight — useful for macro trends, but often lagging and vendor-influenced - **Anecdotal** (a loud customer, one lost deal, a competitor tweet): low weight — flag but do not build strategy on a single instance Note where signals are thin. Explicitly separate "we have evidence" from "we have a hunch." ### Step 2: Trend Classification Sort observed patterns into three buckets to separate durable shifts from noise: - **Structural trends**: durable, direction-clear shifts in buyer behavior, technology, or economics (e.g., buyers consolidating point tools into platforms). These merit strategic bets. - **Cyclical / conditional trends**: driven by current conditions (budget cycles, funding environment, a hype wave) that will reverse. These merit tactical responses, not roadmap commitments. - **Noise**: patterns that appear in one source, lack corroboration, or reflect a vocal minority. Name them so the team stops over-indexing on them. For each structural trend, state: what's driving it, what evidence supports it (tied to Step 1 weighting), and how confident you are (High / Medium / Low). ### Step 3: Customer Jobs & Unmet Needs Mapping Translate signals into jobs-to-be-done, not feature requests: - Identify the top **3–5 jobs** the target customer is trying to get done - For each job, capture: the current workaround, the friction, and the emotional/business stakes - Flag **unmet or underserved needs** — jobs where no current solution (yours or competitors') does well - Distinguish **stated needs** (what customers ask for) from **latent needs** (what their behavior reveals but they can't articulate) Use the pattern: "When [situation], [customer] wants to [motivation], so they can [outcome] — but today [friction]." ### Step 4: Competitive & Market Shift Read Assess how the landscape is moving: - **Where competitors are investing**: new categories, positioning shifts, pricing changes, acquisitions - **Where the puck is going**: adjacent categories, buyer expectations rising, table-stakes shifting - **Whitespace**: jobs or segments the market is collectively underserving - **Threats to current position**: substitutes, consolidation, buyer power shifts, or trends that erode the current differentiation Frame this as movement over time, not a static feature matrix. ### Step 5: Opportunity Sizing & Prioritization For each significant opportunity surfaced, do a directional (not spurious-precision) assessment across: - **Demand strength**: how many customers, how acute the pain (evidence-backed from Step 1) - **Strategic fit**: alignment with current strengths, ICP, and direction - **Feasibility**: rough effort/complexity to serve the job - **Time-to-signal**: how fast the team would know if a bet is working Rank opportunities using a simple High/Medium/Low across these axes — surface the trade-offs explicitly rather than collapsing to a single score. ### Step 6: Strategic Implications (5, Ranked) Convert the synthesis into 5 ranked strategic implications. Each implication must: 1. State the insight in one sentence 2. Name the "so what" — what it means for the team's strategy 3. Recommend a posture: **confirm** the current bet, **adjust** it, or **reverse** it 4. Cite the supporting evidence and its credibility weight 5. Note the risk of ignoring it Rank by strategic consequence, not by how interesting the finding is. ### Step 7: 90-Day Recommended Action Set Translate the top implications into concrete near-term moves: - **Now (0–30 days)**: validation experiments, discovery interviews, or quick tests to de-risk the top implication - **Next (30–60 days)**: roadmap, positioning, or GTM adjustments if signals hold - **Then (60–90 days)**: the bigger bet or decision the brief is building toward, and the specific signal that would greenlight it Each action names an owner-type (product / growth / PMM), a purpose, and a success signal. ## Output Format - **Structure**: Executive summary up top (the answer to the key questions in 4–5 sentences), then the seven analytical sections in order; opportunity sizing and strategic implications presented as tables or structured bullets - **Length**: 1,100–1,500 words - **Format**: Structured strategic brief — scannable headers, tables for prioritization and implications, prose for the executive summary - **Sections**: Executive Summary → Signal Inventory & Credibility → Trend Classification → Customer Jobs & Unmet Needs → Competitive & Market Shift → Opportunity Sizing → 5 Ranked Strategic Implications → 90-Day Action Set - **Tone**: Product strategy lead — decisive, evidence-anchored, comfortable saying "the data doesn't support this yet." No hype, no burying the recommendation. ## Quality Checklist Before delivering output, verify: - [ ] Every strategic implication cites specific evidence with a credibility weight — no assertions floating without support - [ ] Trends are sorted into structural / cyclical / noise — not lumped together as "trends" - [ ] 3–5 customer jobs are stated in jobs-to-be-done form, not as feature requests - [ ] Exactly 5 strategic implications are present, ranked by consequence, each with a confirm/adjust/reverse posture - [ ] The 90-day action set has Now/Next/Then phasing with a named success signal per action - [ ] Executive summary directly answers the stated key questions in the first 5 sentences ## Notes - The most common failure in insight synthesis is treating stated feature requests as strategy — always translate to the underlying job first. - When signals conflict, weight behavioral over stated, and corroborated over single-source; call out the conflict rather than smoothing it over. - In B2B SaaS, a single loud enterprise customer often distorts the read — flag when an "insight" is really one account's agenda. - If the evidence genuinely doesn't support a confident recommendation, say so and prescribe the fastest experiment to resolve it — an honest "we don't know yet, here's how to find out" is more valuable than a confident guess. --- ## How to use this skill This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top. **Installing in Claude Code:** - `~/.claude/skills//SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects) - `/.claude/skills//SKILL.md` — auto-loads only when working in that project (recommended for project-specific skills) Restart Claude Code or open a new session to register. **Using in Claude.ai, ChatGPT, Gemini, or other AI tools:** 1. 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