Skip to content This library is free, offered as dana. If it helps your work, donate here →
penguin tree ai
← back to libraryDonate here

This is one of 3,622 free prompts in the penguin tree ai library. Sign up once and the whole library opens, with new prompts by email.

open the library →

Market trend & customer insight synthesizer

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…

download .md

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 — markdown with YAML frontmatter at the top.

Installing in Claude Code:

  • ~/.claude/skills/<folder-name>/SKILL.md — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
  • <your-project>/.claude/skills/<folder-name>/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. Drag this file into a new chat, or copy and paste its contents
  2. Send your task or request as your next message — the AI will apply the skill where it fits

For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills