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Agent skill

Suede Customer Research

by JasonColapietro in JasonColapietro/suede-creator-skills

Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas.

MITAuto-check passedMarketing & SEO

Install Suede Customer Research

skills CLI
$ npx skills add JasonColapietro/suede-creator-skills --skill suede-customer-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install JasonColapietro/suede-creator-skills suede-customer-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/JasonColapietro/suede-creator-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/suede-customer-research .claude/skills/suede-customer-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
suede-customer-research
GitHub stars
127
Token cost
~3.4k tokens
SKILL.md length
1,719 words
Files
6 (incl. references)
Skills in repo
78
Repo updated
First seen
Licence
MIT

At a glance

Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas.

  • Works in 6 steps: Jobs to Be Done: what outcome is the… → Pain Points: what's frustrating, broken,… → Trigger Events: what changed that made… → …
  • Synthesizing what a defined customer segment actually says
  • SKILL.md covers Before Starting, Two Modes of Research, Mode 1: Analyzing Existing… and Mode 2: Digital Watering Hole…, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Suede Customer Research is an agent skill from JasonColapietro/suede-creator-skills. Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas. Use when discovering or synthesizing what a defined customer segment actually says, does, needs, and resists. NOT FOR: competitor-only profiling (use suede-competitor-profiling), writing final marketing copy (use suede-copy), or deciding product priorities without product evidence (use suede-product-marketing).

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `CARD.md`, `agents/openai.yaml` and `evals/evals.json`).

It sits in Marketing & SEO, covering Market research and Copywriting. The repository describes itself as: Open-source AI skills for SEO, AI search visibility, conversion copy, marketing strategy, and business operations. Reusable workflows for Claude Code and Codex, plus code review… The licence is MIT.

When your agent uses it

  • Synthesizing what a defined customer segment actually says
  • Tasks that involve Market research
  • Tasks that involve Copywriting

Example prompts

  • “/suede-customer-research”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Jobs to Be Done: what outcome is the customer trying to achieve?
  2. Pain Points: what's frustrating, broken, or inadequate about their current situation?
  3. Trigger Events: what changed that made them seek a solution?
  4. Desired Outcomes: what does success look like in their words?
  5. Language and Vocabulary: exact words and phrases customers use
  6. Alternatives Considered: what else did they look at or try?

What it can do on your machine

Read from SKILL.md and the folder at commit e5f94d7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Suede Customer Research loads about 3.4k tokens when it runs, and up to ~7.9k if it reads all its reference files. Until then it costs about 127 tokens; SKILL.md has 1,719 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~127
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from JasonColapietro/suede-creator-skills at commit e5f94d7, republished under its MIT licence (© JasonColapietro). 1,719 words, ~3,396 tokens.

Download SKILL.mdSave it as .claude/skills/suede-customer-research/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
suede-customer-research
description
Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas. Use when discovering or synthesizing what a defined customer segment actually says, does, needs, and resists. NOT FOR: competitor-only profiling (use suede-competitor-profiling), writing final marketing copy (use suede-copy), or deciding product priorities without product evidence (use suede-product-marketing).
metadata.version
2.0.1

Suede Customer Research

Use this Suede customer-research playbook to ground positioning, product, and copy in traceable customer evidence rather than assumption.

Before Starting

Check for .agents/product-marketing.md (or .claude/product-marketing.md, or the legacy product-marketing-context.md) and read it if present: the ICP, segment definitions, and what research already exists decide where to look and what counts as a representative sample. Ask only what it does not already answer.

Two Modes of Research

Mode 1: Analyze Existing Assets

You have raw research material (transcripts, surveys, reviews, tickets). Your job is to extract signal.

Mode 2: Go Find Research

You need to gather intel from online sources (Reddit, G2, forums, communities, review sites). Your job is to know where to look and what to extract.

Most engagements combine both. Establish which mode applies before proceeding.

Mode 1: Analyzing Existing Research Assets

Asset Types

Customer interview / sales call transcripts

  • Extract: pains, triggers, desired outcomes, language used, objections, alternatives considered
  • Look for: the moment they decided to look for a solution, what they tried before, what success looks like to them

Survey results

  • Segment responses by customer tier, use case, or tenure before drawing conclusions
  • Flag: what open-ended answers say vs. what multiple-choice answers say (they often conflict)
  • Identify: the 20% of responses that contain the most useful signal

Customer support conversations

  • Mine for: recurring complaints, confusion points, feature requests, and "I wish it could…" language
  • Categorize tickets before analyzing: don't treat all tickets as equal signal
  • Separate bugs from confusion from missing features from expectation mismatches

Win/loss interviews and churned customer notes

  • Wins: what tipped the decision? What almost made them choose a competitor?
  • Losses and churn: was it price, features, fit, timing, or something else?
  • Segment by reason: don't average across different churn causes

NPS responses

  • Passives and detractors are higher signal than promoters for improvement work
  • Pair scores with verbatims: a 9 with a specific complaint beats a 10 with no comment
Extraction Framework

For each asset, extract:

  1. Jobs to Be Done: what outcome is the customer trying to achieve?

    • Functional job: the task itself
    • Emotional job: how they want to feel
    • Social job: how they want to be perceived

  2. Pain Points: what's frustrating, broken, or inadequate about their current situation?

    • Prioritize pains mentioned unprompted and with emotional language

  3. Trigger Events: what changed that made them seek a solution?

    • Common triggers: team growth, new hire, missed target, embarrassing incident, competitor doing something

  4. Desired Outcomes: what does success look like in their words?

    • Capture exact quotes, not paraphrases

  5. Language and Vocabulary: exact words and phrases customers use

    • This is gold for copy. "We were drowning in spreadsheets" > "manual process inefficiency"

  6. Alternatives Considered: what else did they look at or try?

    • Includes doing nothing, hiring someone, or building internally
Synthesis Steps

After extracting from individual assets:

  1. Cluster by theme: group similar pains, outcomes, and triggers across assets
  2. Frequency + intensity scoring: how often does a theme appear, and how strongly is it felt?
  3. Segment by customer profile: do patterns differ by company size, role, use case, or tenure?
  4. Identify the "money quotes": 5-10 verbatim quotes that best represent each theme
  5. Flag contradictions: where do customers say one thing but do another?
Research Quality Guardrails

Label every insight with a confidence level before presenting it:

ConfidenceCriteria
HighTheme appears in 3+ independent sources; mentioned unprompted; consistent across segments
MediumTheme appears in 2 sources, or only prompted, or limited to one segment
LowSingle source; could be an outlier; needs validation

Recency window: Weight sources from the last 12 months more heavily. Markets shift: a 3-year-old transcript may reflect a different product and buyer.

Sample bias checks:

  • Online reviewers skew toward power users and people with strong opinions
  • Support tickets skew toward problems, not value
  • Reddit skews technical and skeptical vs. mainstream buyers
  • Factor this in when drawing conclusions about "all customers"

Minimum viable sample: 5 independent data points per segment (interviews, reviews, tickets, or community posts) before building a persona or drawing a messaging conclusion for that segment. Below 5, present the material as raw signal, not as a finding.

Mode 2: Digital Watering Hole Research

Online communities are where customers speak without a filter. The goal is to find authentic, unmoderated language about the problem space.

Where to Look

Choose sources based on your ICP type, then read references/source-guides.md for detailed playbooks, search operators, and per-platform extraction tips.

ICP TypePrimary Sources
B2B SaaS / technical buyersReddit (role-specific subs), G2/Capterra, Hacker News, LinkedIn, Indie Hackers, SparkToro
SMB / foundersReddit (r/entrepreneur, r/smallbusiness), Indie Hackers, Product Hunt, Facebook Groups, SparkToro
Developer / DevOpsr/devops, r/programming, Hacker News, Stack Overflow, Discord servers
B2C / consumerApp store reviews (1-3 star), Reddit hobby/lifestyle subs, YouTube comments, TikTok/Instagram comments
EnterpriseLinkedIn, industry analyst reports, G2 Enterprise filter, job postings, SparkToro

Quick decision guide:

  • Have a product category? → Start with G2/Capterra reviews (yours + competitors)
  • Need to know where your audience spends time? → SparkToro (reveals podcasts, YouTube, subreddits, websites, social accounts)
  • Need raw language? → Reddit and YouTube comments
  • Need trigger events? → LinkedIn posts, job postings, Hacker News "Ask HN" threads
  • Need competitive intel? → Competitor 4-star reviews on G2; Product Hunt discussions; SparkToro competitor audience analysis
What to Extract from Each Source

For every piece of content you find:

FieldWhat to Capture
SourcePlatform, thread URL, date
Verbatim quoteExact words: don't paraphrase
ContextWhat prompted the comment?
SentimentPositive / negative / neutral / frustrated
Theme tagPain / trigger / outcome / alternative / language
Customer profile signalsRole, company size, industry hints from the post
Persist Captures Before Synthesizing

Save what you gathered before extracting themes from it: otherwise the provenance gate below is unenforceable and a re-run repeats the entire collection. Mirror the raw-evidence convention suede-competitor-profiling uses: one dated folder per run at customer-research/raw/<YYYY-MM-DD>/, one file per source inside it (reddit.md, g2-<competitor>.md, app-store.md), plus a captures.csv whose columns are the capture table above. Create the date folder fresh each run and never overwrite a prior date's: that is how you diff what moved in the market. Mode 1 assets (transcripts, tickets, win/loss notes, NPS verbatims) usually already live somewhere: don't copy them, record each in captures.csv by file path or system identifier plus date and segment, so every quote resolves to a named record either way.

Show full SKILL.md (679 more words)Show less
Research Synthesis Template

After gathering from multiple sources, synthesize into:

## Top Themes (ranked by frequency × intensity)

### Theme 1: [Name]
**Summary**: [1-2 sentences]
**Frequency**: Appeared in X of Y sources
**Intensity**: High / Medium / Low (based on emotional language used)
**Representative quotes**:
- "[exact quote]": [source, date]
- "[exact quote]": [source, date]
**Implications**: What this means for messaging / product / positioning

### Theme 2: ...

Persona Generation

When there are no reviews yet

Early-stage products (or new categories) lack first-party review data. Don't invent personas: walk outward through proxy sources, in order:

  1. Your own differentiator: what the product does differently defines who feels that difference most; write the hypothesis down as a hypothesis
  2. Direct competitors' reviews: their customers describe the problem space in their words (note what's praised and what's missing)
  3. Comparable products on marketplaces: Amazon/app-store reviews for adjacent solutions to the same job
  4. Adjacent brands sharing the audience: what else this buyer buys; their reviews reveal the buyer's broader language and values

Personas built this way are provisional: tag each with its proxy source, and replace proxy evidence with first-party evidence as real reviews arrive. The minimum viable sample above applies to proxy evidence too.

Persona Structure

Read references/persona-templates.md before writing the first persona of a run: it holds the full fill-in structure (profile, primary job, triggers, pains, desired outcomes, objections, alternatives, vocabulary, how to reach them). Personas written from memory drift field by field and stop being comparable.

Persona Anti-Patterns
  • Don't name them cutely ("Marketing Mary") unless your team finds it helpful: it's often a distraction
  • Don't average across segments: a persona that represents everyone represents no one
  • Don't invent details: if you don't have data on something, leave it blank rather than filling it in
  • Revisit quarterly: personas decay as your market and product evolve

Provenance Gate

Run this over the finished deliverable, before it goes out. Boundaries below forbids fabricated quotes, themes, sample sizes and frequency counts; this is what makes that checkable rather than aspirational.

  • Every verbatim resolves to a named capture record. Mode 2: platform, thread URL, and date, per the capture table above. Mode 1: the asset identifier or file, plus date and segment. A quote that cannot be attributed to a capture record is cut, never paraphrased into a theme, never rolled into a frequency count.
  • Recount the numbers at the same pass. "Appeared in X of Y sources" and every High/Medium/Low confidence label are recomputed from the capture records right now, not carried over from a draft. A confidence label that no longer matches the count gets downgraded, not defended.
  • Name the sample. Source mix, segment, date range, and total captures appear in the deliverable itself, so the reader can judge the base the conclusions sit on.

Deliverable Formats

Default deliverable: a research synthesis report (themes, quotes, patterns, implications) plus a VOC quote bank organized by theme. Produce those unless the user asked for something else.

Offer these instead or in addition when the goal calls for it: a persona document (1-3 personas), a jobs-to-be-done map (functional, emotional, social jobs by segment), a competitive intelligence summary (what customers say about competitors vs. you), or a research gap analysis (what you still don't know and how to find it).

Questions to Ask Before Proceeding

If context is unclear:

  1. What's the goal? Improve messaging? Build personas? Find product gaps? Understand churn?
  2. What do you already have? (transcripts, surveys, tickets, G2 reviews, nothing)
  3. Who is the target segment? (all customers, a specific tier, churned users, prospects who didn't buy)
  4. What's your product? (if not in the product marketing context file)

Don't ask all four at once: lead with #1 and #2, then follow up as needed.

Boundaries

  • Do not fabricate quotes, themes, sample sizes, sentiment, persona traits, or frequency counts.
  • Do not contact participants, record sessions, scrape restricted communities, or expose identifying data without explicit authorization and consent.
  • Do not present a convenience sample as representative; state source, segment, dates, sample size, and collection limits.
  • Do not decide product priorities or customer truth from synthesis alone; separate evidence, inference, and open questions.

Routing

  • Need final copy from customer language -> use suede-copy.
  • Need competitor-only evidence -> use suede-competitor-profiling.
  • Need ICP or positioning synthesis -> use suede-product-marketing.
  • Need churn, outbound, paid, or content application -> use suede-churn-prevention, suede-cold-email, suede-ads, or suede-content-strategy.
  • From those skills, route interview design, review mining, and evidence synthesis back to suede-customer-research.

© JasonColapietro, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/suede-customer-research of JasonColapietro/suede-creator-skills.

  • SKILL.md
  • CARD.md
  • agents/openai.yaml
  • evals/evals.json
  • references/persona-templates.md
  • references/source-guides.md

Open the folder on GitHubat commit e5f94d7

Compare with similar skills

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Suede Customer Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Suede Customer Research this skillJasonColapietro/suede-creator-skills127—~3.4kAutomated safety check: PassMIT
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Marketing Campaignaffaan-m/ECC277k1 repos~1.3kAutomated safety check: PassMIT
Icp Researchgrowthack88/growth-marketing-os116—~4.4kAutomated safety check: PassMIT
Copynicepkg/ai-workflow285—~3.1kAutomated safety check: PassMIT
Ad CreativeLeoYeAI/openclaw-marketing-skills1k8 repos~3.4kAutomated safety check: PassCustom licence

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Categories

Questions about Suede Customer Research

What does Suede Customer Research do?

Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas. Suede Customer Research is an agent skill from JasonColapietro/suede-creator-skills. Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas.

When should I use Suede Customer Research?

Suede Customer Research fits situations like: synthesizing what a defined customer segment actually says; tasks that involve Market research; tasks that involve Copywriting.

How do I install Suede Customer Research in Claude Code?

Run `npx skills add JasonColapietro/suede-creator-skills --skill suede-customer-research -a claude-code`. Or copy the skill folder (skills/suede-customer-research in JasonColapietro/suede-creator-skills) into .claude/skills/suede-customer-research in your project. Claude Code loads it when a task matches its description.

How do I install Suede Customer Research in Codex?

Run `npx skills add JasonColapietro/suede-creator-skills --skill suede-customer-research -a codex`. Or copy the skill folder (skills/suede-customer-research in JasonColapietro/suede-creator-skills) into .agents/skills/suede-customer-research in your project. Codex loads it when a task matches its description.

Can I use Suede Customer Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add JasonColapietro/suede-creator-skills --skill suede-customer-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/suede-customer-research, .gemini/skills/suede-customer-research, .github/skills/suede-customer-research and .opencode/skills/suede-customer-research in your project.

What does Suede Customer Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Suede Customer Research is instructions for the agent only.

Does Suede Customer Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Suede Customer Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Suede Customer Research use?

Suede Customer Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Suede Customer Research use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.5k tokens, read only when the agent opens those files.

What are the alternatives to Suede Customer Research?

Skills that share tags, products or a category with Suede Customer Research: Yao Positioning Skill (yaojingang/yao-open-skills, 1.3k stars), Marketing Campaign (affaan-m/ECC, 277k stars), Icp Research (growthack88/growth-marketing-os, 116 stars) and Copy (nicepkg/ai-workflow, 285 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Suede Customer Research?

JasonColapietro (a GitHub user) maintains it in JasonColapietro/suede-creator-skills, which has 127 GitHub stars. The repository holds 78 skills in this directory. The repository was last updated on October 10, 2026.

Source: JasonColapietro/suede-creator-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.