ditto-product-marketing

📁 ask-ditto/ditto-product-marketing 📅 1 day ago

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安装命令

npx skills add https://github.com/ask-ditto/ditto-product-marketing --skill ditto-product-marketing

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Skill 文档

Ditto for Product Marketing

Run positioning, messaging, competitive, pricing, and launch research using Ditto’s 300,000+ synthetic personas – directly from the terminal.

Full documentation: https://askditto.io/claude-code-guide

What Ditto Does

Ditto maintains 300,000+ AI-powered synthetic personas calibrated to census data across 15+ countries. You ask them open-ended questions and get qualitative responses with the specificity of real interviews.

92% overlap with traditional focus groups
95% correlation with traditional research (EY Americas validation)
Harvard/Cambridge/Stanford/Oxford peer-reviewed methodology
A 10-persona, 7-question study completes in 15-30 minutes
Traditional equivalent: 4-8 weeks, $10,000-50,000

API Essentials

Base URL: https://app.askditto.io Auth header: Authorization: Bearer YOUR_API_KEY Content-Type: application/json

Get a free API key (no credit card):

curl -sL https://app.askditto.io/scripts/free-tier-auth.sh | bash

Free keys (rk_free_): ~12 shared personas, no custom filters. Paid keys (rk_live_): custom groups, demographic filtering, unlimited studies.

The PMM Workflow (6 Steps)

IMPORTANT: Follow these steps in order. Questions MUST be asked sequentially – wait for all responses before asking the next.

Step 1: Recruit Your Panel

curl -s -X POST "https://app.askditto.io/v1/research-groups/recruit" \
  -H "Authorization: Bearer $DITTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "US Product Managers 30-50",
    "group_size": 10,
    "filters": {"country": "USA", "age_min": 30, "age_max": 50}
  }'

Save the uuid from the response.

CRITICAL: Use group_size not size. Use group uuid not id. State filter uses 2-letter codes (“MI” not “Michigan”). Income filter NOT supported.

Step 2: Create Study

curl -s -X POST "https://app.askditto.io/v1/research-studies" \
  -H "Authorization: Bearer $DITTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "title": "Positioning Validation - [Product Name]",
    "objective": "Validate positioning against target ICP",
    "shareable": true,
    "research_group_uuid": "UUID_FROM_STEP_1"
  }'

Save the study id. Always set shareable: true.

Step 3: Ask Questions (One at a Time)

curl -s -X POST "https://app.askditto.io/v1/research-studies/STUDY_ID/questions" \
  -H "Authorization: Bearer $DITTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"question": "Your open-ended question here"}'

Returns job_ids. Poll ALL of them before asking the next question.

Step 4: Poll Until Complete

curl -s "https://app.askditto.io/v1/jobs/JOB_ID" \
  -H "Authorization: Bearer $DITTO_API_KEY"

Poll every 10-15 seconds. Status: queued -> started -> finished. ALL job_ids must show finished before asking the next question.

Step 5: Complete the Study

curl -s -X POST "https://app.askditto.io/v1/research-studies/STUDY_ID/complete" \
  -H "Authorization: Bearer $DITTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"force": false}'

Triggers AI analysis: summary, segments, divergences, recommendations.

Step 6: Get Share Link

curl -s -X POST "https://app.askditto.io/v1/research-studies/STUDY_ID/share" \
  -H "Authorization: Bearer $DITTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"enabled": true}'

Returns a public URL anyone can view without authentication.

The 8 PMM Study Types

Choose the right study for your goal. Each type has a proven 7-question framework. See @study-templates.md for complete question sets.

Study Type	When to Use	Key Output
Positioning Validation	Testing how your positioning lands with target customers	Positioning scorecard, competitive alternative map, value resonance ranking
Messaging Testing	Comparing 3-4 messaging variants	Message performance ranking, language harvest, audience-message fit
Competitive Intelligence	Understanding how the market perceives you vs competitors	Competitive perception matrix, landmine questions, battlecard
Pricing & Packaging	Validating willingness-to-pay and feature-tier allocation	Price sensitivity band, feature-tier recommendation, packaging preference
GTM Validation	Validating channel, motion, and outreach strategy	Channel preference matrix, buying committee map, motion recommendation
Product Launch	Pre-launch concept validation or post-launch sentiment	Launch readiness scorecard, objection library, feature priority ranking
Buyer Persona Development	Building data-backed personas from scratch	Persona documents with demographics, psychographics, decision criteria
Brand Perception	Tracking brand health and competitive positioning	Brand association map, trust scorecard, brand extension potential

Choosing the Right Study

Need to validate your positioning?     -> Positioning Validation
Testing which message wins?            -> Messaging Testing
Understanding competitive dynamics?    -> Competitive Intelligence
Setting or validating price?           -> Pricing & Packaging
Planning your go-to-market?            -> GTM Validation
Preparing for a launch?                -> Product Launch
Building or refreshing personas?       -> Buyer Persona Development
Tracking brand health over time?       -> Brand Perception

One Study, Multiple Deliverables

A single 10-persona, 7-question study produces raw material for MULTIPLE outputs. See @deliverables.md for the full mapping.

One Ditto Study (~20 min)
    |-> Positioning scorecard (5 min)
    |-> Competitive battlecard (5 min)
    |-> Messaging hierarchy (5 min)
    |-> Objection handling guide (3 min)
    |-> Customer quote bank (3 min)
    |-> Blog article draft (10 min)
    |-> Sales one-pager (5 min)

Total: ~60 min from zero to complete PMM kit
Traditional: 3-6 weeks, $15-50K

Demographic Filters

Filter	Type	Examples	Notes
country	string	“USA”, “UK”, “Canada”, “Germany”	Required
state	string	“TX”, “MI”, “CA”	2-letter codes ONLY
age_min	integer	25, 30, 45	Recommended
age_max	integer	45, 55, 65	Recommended
gender	string	“male”, “female”, “non_binary”	Optional
is_parent	boolean	true, false	Good for family/consumer
education	string	“high_school”, “bachelors”, “masters”, “phd”	Optional
employment	string	“employed”, “self_employed”, “retired”	Optional
industry	array	[“Healthcare”, “Technology”]	Optional

Advanced: Multi-Segment Comparison

Run the SAME study across multiple groups to compare segments:

Group A: SMB decision-makers (age 28-40)
Group B: Enterprise evaluators (age 35-55)
Group C: Technical buyers (education: bachelors+)

Same 7 questions, different panels. Claude Code produces a comparative analysis showing how positioning, pricing, and messaging land differently by segment.

Advanced: Cross-Market Research

Ditto covers 15+ countries (65% of global GDP). Run the same study across USA, UK, Germany, and Canada simultaneously. One hour, four markets. Traditional equivalent: 3-6 months, $100-200K.

Common Mistakes

Asking closed-ended questions (“Do you like X?” -> “What’s your reaction to X?”)
Batching questions (ask one, wait for ALL responses, then ask next)
Using full state names instead of 2-letter codes
Using size instead of group_size in recruitment
Using numeric id instead of string uuid for research groups
Skipping the complete step (you miss the AI-generated analysis)
Not setting shareable: true at creation time
Asking leading questions (“Don’t you think X is great?”)
Designing all questions before researching the product/market first
Running only one study when iterative phases would produce deeper insight

Failed Attempts (What Doesn’t Work)

Yes/no pricing questions (“Would you pay $X?”) produce unreliable data. Use Van Westendorp-style ranges instead.
Jargon-heavy questions get shallow responses. Use plain language: “Walk me through what it’s like” not “Evaluate the UX of this experience.”
Leading positioning (“Our revolutionary product…”) biases responses. Describe the product neutrally and let personas react.
Single-pass studies for complex products miss depth. Use 2-3 phase iterative approach: Pain Discovery -> Deep Dive -> Concept Test.
Skipping web research before designing questions. Claude Code should ALWAYS research the product, market, and competitors before writing questions.

Limitations

Ditto personas have NOT used your specific product. For:

Actual UX feedback from real users -> use real user testing
Legal/compliance decisions -> use human research
Safety-critical product decisions -> use human validation
Exact quantitative metrics (NPS, conversion) -> use real data

Recommended hybrid: Ditto for the fast first pass (80% of insight), then human research only where it truly matters (the 20% requiring real customer nuance).