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Designing Surveys

  • 1.9k installs
  • 1.2k repo stars
  • Updated July 16, 2026
  • refoundai/lenny-skills

designing-surveys is an agent skill that guides effective survey design with CSAT, PMF, prioritization constraints, and respondent timing from product leader frameworks.

About

The designing-surveys skill helps developers and product teams create effective customer surveys, NPS measurements, product-market fit studies, and feedback collection flows using frameworks from nine product leaders. It clarifies survey goals, chooses between CSAT, NPS, PMF, or custom metrics, designs single-variable questions, and targets respondents with fresh relevant experience. Core principles flag NPS scientific flaws in favor of CSAT scales, force prioritization with three-choice constraints, survey best customers within three to six months of signup, and use onboarding friction that improved conversion in real examples. It warns against double-barreled questions, unlimited option lists, wrong timing, NPS worship, and mobile hidden scale options. Deep dive references cover ten guest insights and related skills for North Star metrics, product vision, roadmap prioritization, and OKRs. Use when creating customer surveys, measuring satisfaction, running PMF questionnaires, or improving feedback collection mechanisms before product decisions.

  • Frameworks from nine product leaders for survey design and feedback systems.
  • Recommends CSAT over NPS with forced three-choice prioritization patterns.
  • Targets customers three to six months post-signup for fresh before-state memory.
  • Flags double-barreled questions, wrong timing, and mobile scale visibility issues.
  • Routes to North Star metrics, product vision, roadmap, and OKR related skills.

Designing Surveys by the numbers

  • 1,858 all-time installs (skills.sh)
  • +1 installs in the week ending Jul 28, 2026 (Skillselion tracking)
  • Ranked #246 of 3,301 Productivity & Planning skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

designing-surveys capabilities & compatibility

Capabilities
metric selection between csat, nps, and pmf · single variable question design · forced prioritization constraint patterns · respondent timing and segment guidance · common survey mistake detection
Use cases
research · planning · copywriting
From the docs

What designing-surveys says it does

Help the user design effective surveys using frameworks from 9 product leaders
SKILL.md
Customer satisfaction, a simple CSAT metric, is better.
SKILL.md
npx skills add https://github.com/refoundai/lenny-skills --skill designing-surveys

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Listed on Skillselion
Installs1.9k
repo stars1.2k
Security audit3 / 3 scanners passed
Last updatedJuly 16, 2026
Repositoryrefoundai/lenny-skills

How do I design a survey that measures one thing per question, forces prioritization, and targets the right customers at the right time?

Design customer surveys, CSAT and PMF questionnaires, and feedback flows with single-variable questions, forced prioritization, and respondent timing guidance.

Who is it for?

Developers and product teams creating customer surveys, PMF studies, or feedback collection before roadmap decisions.

Skip if: Skip when you only need North Star metric definition without survey instrument design.

When should I use this skill?

Use when creating customer surveys, NPS or CSAT measurements, PMF questionnaires, or feedback collection mechanisms.

What you get

A survey plan with metric choice, clean question design, respondent targeting, and flagged common mistakes before launch.

By the numbers

  • Applies frameworks from 9 product leaders

Files

SKILL.mdMarkdownGitHub ↗

Designing Surveys

Help the user design effective surveys using frameworks from 9 product leaders who have built rigorous research and feedback systems.

How to Help

When the user asks for help with surveys:

1. Clarify the goal - Determine if they're measuring satisfaction, identifying problems, or prioritizing features 2. Choose the right metric - Help them select between NPS, CSAT, PMF survey, or custom approaches 3. Design clean questions - Ensure each question measures one thing precisely 4. Target the right respondents - Help them reach users with fresh, relevant experience

Core Principles

NPS is scientifically flawed

Judd Antin: "NPS is the best example of the marketing industry marketing itself. The consensus in the survey science community is that NPS makes all the mistakes. Customer satisfaction, a simple CSAT metric, is better. It has better data properties, it is more precise, it is more correlated to business outcomes." Use CSAT with 5-7 item scales instead.

Force prioritization with constraints

Nicole Forsgren: "Let them pick three, just three. Of those three, how often does this affect you? Is this hourly? Is this daily? Is this weekly?" Limit respondents to their top barriers to keep data clean, then measure frequency to weight impact.

Survey your best customers at the right time

Gia Laudi: "Very importantly, they signed up for your product recently enough that they remember what life was like before. Generally, we say that's in the three to six-month range." Target customers who have been using the product 3-6 months so their memory of the 'before' state is fresh.

Onboarding surveys improve conversion

Laura Schaffer: "We just asked for forgiveness and put these questions into the signup flow. An improved conversion by like 5%, just improved signups." Adding 'good friction' in the form of targeted questions can increase conversion by reassuring users they're in the right place.

Avoid double-barreled questions

Nicole Forsgren: "You're asking four different questions there. If someone answers yes, was it the build? Was it the test? Was it slow or was it flaky?" Ensure each survey question only asks about one specific variable.

Use MaxDiff for feature prioritization

Madhavan Ramanujam: "Identify the most important for you, and the least important. If you do this a few times, you will be able to prioritize the entire feature set in a relative fashion." MaxDiff (Most/Least) surveys are superior to simple ranking for identifying value drivers.

Questions to Help Users

  • "What specific decision will this survey inform?"
  • "Are you asking about one thing per question, or multiple things?"
  • "Who are your 'best' customers and when did they sign up?"
  • "Are all scale options visible on mobile without scrolling?"
  • "How will you force respondents to prioritize rather than rate everything high?"

Common Mistakes to Flag

  • Double-barreled questions - Asking about speed AND complexity in one question
  • Too many options - Allowing respondents to select unlimited items instead of forcing prioritization
  • Wrong timing - Surveying customers who are too new (no experience) or too old (forgot the 'before')
  • NPS worship - Relying on a metric with known scientific flaws over simpler, better alternatives
  • Hidden scale options - Mobile surveys where users can't see all options create response bias

Deep Dive

For all 10 insights from 9 guests, see references/guest-insights.md

Related Skills

  • Writing North Star Metrics
  • Defining Product Vision
  • Prioritizing Roadmap
  • Setting OKRs & Goals

Related skills

FAQ

Who is designing-surveys for?

Developers and software engineers designing customer research surveys, satisfaction metrics, and PMF feedback flows.

When should I use designing-surveys?

When building surveys for satisfaction, problem identification, feature prioritization, or onboarding conversion research.

Is designing-surveys safe to install?

Review the Security Audits panel on this page before installing in production.

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