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Customer Experience

Knowledge Base Content Effectiveness Survey

Measures article findability, clarity, completeness, and task-completion outcomes for knowledge base users. Use to identify content gaps and prioritize help center improvements.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

24 questions · ~11 min
Q01
Message

Welcome, and thank you for taking a few minutes to share your feedback about our knowledge base. This survey asks about your most recent experience finding and using a knowledge base article. Your responses are confidential, will be reported only in aggregate, and will help us improve the help center. Participation is voluntary—you may stop at any time. There are no right or wrong answers; we simply want your honest opinions. Estimated time: 11 minutes.

Q02
Dropdown

When did you most recently read an article in our knowledge base?

  • Within the last 7 days
  • 8–30 days ago
  • 31–90 days ago
  • More than 90 days ago
  • Not sure
Q03
Multiple Choice

How did you find that article?

  • Typed a query in our site search
  • Browsed categories or menus
  • Used Google or another search engine
  • In-product link
  • Link from a support agent or email
  • Link from a community or forum
  • Saved bookmark
  • Other (please specify)
Q04
Message

The following statements are about the article you read most recently. Please indicate how much you agree or disagree with each one.

Q05
Multiple Choice

Did this article enable you to complete your task?

  • Yes, completely
  • Yes, partially
  • No
  • I was just browsing
Q06
Long Text

What, if anything, was missing or unclear in the article?

Q07
Dropdown

Which best describes your role?

  • Individual contributor
  • Team lead or manager
  • Executive or founder
  • Consultant or agency
  • Educator or trainer
  • Student
  • Prefer not to say
Q08
Message

Thank you for your time—your feedback helps us improve the knowledge base for everyone.

Q09
Multiple Choice

Which type of article did you read most recently?

  • Getting started / Onboarding
  • How-to / Step-by-step
  • Troubleshooting / Error resolution
  • Reference / API or developer docs
  • Release notes / What's new
  • Account, billing, or licensing
  • Other (please specify)
Q10
Multiple Choice

When you use search on our knowledge base, how often does it return a helpful article?

  • Always
  • Often
  • Sometimes
  • Rarely
  • Never
  • I have not used search
Q11
Opinion Scale

The article was easy to understand.

Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q12
Opinion Scale

Overall, how easy was it to use the article to achieve your goal?

Scale: 1 – 7
Min:Very difficultMax:Very easy
Q13
Multiple Choice

Which improvements would most help you find the right articles? Select all that apply.

  • Clearer article titles
  • Better search relevance
  • More tags or filters
  • Better categorization
  • More cross-links between articles
  • Show article dates and last-updated info
  • None of the above
Q14
Dropdown

Which industry best describes your organization?

  • Technology / Software
  • Finance / Insurance
  • Healthcare / Life sciences
  • Education
  • Manufacturing
  • Retail / eCommerce
  • Government / Nonprofit
  • Media & Communications
  • Other
  • Prefer not to say
Q15
Dropdown

Approximately how long did it take you to find that article?

  • Less than 1 minute
  • 1–3 minutes
  • 4–10 minutes
  • 11–20 minutes
  • More than 20 minutes
  • I don't remember
Q16
Opinion Scale

The article covered the topic completely.

Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q17
Opinion Scale

How likely are you to use our knowledge base again in the future?

Scale: 1 – 7
Min:Very unlikelyMax:Very likely
Q18
AI Interview

Thank you for your survey responses. I'd like to ask a couple of follow-up questions to better understand your knowledge base experience. What was the main reason you visited the knowledge base on your most recent visit, and how well did it meet your expectations?

Q19
Dropdown

How many employees work at your organization?

  • 1–9
  • 10–49
  • 50–249
  • 250–999
  • 1,000–4,999
  • 5,000+
  • Prefer not to say
Q20
Opinion Scale

How easy was it to identify the right article from the search results or category listing?

Scale: 1 – 7
Min:Very difficultMax:Very easy
Q21
Opinion Scale

The information in the article was accurate and up to date.

Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q22
Long Text

Based on your responses in this survey, please share any additional thoughts or feelings about your knowledge base experience.

Q23
Opinion Scale

The article was well-organized and easy to scan.

Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q24
Opinion Scale

The article included helpful examples, screenshots, or visuals.

Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Includes an AI follow-up interview that adapts based on the respondent's specific ratings, letting you dig into why an article was rated low on clarity or completeness rather than just capturing a static score.
  • Combines findability metrics (search success rate, time-to-find, ease of locating the right article) with content-quality ratings (clarity, completeness, accuracy, organization, visuals) and a task-completion outcome question in one flow.
  • Captures open-text detail on what was missing or unclear plus a multi-select on desired improvements, giving concrete, actionable content-gap data instead of only satisfaction scores.
  • Segments results by role, industry, and company size so you can prioritize help-center fixes for the users and use cases that matter most.

SurveySparrow

Knowledge Article Feedback Template

A fielding-ready template focused specifically on gathering feedback for individual knowledge base articles. It's conversational in style, which suits SurveySparrow's chat-form UI, but the question set appears fixed rather than adaptive to each respondent's answers.

What it does well

  • Purpose-built for article-level feedback rather than generic satisfaction surveys
  • Conversational form format may improve completion rates for quick feedback
  • Part of a broader survey platform with standard reporting/dashboard tools

Where it falls short

  • No adaptive AI follow-up questioning based on how a respondent scores an article
  • No published methodology or per-response quality scoring for feedback reliability
  • No voice-based interview option or guided task/screen-share capability

QuestionPro

Company - Knowledge Management Survey Template

This template addresses broader organizational knowledge management (how knowledge is created, shared, and used internally) rather than help-center article findability and clarity specifically. It's a static, fielding-ready survey backed by QuestionPro's established analytics suite, but it's a different scope than a content-effectiveness audit.

What it does well

  • Established enterprise survey platform with mature reporting and segmentation tools
  • Customizable question library for broader knowledge-sharing assessments
  • Likely supports standard skip logic and multi-channel distribution

Where it falls short

  • Framed around general knowledge management, not specifically knowledge base article findability/clarity/task completion
  • No adaptive AI follow-up interview or voice AI interview option
  • No transparent, per-response quality scoring or documented prompt methodology

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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