Free KANO analysis Template Alternatives

Have you ever experienced this situation: when your team discusses new features, someone thinks this one is important, someone else thinks that one is more urgent, and you argue without reaching a conclusion? Or after product launch, you find users just aren't interested in certain features?

Actually, all the problems mentioned above can be well solved with KANO analysis. It's amature way to categorize needs, helping you clearly identify: which features users feel should be there and are essential basic needs; which features, when delivered, bring extra surprise and delight—these are excitement needs; and which features, whether present or not, don't affect user satisfaction—these are indifferent needs.

And SurveyMars, as the overseas brand of "Wenjuanxing," not only helps you easily design KANO surveys, but also provides ready-made KANO analysis templates, so you don't have to build from scratch. In this article, I'll walk you through what KANO analysis is, and how to use SurveyMars's free templates to do it right.

What Is a KANO analysis Template?

A KANO analysis template is a pre-designed questionnaire framework used to collect and analyze user attitudes toward different features, finally categorizing needs into different types.

This template typically includes:

Positive and negative questions foreach feature

Standard five-level options (Like,Expect, Neutral, Tolerate, Dislike)

Automatic classification rules toconvert user responses into need categories

Visual charts showing each feature'sposition at a glance

The advantage of using this template is obvious: you don't need to design question formats yourself, or remember complex classification rules. Just put in your features, send to users, and SurveyMars automatically calculates for you.

Why Are KANO analysis templates So Important?

Many product teams know the KANO model is good, but few actually use it. Why? Because doing it manually is too troublesome.

Save Time and Effort, No Need to Start from Zero

I know a product manager who had heard about KANO for a long time but never dared to use it. She said: "For each feature, I need to design positive and negative questions, then对照表格 classify one by one. After dozens of features, my eyes get tired."

Later she used SurveyMars's KANO analysis template and found things became simpler. List the features, the template automatically generates the survey. Data collected, classification results come out directly, complete with Better-Worse coefficient charts.

See? With the right tool, complex things can become simple.

Results Are Intuitive, Team Understands at a Glance

The biggest challenge with KANO analysis is explaining the results clearly to the team. Just saying "this is basic, that is excitement," everyone might not understand.

SurveyMars's template directly generates a four-quadrant chart. Which feature sits where, crystal clear. In meetings, open the chart, point and say: these four features must be built, these three can be pushed back, those two just don't do. The team reaches consensus immediately.

How to Use SurveyMars's KANO analysis Template?

Alright, principles clear. Now let's jump into practice.

Step 1: Find the Template

Log in to SurveyMars, search for "KANO" in the template library, and you'll see the ready-made KANO analysis template.

Click in, the template is already designed:

Survey has simple instructions telling users how to fillit out

Each feature corresponds to positiveand negative questions

Options are the standard five-levelscale

You just need to replace the example features in the questions with the features your product wants to test.

Step 2: Fill in the Features You Want to Test

Take your previously listed candidate features, and fill them into the template one by one.

For example, if you're making a budgeting app and want to test these features:

Feature A: Auto-sync bank transactions

Feature B: Generate annual spendingreport

Feature C: Set monthly budgetreminders

Feature D: Support shared ledger withothers

In the template, each feature needs two questions:

Positive: If the app supports auto-syncing bank transactions, how would you feel?

Options: Like, Expect, Neutral, Tolerate, Dislike

Negative: If the app does NOT support auto-syncing bank transactions, how would you feel?

Options same as above

Fill in all four features, and the survey is ready.

Step 3: Distribute Survey, Collect Data

Survey ready? Next step is sending it to users.

SurveyMars supports multi-device filling—mobile and computer. You can generate a QR code from the link, share it in user groups, or put it in-product for users to fill voluntarily.

Watch sample size. Generally, each user group ideally has 30+ valid responses for results to have reference value.

Step 4: View Classification Results

After data collection, SurveyMars automatically classifies for you.

Open the results page, you'll see:

Each feature's need category (Basic,Performance, Excitement, Indifferent)

Count statistics for each category

Better-Worse coefficient chart, witheach feature plotted in four quadrants

This chart is especially intuitive: top right is Performance needs, top left is Excitement needs, bottom right is Basic needs, bottom left is Indifferent needs.

Step 5: Interpret the Better-Worse Coefficient Chart

Chart's ready, how to look at it?

Top right (Performance): Better coefficient is relativelyhigh, Worse coefficient absolute value is also relatively high. Thesefeatures, if implemented, can increase satisfaction; if not implemented, will decreasesatisfaction. They have the highest priority

Bottom right (Basic): Better coefficient isn't very high,but Worse coefficient absolute value is relatively high. If these featuresaren't implemented, users will be very dissatisfied; if implemented, userswill take them for granted. Must guarantee them

Top left (Excitement): Better coefficient is relativelyhigh, but Worse coefficient absolute value is relatively low. If thesefeatures aren't implemented, users won't mind; if implemented, users willbe pleasantly surprised. Can use for differentiation

Bottom left (Indifferent): Both Better and Worse coefficientsare relatively low. Implementing or not has relatively little impact onusers. Can consider abandoning

What to Do After Getting Results?

Analysis done, don't just leave the report aside.

Basic needs must be guaranteed. First check if these featurescurrently exist; if not, quickly add them; if they do, ensure stableexperience

Performance needs must be continuouslyoptimized. This iswhere you compete with rivals; the better you do them, the more satisfiedusers will be

Excitement needs should be invested inappropriately. Can beused to create surprises, improve口碑，but don't spend too many resources

Indifferent needs should be decisivelycut. Don't waste timeon things users don't care about

Using SurveyMars's KANO analysis templates, not only helps you understand users better, but also lets the team argue less and do more.

Frequently Asked Questions

Q: Is SurveyMars's KANO analysis template free?

A: Yes, templates in the library can be used for free. Creating surveys, collecting data—basic functions are free.

Q: I've never done KANO analysis before, can I use this template well?

A: No problem. The template already has the format and question design handled. You just need to fill in your features, send to users, and then look at the results.

Q: How many features are suitable to test in one survey?

A: 10-15. Each feature needs positive and negative questions; if there are too many features, the survey will be too long, and users might lose patience filling it out.

Q: Why can't I understand the Better-Worse coefficient chart?

A: Don't worry, SurveyMars's results page has simple text explanations telling you which category each feature belongs to. The chart is assist, looking at the text conclusions first is fine.

Q: What if the classification results differ from what I thought?

A: Trust the data. Sometimes our intuition and users' real thoughts have obvious gaps. If the survey results differ from expectations, it shows this survey was valuable—it helped us discover problems we previously overlooked.