Conjoint Analysis: How to Understand What Customers Are Really Willing to Pay For
Customers choose combinations, not features. Conjoint analysis shows what really matters and what people pay for.
Imagine a familiar scene in any product team. You have a product. Over time, it grows more features, functions, and improvements. Every new meeting sounds примерно одинаково:
— We absolutely need a closed courtyard, that’s a key value!
— No, location is what really matters.
— Customers definitely want ready-to-move-in renovation.
— No, price is more important.
— And let’s add an AI assistant, that’s trending now.
And every argument sounds very convincing.
But here’s the problem: In real life, a customer doesn’t choose one parameter.
They choose a combination of attributes.
An apartment is not just price.
A phone is not just a camera.
A bank is not just an interest rate.
And this is where one of the most powerful marketing research methods comes in — Conjoint Analysis.
What is Conjoint Analysis
Conjoint analysis is a marketing research method that helps you understand:
which product attributes are really most important to customers
which combinations of features they choose
how much they are willing to pay for each attribute.
The method was developed in the 1970s by Professor Paul Green at Wharton School and is now considered one of the most powerful tools for product and pricing decisions.
In simple terms, instead of asking:
“How important is organic coffee to you?”
we ask a more honest question:
“Which of these two options would you choose?”
For example:
Option A
— restaurant in the city center
— average check $15
— standard menu
— regular coffee
Option B
— restaurant in a residential area
— average check $20
— chef’s menu
— organic coffee and farm products
What will the customer choose? After several choices like this, we start to understand not just preferences, but the decision-making logic.
Where Conjoint Analysis Is Used
Today, conjoint is one of the most widely used tools in:
Product development
What features a new product should have.
Pricing
What customers are willing to pay for.
CX research
What actually drives brand choice.
Concept testing
Which product concept will be most successful.
Examples of Use
Medical Centers
What influences the choice of a clinic:
consultation price
doctor’s qualification
modern equipment
appointment speed
location
availability of online consultations
And most importantly — which combination of factors makes a clinic the most attractive to a patient.
Banks
What influences the choice of a card:
cashback
interest on balance
mobile app
bank brand
Mastercard and Visa actively use conjoint to design new financial products.
FMCG
Procter & Gamble regularly uses conjoint to test:
flavors
packaging
price
product size
One of the Most Famous Cases
In the early 2000s, Dell used conjoint analysis to design laptop configurations. The study revealed something unexpected.
Users were willing to:
sacrifice more memory
sacrifice a more powerful processor
but they were not willing to sacrifice the weight of the laptop.
After that, Dell changed its product line and increased sales in the mobile laptop segment.
Source:
Green & Srinivasan, Journal of Marketing Research.
Why Traditional Surveys Often Give the Wrong Answers
If you ask a customer:
“How important is modern equipment in a medical center?”
Almost everyone will say:
— Very important.
But in reality, a person might choose:
a clinic closer to home
a lower price
faster appointment availability
Conjoint works better because it simulates a real choice.
This is confirmed by many studies. For example, Orme (Sawtooth Software), one of the leading experts in conjoint analysis, shows that choice-based conjoint predicts real purchases much more accurately than traditional surveys.
Source:
Orme, Getting Started with Conjoint Analysis, 2010.
How Conjoint Works
Conjoint studies use attributes and levels.
For example, when choosing a school.
Attribute:
Tuition fee
Levels:
— $500 per month
— $900
— $1300
Attribute:
Language of instruction
Levels:
— local language
— English
— bilingual
Attribute:
Additional opportunities
Levels:
— basic program
— sports and clubs
— international program and exchanges
These parameters are combined into school profiles.Parents are then asked to choose between them.
After analysis, we can determine:
importance of each attribute
utility of each level
optimal product configuration.
What Businesses Get in the End
After a conjoint study, a company gets answers to key questions:
1. What really drives choice
For example:
price — 32%
doctor qualification — 27%
equipment — 18%
appointment speed — 13%
location — 10%
2. Willingness to Pay
For example, customers are willing to pay more for:
+20% for a doctor with international qualifications
+15% for modern equipment
+10% for same-day appointments
3. The Ideal Product Configuration
You can build a product with the maximum probability of being chosen.
How Often Should You Run Conjoint Studies
This is a good question, and there are scientific recommendations. According to Harvard Business Review and McKinsey, conjoint studies should be conducted:
every time product strategy changes.
On average, companies run them:
every 1–2 years in stable markets
every 6–12 months in fast-changing industries (tech, fintech)
A Deloitte (2022) study shows that companies that regularly use conjoint in product strategy make more profitable pricing decisions.
Why Conjoint Is Experiencing a Second Renaissance
In the past, these studies were expensive and slow.
A typical project looked like this:
3 weeks to design the study
2 weeks for fieldwork
1–2 weeks for analysis
Today, this is changing thanks to AI.
AI can:
generate the research design
optimize samples
automatically calculate utility scores
build product simulations
What used to take a month can now be done in hours.
Conjoint Is Not Just Research
It’s a way to stop arguing inside the company.
Because when you have real data, you understand:
what customers are willing to pay for
what can be removed from the product
what should be strengthened
And sometimes the results are surprising.
For example, customers are often willing to pay more for simplicity, not for more features.
The Next Time a Product Debate Starts
“This feature is a must-have.”
Try asking a different question:
Are customers willing to pay for it?
And if you want an honest answer — ask them to choose between two options.
Sometimes one small choice tells you more than a hundred surveys.
