Conjoint Analysis 101: What, Types, Working [+4 Tools]

Learn how to use conjoint analysis to understand the features of your products or services your customers love the most.

As a business owner, you can choose what functionalities you want to include in your products/services. Later, you need to go to the market and gather customer reviews to understand whether the existing features are good to go for the long term or if there is need for improvements.

To help you with the analysis of such vast customer data, conjoint analysis is the appropriate analytical method. Save time by reading this ultimate guide on conjoint analysis that helps you understand the concept from the foundation level.     

What is Conjoint Analysis? 

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Conjoint analysis is a common statistical method of pricing and product research. The method uncovers customers’ choices through market surveys. Then it analyzes survey responses to select and predict the followings: 

• Product functionalities and features
• Assess pricing sensitivity
• Market share
• When customers will adopt new services or products

Different industries frequently use this statistical analysis for all types of consumer goods and services like the ones mentioned below, but the list goes beyond these: 

• Consumer durables
• Smartphones and tablets
• Smart home devices and wearables
• Electronics and electrical products
• Investment products

The primary goal of conjoint analysis is to predict what features customers want in a new product. Hence, businesses do not need to invest additional budget in market surveys after launching a product that does not align with customers’ needs.

Why and When do you need Conjoint Analysis?

Developing, testing, and marketing a product or service is a costly affair. A product failure can break the entire business, and trust us this happened a lot. Hence, you need to run a conjoint analysis program around your prototype product before producing it at massive levels. 

If the result of this quantitative analysis comes positive, you can begin mass production. If the outcome is negative, you need to include the features customers want and release the product to the public.

But why conjoint analysis for market survey and not any other methods? That is a valid question that many business managers, leaders, and owners ask. 

Because usual rating-based surveys are not effective for all the features and functionalities of a product. A consumer good contains many unrelated features, and comparing them all in one survey will become an apple-to-orange comparison. 

Contrarily, the conjoint analysis filters the survey participants’ responses, like their preferences, dislikes, etc., for different features. Ultimately, it delivers data that can uniformly say what the customers like and which elements will drive sales in the market. 

Now, here are the business scenarios where you need to apply conjoint analysis: 

Product Price Discovery

When you need to create a new or revised product pricing, conjoint analysis is the most effective tool. You ask customers direct questions to value various features of a product. Then, analyze the survey data and increase or decrease the price according to the weightage of the feature that is most valued. 

Research and Development (R&D)

Since product R&D is a costly affair, you can not just run R&D projects for all the features. By performing a conjoint analysis, you understand which features are most important and develop only those. It helps you to run R&D through a budget. 

Sales and Marketing 

If you need to run targeted marketing campaigns for different customer segments, you can use conjoint analysis. It will suggest how to distinguish the marketing materials like brochures, website landing pages, discount offers, online advertising, and more for various customer groups.  

Examples of Conjoint Analysis

Freemium Plan for Applications

Nowadays, software companies launch a freemium plan for their apps. Users can access the application for free and use a few important features. Now, the developers perform conjoint analysis to figure out which features are most popular. 

Then, they would place those features behind a paywall to earn money through paid subscriptions.

Headphone Jacks of iPhone

In 2016, Apple removed headphone jacks from all of its iPhone models. It freed up space so that Apple could introduce new functionalities in iPhones. It is fair to conclude that Apple ran a conjoint analysis and discovered that customers preferred other features over the headphone jack.

Mobile Carrier Services Offering

Mobile network service providers often run conjoint analyses to revise plan features to make more profits without losing the customer base. For example, the carrier sends a combination of Attributes like Price, Calls, Mobile Data, International Minutes, and Texts.

They can include different Levels for these Attributes. One combination could be Price: $20; Calls: Unlimited; Texts: Unlimited; International Minutes: Zero; Mobile Data: 10 GB shareable.

Now, the carrier will analyze all inputs from all the combinations to figure out which combination will fetch the maximum revenue. 

A restaurant or ice cream brand wants to launch new flavors of ice cream. Instead of setting the flavors on their own, they could go to the public with conjoint analysis surveys. The analyses of such survey data would reveal which flavor the customers will like the most.        

Pros of Conjoint Analysis

• The analysis makes it possible for businesses to measure the individual preferences of their customers. 
• You can get insights on hidden drivers and include or implement them in your products and services.
• This study of consumers and features allows you to create a need-based segmentation of the customer base. 
• It makes you aware of the tradeoffs people are willing to make while comparing multiple functionalities.

Cons of Conjoint Analysis

• The design of this analysis is complex in nature. Hence, not everyone can perform it or analyze the data procured by the surveys.
• Such analysis has to be done regularly. It will be of no use if companies conduct it once a year.
• If the surveys are not designed properly, they might end up containing overvalued or undervalued variables.
• When new or unimportant categories are included, respondents might find it difficult to explain or not feel interested at all.

Types of Conjoint Analysis

Depending on the business and its products/services, there could be many types of conjoint analysis. However, the followings are highly popular: 

Adaptive Conjoint Analysis

Here, you send one survey to a customer group. Analyze the data and send another survey by customizing the feature combinations based on the previous responses. 

In this type, you show customers a menu of features for a smartphone. The survey participant will choose the features, and then the original survey would show up.

Choice-Based Conjoint Analysis

It is the most basic one, where you send a few combinations of features. The customer selects one product from each combination. 

MaxDiff Conjoint Analysis

In this conjoint analysis method, the survey participants organize combinations of functionalities from best to worst. 

Full-Profile Conjoint Analysis

Here, you present the customer with a complete profile of features for multiple products like smartphones. The customer needs to choose one from all the products. 

Working of Conjoint Analysis

This statistical analysis method works by breaking the service or product into its functional elements. These elements are Attributes, and their values are the Levels.

In the next step, you need to test multiple combinations of the Attributes and Levels. Testing means sending 8 to 12 survey questions to a group of customers and asking them to choose the final products for different sets of Attribute and Levels combinations.

Experts call outputs from such surveys Consumer Preferences. You shall use Consumer Preferences data to create a Preference Score.

For instance, a conjoint analysis for a new smartphone should contain these Attributes: Brand, Screen Size, Color, and Price. The Levels for this study will be values for these Attributes. For instance, iPhone for Brand; 6” for Screen Size; Silver for Color; $600 for Price, etc.

Once you get the Preference Score, you can input that into a Market Share Simulator to understand probable valuation and sales for a set of features. And, this is how you conclude the features of your new smartphone so that it sells well. Let’s explore some conjoint analysis tools below:

Conjointly 

Conjointly is a powerful platform that allows you to make confident business decisions by performing conjoint analysis. It comes with a simple interface that both novice and seasoned users will find to be helpful.

Using this tool means not depending on only the old sales data anymore — It offers all new insights to determine product features and optimal pricing. Thanks to the competitive context simulation, you can seamlessly predict the effects of changed features, claims, and product pricing.

In the product portfolio of Conjointly, you can prioritize products and concepts that are more valuable. Moreover, this tool provides you with actionable insights for your company. Whether you need to analyze customized and complex projects or automated agile experiments, the software can do that for you.

Using this application, users can gather quality-assured respondents worldwide. Also, it assists in developing the study with support from experienced researchers. Hence, it becomes easier to apply the results of the studies with the top reporting tools. 

Additional features of this step-by-step application include customizable templates, design tool demonstrations, personalizable text and images, product concept ranking, and more.

1000minds

1000minds brings you award-winning software to find out what matters to the customers and the stakeholders. With its help, companies can discover what customers think about certain features or characteristics of their products and services, along with the management processes. 

This tool is beneficial for domains such as market research, policy-making, management processes, and surveys of national and international markets. It lets you set up and manage your survey without any complex design issues. 

As you use the intuitive technology of this software, you will notice a boost in the survey response rates and get data of high quality. Businesses can use the data to develop better products and policies for more significant market share and investment. 

Its easy integration feature allows you to merge the tool with various survey panels and tools. The results become available on this platform when the people finish their surveys.

QuestionPro

QuestionPro is a conjoint analysis tool that contributes to businesses with market research and product optimization. It is packed with useful features to help you find out what people want in your products so that you can invest resources accordingly.

With this tool, designing a survey only takes minutes with 300+ free survey templates and a drag-and-drop interface. Securely collecting insight-rich data is also possible while complying with laws regarding data privacy and security.

QuestionPro also offers you the power filter data based on demographics and other attributes. Furthermore, you can generate 30+ online reports with this tool and export those in Excel, Word, SPSS, and PDF formats.

Enterprises can integrate it with other business applications, including Microsoft Dynamics CRM, Tableau, SalesForce, Zapier, and Marketo.

SightX

For automated conjoint analysis, you can rely on the robust software SightX. With its help, you can optimize your product features and decide on pricing even before the product launch.

This is a platform for end-to-end market research that businesses can use for project designing, survey distribution, and real-time data analysis. Whether it is about consumer products or subscription bundles, you can optimize your product features and pricing with SightX.

Wrapping Up

By going through an in-depth discussion on the conjoint analysis method, you might have already understood that it is an extremely useful analytical tool. It helps you in finding out the product/service features that the customers like the most. 

Once you know your consumers’ liking, you can improvise your offerings aligning the users’ interests. Also, you can weed out unused functionalities and save money on product development. 

The above basics of this survey-based statistical technique will help you in planning a conjoint analysis project. And the above web apps will help you execute the conjoint analysis for a product/service and acquire insights for product development and improvement cycles.

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