Conjoint Analysis: A Powerful Tool for Business Decision-Making 

Firms must know how customers value their products to build a successful business. Making sales, marketing, pricing, and product development decisions is imperative. Conjoint Analysis helps in this regard. 

Understanding what influences consumers can be very useful for firms to become more customer oriented. Hence, market researchers are always on the lookout for ways to understand consumer psychology.  

For every brand, each of its products has multiple features and utilities. How do businesses know which features are most valued by customers? In what areas should businesses concentrate their efforts? 

Conjoint analysis helps find an answer to these questions. Businesses can confidently make data-backed decisions through conjoint analysis. 

What is Conjoint Analysis? 

The conjoint analysis uses statistical analysis tools to create a hierarchy of consumer preferences. It’s based on the principle that every product is a set of attributes that impact its perceived value. It highlights the most desired features and components of products and services. Market researchers use conjoint analysis to understand consumer wants. 

It relies on survey methods to gather data. Such surveys ask consumers to rank specific features according to their importance. Responses to these surveys are in numerical format. After analyzing it, researchers assign a value to each component. 

For example, if one wants to buy a mobile, there are many features one must consider.  

• Display size 
• Brand value 
• RAM 
• Camera 
• Storage 
• Battery life 
• Budget 
• Usability 

But since no mobile is perfect, there will be tradeoffs. Analysis mimics such tradeoffs. Consumers who buy budget phones cannot expect to get the latest processors or high-end cameras. 

Consumer preferences differ across income levels and geography. A consumer from a low-income country may value budget over specifications and vice versa. This means it is not profitable for luxury mobile brands to enter such a market. The same market may offer great opportunities to other cheaper mobile brands. Thus, firms can use conjoint analysis data to understand how consumers think. 

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What Are the Areas to Use Conjoint Analysis? 

Conjoint Analysis in Pricing 

Pricing is critical to ensure that a maximum number of consumers buy a product. But a pricing strategy may get more complicated when a product has many features. Which features would consumers be most willing to pay for? Conjoint analysis insights help answer this question. 

For example, a food delivery app planning to create a premium service should know what its consumers value most. Since subscribing to a premium service would be costly. If its customers value fast deliveries over discounts, then the premium service should be around that. 

Conjoint Analysis in Marketing and Sales 

In today’s hypercompetitive market, sales, and marketing are needle movers for most businesses. Conjoint analysis results help companies to narrow down the right marketing and sales plans. 

For example, if a coffee shop owner finds out that customers value two things most about his product. First is the taste of the coffee and the fact that their coffee is served in biodegradable glasses. With this in mind, the coffee shop owner can market his coffee as “Tasty Eco-friendly Coffee.” This may drive more sales for the product. 

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Conjoint Analysis in Research and Development 

The R&D department of a company is often the most capital-intensive business unit. Products in the pipeline and future plans for developing current products are non-negotiable for businesses. R&D efforts can be prioritized and shaped using conjoint analysis. 

For example, Tata discontinued its flagship vehicle Nano because of a lack of public interest. Despite a cheap marketing campaign, Indians did not buy the car. Instead, they focused on developing affordable EVs since that draws most people. 

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How does Conjoint Analysis Work? 

Conjoint Analysis works in 3 simple steps as follows: 

Breaking Down Products into Attributes 

The first step is finalizing a product’s or service’s attributes or features. These attributes should be outstanding and influential. For example, a smartphone has the following parts or components: 

• Brand 
• Operating system 
• Camera 
• Model 
• Network connectivity 
• Body design 
• Price

Consumers consider these features when making buying decisions. There is a wide range of preferences among audiences. Depending on the individual’s preferences, each attribute is marked. It may matter little to someone what brand they choose. Others, however, may find it appealing. Therefore, breaking down product specifications is important to know that X percentage of people like products. 

Conducting Survey 

The second step is to gather consumer preference data for these features. The goal of such a survey is to achieve a strategic goal. Consumers are asked to choose between the options available to them. These options contain varying features. 

Examples of such options can be the following— 

• Option 1: Samsung Phone with an outdated OS, 5G network, and priced at ₹30,000 

• Option 2: Apple Phone with an updated OS, 5G network, and priced at ₹90,000 

• Option 3: Oppo Phone with an outdated OS, 4G Network, and priced at ₹12,000 

There are certain tradeoffs associated with all of these options. In order to get better quality, consumers should be prepared to pay more. But will they be willing to pay more is what business researchers have to determine through conjoint analysis. 

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Quantifying Results 

The third and last step is to quantify the results of the survey. 

After analyzing survey responses, a researcher can decide what company, model, and price consumers prefer to buy. Suppose 50% of consumers choose to buy a cheaper phone. In that case, that suggests— price is the deciding metric of consumer decisions. Similarly, if consumers choose other attributes more often, those specific items are classified as the more preferable attributes. 

How to Interpret Conjoint Analysis? 

Understanding Preference Scores 

Researchers are left with a preference score once the results are quantified. Understanding these preference scores is essential. The higher the score, the better.  

It means that the score represents how preferable an attribute is to the consumer. Preference scores highlight the utility of a feature. The utility determines a feature’s value and desirability. 

Attribute Importance 

All attributes are not equally important. Some have a disproportionately huge impact on other characteristics. This is why a classic output of conjoint analysis known as attribute importance is used.  

When all attributes are considered together, they form 100% importance. Conjoint analysis results can be interpreted better by understanding which points are essential. 

Market Simulations 

Market simulations are similar to simulation games. A market test is meant to give an idea of how a potential buyer will receive a product.  

One can create many market scenarios to understand consumer reaction to a product being put out in the market. Various pricing formulations and product models can be tested using market simulations. 

Conclusion 

Conjoint analysis is a valuable decision-making tool for marketers and product leaders alike. This analysis can help them avoid wasting precious resources on ill-informed decisions. Knowing one’s consumers is the first step to satisfying them.  

It is a powerful tool businesses can use to gain a competitive advantage by understanding what their customers truly value. Companies can leverage this information to make data-driven decisions that increase customer satisfaction and profitability.