How To Conduct Pricing Research Using Choice-Based Conjoint Analysis

choice based conjoint pricing research

This blog explores what choice-based conjoint is and how the advanced method can be effectively used for insightful pricing research. 



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What is choice-based conjoint analysis in pricing research?

Choice-based conjoint analysis (aka discrete choice conjoint analysis) is a research approach that presents respondents with several hypothetical product profiles and forces them to make trade-offs. Automated analysis then helps brands identify an optimal mix of product attributes.

The tested product profiles are made up of attributes that may be common to all the hypothetical products, but which differ in their nature; these differences within attributes are called levels (i.e. price levels 1, 2, 3 would be all different price tiers).


There might also be attributes that are present in some products and not in others. For example, if a brand were comparing cell phone products, all of them might have different screen sizes, battery life, and storage capacities, but only some might have a home button, metallic details, or wireless charging capabilities. The goal is to include attributes (and levels of them) that consumers would realistically compare in a shopping scenario.

In pricing research, choice-based conjoint analysis takes a value-based approach, determining how important price is relative to other product features. It also determines which other features drive up price (or drive it down), providing insights into the willingness to pay for a product (and individual features within it) at a certain price.
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Why you should conduct pricing research

Price is central to any business’s offer. No matter how all-encompassing your product may be, if it’s too expensive (or, too cheap!) it will impact sales and market share. The price point of a product says a lot about what consumers might expect from its quality. While consumers often look for a good deal, if a product is priced too low they might question its credentials. Similarly, while consumers generally want high-quality products, they’ll have a limit on what they consider ‘worth’ their money.


To find the sweet spot for pricing, brands conduct pricing research to get an idea of consumers’ willingness to pay and which elements of a product they may be inclined to spend more or less on. Without conducting pricing research ahead of a product launch, you risk bringing a product to market that doesn’t align with consumer expectations or spending habits. Knowing what consumer preferences and expectations are mean you can build data-backed retail pricing strategies that both you and your target audience will be happy with.
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Why use choice-based conjoint for pricing research?

Choice-based conjoint in the context of pricing research provides strategic guidance for brand managers and their wider team to create a product with the most desired features at a price that consumers are willing to pay.

In a conjoint analysis, different price points are typically just one of several product attributes that make up each product, so respondents don’t actually know that the research is primarily concerned with price; this helps mitigate survey bias (vs. asking flat out about pricing in a U&A survey question). This also means it mimics a real shopper experience - rarely do consumers only consider price when making a purchasing decision between different products. Rather, their decision is made based on a multitude of product attributes - which is where choice-based conjoint excels.


Another benefit to using conjoint analysis for pricing research is that it forces respondents to focus solely on the products and features (rather than marketing, promotions, or other influences). While these are all genuine factors that shoppers might consider, it allows the brand to first focus on product optimization before moving on to a marketing strategy for the product.


In contrast, other types of surveys - like U&A studies, can introduce bias in how they ask consumers about the importance of product pricing. For example, asking a consumer ‘Would you buy snack X at $1.95/$4.65/$10.50?’ etc. might give an indication of the value that a consumer attaches to that snack in isolation, but it doesn’t provide context into other product elements that could influence their overall decision. Focusing on price as the only factor of a product sometimes puts too much attention on price and doesn’t reflect how consumers might consider products in real life.

Conjoint analysis surveys can be used just as effectively for new products (i.e. fine-tuning product design and working out optimal pricing during product development) - as they can for existing products that need refreshing. Brands can also use conjoint on existing products to see how sensitive consumers would be to price changes.
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How to find consumers’ willingness to pay using conjoint analysis 

So what does choice-based conjoint pricing research look like in practice? Below are two examples of how you would measure willingness to pay using this advanced method.


Imagine you’re a shampoo brand and you’d like to explore how much consumers are willing to pay for a new product. Using a choice-based conjoint analysis, you’d break down components of your product into key attributes - texture, fragrance, look, package type, and, price - and test your planned configuration with different price points to see how the share of preference is impacted and to understand elasticity among your target audience. This analysis can be made even more impactful by including several key competitors to understand share and pricing in a competitive context (i.e., the ability to steal share at different price points).


Now, imagine your shampoo brand has an established product and is considering increasing price. Conjoint analysis has you covered here too! You can keep the current in-market product configuration static and increase price to see how your share is impacted (including competitors can give you an idea if a pricing increase will cause attrition to competitive brands). If share is negatively impacted, conjoint offers the ability to swap in various levels of the tested attributes to understand if additional value can be added to the value proposition to support the higher price point without negatively impacting share.

Conjoint analyses that offer the ability to navigate between price points (i.e., to explore any price point between the lowest and highest tested, not just the specific price points entered as levels in the price attribute) are especially powerful in both of these scenarios, as interpolation of price offers a great degree of flexibility without the need to test hundreds of discrete price points.
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How else can you measure willingness to pay?

Conjoint analysis is a great research method to use for understanding willingness to pay - and many consider conjoint studies the strongest of any other pricing methodology. However, there are other approaches if conjoint isn’t an option.


Price Sensitivity Meter (PSM) - also known as Van Westendorp, is another common pricing method to indicate the right price level for optimum sales. This advanced research method asks respondents to name the price point that is:

  • Too expensive they wouldn’t consider buying the product

  • Too cheap they would question the product’s quality

  • Expensive, but they would consider buying the product

  • A great price, they would consider the product a bargain

The aim is to identify the optimal price point - the price at which a product is not considered so cheap that the quality is in question, nor so expensive that consumers won’t buy it. Along with the optimal price point, PSM points to other helpful pricing metrics such as the indifference price point, and the price range.

Read more on Price Sensitivity Meter here.
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How to use quantilope to conduct advanced method pricing research

Identifying the optimal price point is one of the most important business decisions a company has to make. quantilope makes those difficult decisions easier by providing automated, advanced pricing research methods.

quantilope’s fully automated choice-based conjoint analysis helps brands decide which attributes to include in a final product and how to fairly price it. With access to real-time charting and a live insights dashboard with automated statistical testing, brands set themselves up for a successful pricing strategy to bring a product to market.

If conjoint doesn’t quite fit your pricing needs, quantilope also offers an automated price sensitivity meter to help with price optimization. As mentioned above, this is a great way to identify the optimal price point for a product whose attributes have already been decided upon, to see what consumers would pay for it in the real world.

Whichever methodology you use, quantilope’s automated pricing methods are flexible, intuitive, and ready to drop into your survey with a click of the mouse.

To learn more about conjoint analysis, price sensitivity meter, or any other advanced method quantilope offers as part of its Consumer Intelligence Platform, get in touch below!


Get in touch to learn more about choice-based conjoint for pricing research!



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