MBA in 2 minutes | Lesson 23: Pricing using Conjoint Analysis

We will be solving practical challenges through MBA concepts. No theory only applications!

As a founder, marketer and a management consultant, we are often tasked with identifying optimal pricing of a new product or service launch. While I have previously covered the 3 main methods of pricing (cost based, value based and competitor based), in this lesson we will delve deeper into 'value based' pricing by using a analysis called, Conjoint Analysis.


Pricing using Conjoint analysis is globally used by hotels (Courtyard by Marriott), automobiles (Ford) and many other big corporate giants. So lets dig deep on this beast called Conjoint Analysis.


Step 1: Identifying attributes impacting value of the product

Imagine you are tasked to price the new ipod using value based pricing. The first step you need to do is identify atributes that users will value in the product such as-

  1. Brand value

  2. Capacity (storage)

  3. Battery life

  4. Display (color)

  5. Warranty

  6. Price

It is critical to understand that one cant solve for the long tail i.e. exhaustive list of attributes as it will unnessary make the exercise unproductive. Hence, it is critical to take a judgemental call and input 20% attributes impacting 80% of the decision making.


Below are few values of an apple v/s generic product on various attributes-


Step 2: Conduct consumer survey and experiments

Post this, the interesting journey starts when we create select profiles by mixing and matching few of the attributes as shown in the below picture. Usually this can be conducted outside stalls in malls and markets. The user is shown variants of products and asked to price it.

The response on "price" for various combination of attributes is recorded.


Step 3: Recording data and finalize pricing via conjoint analysis


The data is usually recorded in binary format (0 and 1) of product varinst.

0 represeting preference and 1 higher preference.

Utility (Value) =α + β Brand Brand + β Capacity Capacity + β Battery Battery + β Display Display

+ β Warranty Warranty + β Price Price


Finally, the data is plotting using linear regression analysis where the numbers represents variables α and β above.

Step 3A- What is the utility to $ “exchange ratio" ?


Exchange rate = ($249 –$99) / 33.6 = 4. 45 $/utility

(When price changes from $99 to $249, utility reduces by β Price)


Step 3B- What is the willingness to pay for the product ?

73.45 utility = 73.45 x $4.45 = $326.85


Hence, the williness to pay is around 325 dollars and we can benchmark it further to nearest competition. Conjoint analysis is very often used by marketing professionals graduated from BSchools. Hope this lessons further aids in breaking any myth around what marketing professionals do and how to leverage such tools without an MBA :)

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©2019 by Shatakshi Sharma | MBA in 2 minutes

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