Day 11- Team F( Sidharth )

 We started off the 9 ‘o’ clock session with a very interesting topic ‘Conjoint Analysis’. It is one of the very important tools of Business Analytics and performs the analysis in a much better and concise manner. So what exactly is Conjoint Analysis? It is one of the most widely-used quantitative methods in Marketing Research. It is used to measure the perceived values of specific product features, to learn how demand for a particular product or service is related to price, and to forecast what the likely acceptance of a product would be if brought to market.

           

Respondents usually complete between 12 to 30 conjoint questions. The questions are designed carefully, using experimental design principles of independence and balance of the features. By independently varying the features that are shown to the respondents and observing the responses to the product profiles, the analyst can statistically deduce what product features are most desired and which attributes have the most impact on choice. In contrast to simpler survey research methods that directly ask respondents what they prefer or the important of each attribute, these preferences are derived from these relatively realistic tradeoff situations.

But the direct survey question "how much would you pay for xyz?" is unreliable and misleading. So instead, we ask the consumer's opinion on a series of products with differing features over a range of prices. Our techniques then use regression analysis to compute mathematical values that explain consumer behavior -  how much value is placed on price, or location, or features, etc. and then correlate this data to demographic, lifestyle, or other consumer profiles.

Decoding of the Conjoint Analysis Results:

Here’s an example of a survey regarding the consumer tastes in ice creams. The data is collated as per the consumer preferences.

Given the consumers' ratings of all 16 diverse combinations, the software package computes a mathematical regression to tell us how important each of the five factors is to the individual responding consumer, and to the group of responding consumers as a whole.

According to the results shown to the left (actual output from the online survey), we'd know that consumer X bases 47% of his decision on price, 23% on the flavor, 19% on the freshness, and is less concerned about the container or healthiness. We also learn get a relative ranking of the different flavors, as shown in the lower graph.

Maybe older customers who eat ice cream regularly are more concerned about healthiness.   Maybe younger consumers don't really care about the cone after all.  Perhaps those who work in a nearby office building and pass by for a snack really appreciate the homemade fresh ingredients.  All of these facts will be mathematically predicted using conjoint analysis. The end result is a quantitative, robust analysis of what consumers really want, with each attribute evaluated in the context of the others, incorporating the trade-offs that ultimately project the greatest influence on consumer behavior.

- By Sidharth 

Team F