No. 30 in a Continuing Series

What If...?
How conjoint-based simulators can help make better product development decisions
As companies attempt to innovate on their new products and services, they are often faced with many difficult trade-offs. Which features should be developed, which are actually worth including, and if developed, how much could be charged for them?

Conjoint analysis is a powerful quantitative tool that can help answer these questions. When used correctly, conjoint analysis can bring great clarity to what are often murky pricing and product or service configuration issues. It can also provide a clearer understanding of how important each feature is, relative to others, in customers’ purchase decisions. And perhaps most importantly, conjoint analysis allows users to predict the actual market potential of hypothetical offerings.

But interpreting conjoint results can be complicated and confusing, and typically requires assistance from a professional researcher. While most conjoint reports answer the most immediate strategic questions, they often provoke many follow-on “what if” questions that are essential to answer before making the final product design or configuration decisions. While conjoint-based simulators have been around for many years, and are often the preferred tool to answer these questions, most are not very intuitive or easy-to-use. These simulators are predominantly designed with professional researchers in mind, making them too clunky and cryptic for people without formal quantitative research training to use. Consequently, most clients remain dependent on their research vendors to extract many of the most valuable insights from a conjoint analysis, which can be highly frustrating and time-consuming.

The following example illustrates these short-comings. Imagine that you are a computer manufacturer interested in producing a new laptop. Now think of the myriad of feature-price combinations that you could offer. To help navigate through these possibilities, you conduct a conjoint analysis to serve as your compass. After the initial research report, you will have a good sense as to which features are preferred and which configurations are likely to be the winners.

And with a better understanding of what each feature is worth, you will need to decide which precise configurations you should offer. For instance, “What if we extended the battery life to 3.5 hours instead of 2 hours, but we reduced the screen size from 17 inches to 13 inches?” Or “What if we only offered a 100GB hard drive instead of a 200GB or 400GB hard drive, but were able to drop the purchase price from $795 to $649?” And perhaps most importantly, “If we do these things, how would they impact market share?” Without a solid understanding of conjoint analysis and their companion simulation models, you would still be dependent on a third-party research vendor to answer these types of questions.

Is there a good solution to this all-too-common problem? We’ve found that a customized spreadsheet-based conjoint simulator works extremely well (see Exhibit 1 for an example). These simulators are easy to use and allow users to input a multitude of potential product configurations that cover all of the relevant “what if” scenarios. Once these various offerings are entered, the simulator returns an estimate of market share, the overall attractiveness of each offering, and the impact of a given price level. The tool is particularly powerful because it is fully customized to an individual client’s needs – meaning that the nuances unique to a particular company and their industry can be accounted for.

AMS has now developed a number of these powerful simulators for clients in a wide array of industries. In each of these models, the user interface is extremely intuitive and easy to use. These characteristics make custom conjoint-based simulators a great tool for managers interested in evaluating an extensive list of product development options – even if it is long after completion of the conjoint study. Managers no longer have to experience the frustration of depending on a third-party to answer the most critical questions in new product development: “What if…?”

—Andrew Wilson
awilson@ams-inc.com

© Copyright Applied Marketing Science, Inc.

Exhibit 1: This exhibit depicts a hypothetical custom conjoint simulator for Netbook Computers. A user would input the appropriate product descriptions (screen size, hard drive size, operating system, etc.) for products currently available on the market along with potential offerings they might be considering. The model then predicts the relative appeal and market share for each offering.