Setting the optimal price can be challenging. Many companies simply add a mark-up to their base cost and leave millions on the table without ever knowing it. Smart companies engage the buyer to help set an optimum price point.
We prefer two approaches. The first is already demonstrated in the chart above. Price simply becomes a variable in the different feature sets buyers evaluate. Once the conjoint data is out-putted marketing and other relevant departments can make quick calculations on what the base cost of each the optimized products is and again set their pricing strategy.
Another approach allows the buyer to assess price relative to the perceived value of the product or service. Buyers are required to answer four unstructured questions:
“Build it and they will come” only works in movies like “Field of Dreams.” And yet, that is that exactly the new product development philosophy that many companies follow. Let’s ignore what buyer’s needs are and make what we can.
Product optimization methods are different by product category. Food and beverage products are typically optimized using a series of sensory tastings across a range of alternative product configurations which vary by the ingredient mix, texture, aroma, mouth feel etc. These types of test are typically conducted among professional testers during the early stages of product development followed by consumer taste test in in-home use test. These types of tests are typically conducted unbranded.
Here is a little fun fact. Recall the heavily publicized New Coke vs. Pepsi taste testing. In this scenario research participants actually tasted three products: Classic Coke, New Coke and Pepsi. Based on this research, the decision was made to launch New Coke and the results are still talked about today. Was the research incorrect? No, the research was right. New Coke was launched because in blind testing its flavor profile came closer to matching the Pepsi taste profile. However, the research also indicated that consumers still preferred the taste of Classic Coke. The morale – be careful what you wish for.
In hard goods, both consumer durables such appliances, automobiles and so forth, and industrial or high tech products some form of conjoint research is recommended. Some people also refer to conjoint analysis as trade-off analysis, and as the name implies, the research process asks members of the target audience trade-off between different product features. Statistical modeling is then applied to the trade-off data to predict consumer purchase behavior when presented with a complete set of features and benefits for alternative configurations of the same product. Conjoint analysis also guides marketers strategically with respect to what they want the product achieve in the market place. Products and be developed which maximize market or which optimizes the product’s gross margin. At the same time, alternative product configurations can be developed to meet buyer needs across different channels, buyer segments, levels of quality, etc. Below is a highly simplified example of conjoint research we conducted for an ISP when deciding how to launch their first internet offering.