New Product Development and Conjoint Marketing Research
New product development research and conjoint marketing research are tools that help managers assess future profitability and understand situational market variables.
Marketing managers are often faced with difficult tasks directed at assessing future profitability, sales, and market share for new product entries or modifications of existing products or marketing strategies. To be successful, market research is essential for competitive evaluation and strategic positioning. Specifically, customer research is needed to best understand the impact of situational market variables. Forward Analytics offers new product development research and conjoint marketing research to help our clients understand and execute important business decisions.
Real enterprise problems can be addressed and solved using the methodologies of conjoint marketing research. For instance, we can help you construct a strategic marketing plan that takes into account how specific customer goups will react to a new product, at which price points, and how the competition is likely to behave. First, let's take a moment to explain how conjoint work anyways?
Conjoint analysis is a multivariate statistical technique used to measure consumer preference of multi-feature product or service alternatives. A custom research study is designed to show how various elements of a product can be selected to predict customer preferences for those elements. Conjoint assumes that when a consumer makes a decision about a product, the decision is based on trade-offs among product characteristics. Since any one product probably will not contain everything the customer wants at a price they are prepared to pay, the customer has to decide which features they need or want the most and which they are prepared to trade-off.
Conjoint analysis allows the researcher to simulate real world consumer decision-making processes by designing product profiles incorporating various features, or attributes, with each attribute having two or more attribute levels. Like Customer Value Analysis, conjoint marketing research can show the weight of importance of each product attribute.
How to Identify and Rank Attributes
There are two methods of performing conjoint analysis: full profile or an orthogonal array. The full profile method generates every possible profile, given the attributes of interest. While this type of conjoint analysis is practical for products or services with only a few attributes and only two levels per attribute, it becomes quite cumbersome to evaluate products or services with more attributes and more than two levels per attribute.
For instance, if your range of features incorporates 8 attributes, with each attribute containing 2 to 4 levels. These parameters generate 1,536 possible profiles, a number too high to expect any sort of meaningful evaluation by the targeted audience. Therefore, when the product or service analyzed has more than a few attributes and each attribute has more than two levels, researchers will often use a subset of all possible profiles. This subset is called an orthogonal array.
An orthogonal array assumes no interaction exists between attributes and focuses strictly on the level of consumer preference for each of the attributes independent of one another. In this case, an orthogonal array narrowed the number of service profiles down to 16, a significantly more manageable number for customer research.
Once the service profiles have been generated, respondents are asked to rank each of them in order of personal preference. The results of this research are analyzed using the conjoint procedure. This procedure derives a level of importance for each attribute and a utility score for every level of each attribute. Levels of importance and utility scores are derived for each individual respondent, and levels of importance and utility scores for the entire sample are calculated by averaging the individual scores. The level of importance for each attribute is calculated by taking the range of the utility scores for each attribute and dividing it by the sum of the ranges of all attributes. The level of importance coefficient, therefore, measures on a proportional scale (levels of importance for all attributes will total 100) the relative importance of each of the attributes.
Conjoint Analysis requires a custom research study with custom data collection. Forward Analytics' market research consultants can work closely with you to design a consumer market research study, specifically crafting a marketing research questionnaire to employ to your customers and potential customers.
With the client's knowledge of their markets and products and our expertise in marketing research questionnaire design and methodology development, we design a detailed consumer market research survey. Forward Analytics' market research consultants will work closely with you regarding the control product attributes (e.g. price, ease of use, etc.) and attribute levels (e.g. price ranges, controls or easy-to-read manual, etc.) to be included in the conjoint analysis and consumer market research.
The SPSS conjoint analysis will show such things as which combination of features is most preferred, which particular features most influence preference of the total product, and the relative importance of each feature. More importantly, the system allows us to enter simulations after all of the data is collected and analyzed. We will be able to specify products with attribute levels you can provide and test which are the most preferred. Our marketing research consultant will explain how to implement the results into your strategic market plan.
Forward Analytics' new product development research and conjoint marketing research will benefit your strategic marketing plan by factoring:
Conjoint marketing research is an excellent resource for understanding how choices are made and consequently the importance of price. For some, conjoint analysis is the only way of carrying out pricing research. However, conjoint analysis is a more technical form of customer research and requires higher levels of design skills. If pricing research is to be conducted it is often advantageous to include it as part of a broad conjoint study or new product development research study.
Our conjoint research will help you predict:
Optimal Price Levels
Customer Switch Rates
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