Advanced Marketing Solutions For Strategic Decision-Making

Advanved Research Solutions For Strategic Decision-Making

Advanved Research Solutions For Strategic Decision-Making

THE MARKETING ANALYSTS is concerned with helping clients identify, select and implement successful marketing strategies.   Our intent is to provide our clients with advanced research solutions to improve the quality of strategic decision-making.

Clearly, the right strategic decision-making produces the positive outcomes that every organization seeks.  However, wrong decisions may produce disastrous results.  As example, here are some startling statistics from well-known American retailers:

•             1990 – 2004         Circuit City grew from $2 billion to $9.75 billion.  Five years later, the company filed for bankruptcy.

•             1930’s   Sears Roebuck and Montgomery Ward were about equal in sales and profits.  Twenty years later, Sears was about three times larger than Montgomery Ward.  In 2001, Montgomery Ward closed all of its remaining stores.

•             1991       Walmart surpassed Sears and Kmart to become the largest US retailer.  Today Walmart is the largest retail company in the world and is becoming one of the largest grocers in the US.

While these examples are dramatic, every organization is affected by strategic decisions. Thus every company must plan and act strategically.  You can uncover the information you need through numerous ways—from online research to focus groups to predictive models.  With effective market research, we can help you determine the need for your service or a product’s likelihood to sell, target-market demographics, and determine desirable store locations. To help you meet your target market’s needs, we offer a leading collection of tools, resources and professionals.

THE MARKETING ANALYSTS can help you.

Conjoint AnalysisMarketing Mix ModelsBrand MapsMarket SegmentationProduct Line ManagementSales ForecastsAdvertisement OptimizationData MiningMarket Basket AnalysisCustomer Retention/Predictive Customer Churn

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Ensure The Success Of Your New Product With Conjoint Analysis

Conjoint analysis is a term given to a broad set of marketing research techniques that are used in new product development.  Some of the main types of conjoint analysis include Choice Based Conjoint (CBC), MaxDiff, and Adaptive Conjoint Analysis (ACA).  Because each offers special advantages, THE MARKETING ANALYSTS offers all major types to address the specific requirements of your project.

How Can Conjoint Analysis Help Me?

When the correct conjoint method is used, it is extremely effective determining the optimal set of features that a new product should have and the best pricing strategy.  Conjoint analysis works by simulating an actual purchase experience and explains how people make choices between products and services.  The result is a dynamic market model that determines the best product design and pricing strategy that optimizes profitability, market share and how the behavior of competitors will influence your market position.

How Conjoint Analysis Works

While the conjoint analysis has been used for many years, new varieties continue to be developed that provide more powerful and accurate results.  In a typical study, respondents are asked to make a series of product feature relates trade-offs or choices.  The simple exercise usually asks respondents to select or rank the most preferred alternatives from a selection of competing alternatives.  The analytical analysis is usually carried out using hierarchical Bayesian mathematics.  Because of the flexibility of new conjoint methods, research studies can be conducted by web or paper-and-pencil surveys.

Conjoint analysis can be used to determine what really drives customers to buy one product over another and what customers really value, when the following assumptions are met:

  1. A product (good or service) must be able to be described or represented by a set of attributes that are mutually exclusive.
  2. Consumers view the product as a combination of attributes that can be exchanged for others.  An example is the inclusion of an additional product feature in exchange for a higher price.
  3. The total utility (value) of the product being analyzed is equivalent to the sum of the individual utilities of each attribute.  It is important to realize that several common forms of “conjoint analysis” do not consider nonlinear relationships, particularly interactions among attributes.  Ignoring interaction will lead to bad research results.
  4. Products with a greater overall utility are more attractive than products with lower total utility scores.

When these assumptions are met, conjoint analysis provides quantifiable and actionable data that include:

  • Relative importance for each product attribute
  • Most desirable level of each product attribute
  • Potential market share for the product
  • Market segmentation information

For additional information about conjoint analysis, please visit  and contact us today about our low prices.