DDW ADVANCED ANALYTICS

The design and execution of a successful market research project parallels many creative efforts - from building a home to producing a work of art. If you start with a solid plan that meets your needs, keeps within your budget, uses the best materials and demands skilled workmanship, you will be pleased with the result. If you fail to plan effectively, purchase shoddy materials or 'black box' solutions, the effort can be painful and disappointing.

With proper planning and design, advanced analytic tools can make an otherwise mind-boggling research problem into a source of pride and accomplishment.

• Designing a creative, efficient approach to your market research issues

  Whether your goal is to assess and build your brand's equity, better understand your customer, enter a new market or assess your progress over time, DDW has built state-of-the-art market research approaches and products to fulfill that goal. These form a starting point for the design effort. We bring these approaches and our experience in using them in a broad range of situations to the table when we sit down to plan your market research project.

  We will not present a 'black box' solution. We will probe for your issues, suggest alternatives, describe what has worked in similar situations and tailor the approach to your issues, budget and timing.

  Thorough planning begins with the analytic approaches we employ. Advanced modeling and multivariate tools allow us to create research plans that are succinct and to the point. The Advanced Analytic group works with you and your DDW project team to incorporate these state-of-the-art solutions into your project design.

• Building a solid market research foundation

  The foundation of our Advanced Analytic and Modeling efforts is the individual respondent. In the past, multivariate work addressed the marketplace descriptively, as a homogeneous group. We know that your marketplace is diversified. And we know that descriptive statistics, while interesting, are not sufficient to produce proactive decisions.

  Advanced computing power and new statistical techniques provide the capability of bringing statistical analysis to the individual respondent level. Whether we are trying to understand what drives a consumer to choose your product/service over the competition or we are building a concept, product or service to meet customer needs, we calculate our models for each respondent, and then aggregate to the market.

  In this way, we incorporate the diversity that exists in your market. Importantly, this approach provides predictive power to understand how a customer could react to changes in the market and in your offer to them.

• Drawing from the best available analytic tools

  We develop and update our analytic toolbox in a number of ways. First, we evaluate and incorporate the work of leading academics and statistical software developers to meet our needs. The approaches in our toolbox include state-of-the-art work in Hierarchical Bayesian analysis, Latent Class analysis, Conjoint/Choice modeling and Maximum Difference Scaling.

  Second, we adapt and refine the standard statistical tools used in perceptual mapping, segmentation and descriptive statistics.

  Third, our experience in analyzing a broad spectrum of markets has led to the development key measurement tools such as Value Bead, Customer Loyalty Index and the Adaptor spectrum.

• Adapting the tools to your needs

  You will see these analytic tools incorporated throughout our research approaches. For example, advanced Choice modeling tools form the basis for our PriceDeveloper and OptionDeveloper approaches. We have adapted Maximum Difference Scaling for use in LineDeveloper.

  More importantly, when we are building a design to solve complex research problems, such as we might see in pricing structure problems and market structure analyses, we draw from and adapt a wide range of tools to meet the problem at hand.

  Your problem is not force fit into our solutions. We adapt our tools to solve your problem.

• Employing the tools effectively

  It is one thing to have a tool at your disposal and quite another to use it effectively. Consider market segmentation, for example. We regularly use both K-means segmentation and Latent Class segmentation approaches as our preferred tools. When should one be chosen over the other? What data considerations play into the decision? When should responses be normalized or centered? Should we be using individual items or factor scores? Should we be segmenting across multiple questions or use a single question with others as profilers? Should we segment separately for alternative customer groups? All of these questions, and more, need to be considered and addressed to insure a successful segmentation.

• Producing results that lead to proactive decisions

  Whether your issue is market segmentation, communications development, product development or customer loyalty, DDW analytics are designed to lead to business action. How? Here are a few examples.
  
  DDW interactive Excel-based simulators allow you to play 'what-if' scenarios in pricing, line optimization and new product/service development. Try some new pricing strategies, reconfigure your product line, revamp your product or predict competitive action. These simulators will allow you to query and answer questions long after the study is completed. Many of our clients use these simulators to further incorporate financial considerations to estimate potential profitability of their actions.
  
  Excel-based leverage models are incorporated into our LoyaltyBuilder and EquityBuilder approaches. These allow you to evaluate alternative customer retention strategies and the impact of potential actions on your brand's equity in the marketplace.
  
  Your DDW project team will make sure that the models are easy to use and easy to disseminate to your core team.

Karen Buros, Director of Advanced Analytics

Ms. Buros has more than 25 years experience in the design and analysis of marketing research studies. She focuses on the application of multivariate and modeling techniques to research issues, specializing in customer satisfaction modeling, conjoint analysis, price elasticity models, market segmentation and market structure.

Ms. Buros has served on the program committee for the Advanced Research Techniques Conference for the AMA, has given tutorials on the use of Hierarchical Bayesian regression and conjoint pricing approaches at industry conferences and has presented papers at both ESOMAR and Sawtooth Software conferences on advanced research approaches.

Prior to her affiliation with DDW, Ms. Buros headed the Customer Satisfaction Division at Research International where she also headed developmental research activities for North America.

Ms. Buros holds a BS and MS from Northwestern University, Medill School of Journalism, focusing on Marketing Research and Statistics.