Marketing science is the application of the scientific method and scientific experiments to the solution of marketing problems.It involves mathematical modeling, simulation, and optimization. Choice modeling, conjoint analysis, latent class regression, logistic regression, factor analysis, discriminant analysis, time-series analysis, and Bayesian statistics are some of the commonly used techniques. The goal is to build simulation models at the micro level (advertising, promotion, etc.) and the macro level (the overall mix of marketing inputs), so that optimal solutions can be derived.
What is the structure of the market for a product or service? Should the market be segmented or not? What are the most useful ways to segment the market? Which market segments represent the greatest profit potential? Which market segments offer opportunities for new products? What positionings and messages resonate with the target-market segments?
What combination of marketing inputs (positioning, messages, media advertising expenditures, distribution channels, new products, sales organization, etc.) will maximize long-term sales revenue or profitability? In effect, what is the optimal marketing model for a company, or a brand, and how and when should this model change?
Positioning is a fundamental element of marketing strategy. What are the viable positioning options? What is the optimal positioning for a brand or service? Which positioning helps support higher prices over time? Which positioning provides the best “air cover” for new products? Which positioning builds the best defense against competitive attack?
What combination of positioning, themes, imagery, music, and colors creates the most effective advertising for a company or brand? Given optimal creative, what media or mix of media will be most effective? What is the optimal level of media expenditures? How should these media expenditures be allocated across time and across markets to achieve maximum effect?
How can promotions be best used to support strategic objectives? How can promotions reinforce the brand’s positioning? What are the elements and messages that create effective promotions for a given brand? What is the ideal timing of promotions in relation to other marketing activities? What is the balance between reach and frequency? How can a brand or business be promoted without resorting to discounting?
New Product Optimization
What role should new products play in the strategic plan? What are the market spaces where new products might be created? What are optimal methods of generating ideas and creating new product concepts? Which new product concepts have the greatest chances for success? How can these new product concepts be optimized? What is the best brand name, the best package design, and the optimal price for the new product?
Product Design Optimization
For an existing or new product, what is the optimal design? Which features, functions, capabilities, colors, finishes, graphics, etc., and at what price, constitute an optimal product? How can these design variables be manipulated to maximize market share or profitability? What are the tradeoffs among the different product design variables? What is the "utility" of each variable?
Product Line Optimization
What is the optimal product line? How many different products (and with what features) should be offered at what price points? What types of products at what prices should fill a vending machine—to maximize sales? What menu items will maximize a restaurant's sales or profits? What product line maximizes sales and minimizes distribution costs?
What is the optimal pricing strategy? What positioning and messages best support this pricing? What product features and service levels go with the optimal price? What events or competitive actions should trigger changes in prices? What is the interaction between pricing and advertising spending levels?
Database Marketing Optimization
What are the motive variables that divide customers into similar groups? How can the direct marketing to each of these target segments be optimized? What themes and messages resonate with each segment? How can the Web be integrated into the marketing plan to maximize efficiency? What is the return on investment (ROI) for each direct marketing campaign?
Customer Service Optimization
What drives the consumers’ perceptions of good service in a given industry? Which variables, if changed, have the greatest impact on perceived service? What is the optimal investment in good service, relative to competing investments? What is the optimal level of service to maximize market share or profitability?
Customer Satisfaction or Loyalty Optimization
The goal is not to maximize customer satisfaction (no company can afford that), but to optimize customer satisfaction and/or loyalty. What are the real drivers of customer satisfaction in an industry? How can these drivers be optimized for an individual company or brand? The answers to these questions are often elusive and can only be answered by carefully controlled experiments.
Sales Force Optimization
What are the optimal number and type of salespeople to maximize market share or profitability? What type of sales organization will be most effective in a given industry? What should the mix of direct and indirect salespeople be? What types of marketing efforts will maximize the performance of the sales force? How should the sales organization vary across different types of geography?
Analytical Consulting Services
Decision Analyst’s strengths in statistics and mathematics, simulation, modeling, and optimization provide the analytical foundation to address complex business and strategy issues.
If your company is facing tough, complex decisions, and wants to improve its marketing strategy and performance, Marketing Science offers powerful analytical tools to help you make the very best decisions. If you would like to learn more or discuss a specific topic with one of our consultants, please contact contact Jerry W. Thomas, President/CEO (firstname.lastname@example.org), or John Colias, Ph.D., Senior Vice President, Advanced Analytics (email@example.com), or call 1-800-ANALYSIS (262-5974) or 1-817-640-6166.