Advanced Analytics
Gooley Group brings deep experience across a broad spectrum of sophisticated marketing research and analytics tools — applied to your most pressing business challenges.
Marketing Mix Modeling
Typical questions
What would happen if I stopped all TV ads? How can I forecast the effect of a price cut on sales?
Our approach
We deploy sophisticated econometric and time series techniques such as Autoregressive Distributed Lag Models and Bayesian Shrinkage to derive the impact of each component of the marketing or media mix on awareness or business results — with deep experience across financial services, automotive, and consumer packaged goods.
Discrete Choice Modeling
Typical questions
Which features should be included in our product? What is the optimal price to charge?
Our approach
We typically use innovative conjoint and choice experiments to quantify the impact of varying features, pricing, and brand equity on consumer choice behavior at the individual level.
Product Line Optimization
Typical questions
Given limited shelf space opportunities, which varieties should I offer to reach the most customers? Are there products that I can eliminate from my line?
Our approach
We use TURF and Bundle Optimization Analysis to determine the line of products that will maximize consumer appeal (reach) with the fewest varieties offered, and to measure the incremental value to overall reach of each variant tested.
Message Preference Modeling
Typical questions
What messages resonate with my target segments? What attributes are important to them? Which features do they prefer?
Our approach
We utilize Maximum Difference Scaling to assess the relative importance and desirability of different items and attributes — as well as the magnitude of differences in importance between attributes — without the shortfalls of traditional rating scales.
Segmentation
Typical questions
How do I identify my most profitable customers? Which prospects are the most attractive? Which segments should I target?
Our approach
We utilize advanced statistical techniques such as Latent Class segmentation to uncover heterogeneity in consumer attitudes, preferences, behavior, and demographics — helping identify the most profitable and attractive segments for targeting.
Predictive Modeling
Typical questions
How do I prioritize my prospects based on potential to convert to a customer? How do I identify and rank order the right customers to cross-sell to?
Our approach
We employ CART, MARS, Mixed and Nested Logit Models, Bayesian methods, Nearest Neighbor Models, and hybrid modeling techniques to develop accurate models for prospecting, cross-selling, and customer retention.
Customer Loyalty Analysis
Typical questions
What attributes of customer service are most important in retaining customers? Do these attributes differ by market segment? By delivery channel?
Our approach
We utilize sophisticated statistical models — including Path Analytic Techniques and Structural Equations Models — to determine the direct and indirect influences of product and service performance attributes on customer loyalty and mediator variables such as value, reputation, and customer satisfaction.
Brand Equity Modeling
Typical questions
What brand levers should I pull to increase the equity of my brand? Which levers can I de-emphasize? Are product and service quality more or less important than brand imagery?
Our approach
We utilize sophisticated statistical models, including Path Analytic Techniques and Structural Equations Models, to determine the direct and indirect influences of various brand attributes on brand equity.
Market Structure Analysis
Typical questions
How do my consumers perceive my brand in the marketplace relative to my competitors? How can I see this visually represented?
Our approach
We apply the right perceptual mapping technique for your situation — with experience in Multidimensional Scaling, Correspondence Analysis, Discriminant Analysis, and Quadrant Analysis — to vividly illustrate marketplace perceptions.